tophat 2.1.1+dfsg-2+b2 / usr / bin / tophat-fusion-post

#!/usr/bin/env python


"""
tophat-fusion-post

Created by Daehwan Kim on 2011-05-05.
Copyright (c) 2011 Daehwan Kim. All rights reserved.
"""

import sys, getopt, warnings
import os, subprocess, errno
import copy
import string, re
import random
from datetime import datetime, date, time
import math
from collections import defaultdict
from intervaltree import Interval, IntervalTree

use_message = '''
TopHat-Fusion

Usage:
    tophat-fusion-post [options] <bowtie_index>
    
Options:
    -v/--version
    -o/--output-dir                <string>    [ default: ./tophatfusion_out ]
    --num-fusion-reads             <int>       [ default: 3                  ]
    --num-fusion-pairs             <int>       [ default: 2                  ]
    --num-fusion-both              <int>       [ default: 5                  ]
    --max-num-fusions              <int>       [ default: 500                ]
    --fusion-read-mismatches       <int>       [ default: 2                  ]
    --fusion-multireads            <int>       [ default: 2                  ]
    --non-human

    -p/--num-threads               <int>       [ default: 1                  ]

    --no-filter-by-annotation

    --skip-fusion-kmer
    --skip-filter-fusion
    --skip-blast
    --skip-read-dist
    --skip-html

    --tex-table
    
    --fusion-pair-dist             <int>       [ default: 250                ]
'''


class Usage(Exception):
    def __init__(self, msg):
        self.msg = msg

        
output_dir = "./tophatfusion_out/"
logging_dir = output_dir + "logs/"
tmp_dir = output_dir + "tmp/"

class TopHatFusionParams:
    def __init__(self,
                 keep_tmp = ""):
        self.keep_tmp = keep_tmp

        self.num_fusion_reads = 3
        self.num_fusion_pairs = 2
        self.num_fusion_both = 0
        self.max_num_fusions = 500

        self.fusion_read_mismatches = 2
        self.fusion_multireads = 2

        self.is_human = True

        self.num_threads = 1

        self.filter_by_annotation = True
        
        self.skip_fusion_kmer = False
        self.skip_filter_fusion = False
        self.skip_blast = False
        self.skip_read_dist = False
        self.skip_html = False

        self.tex_table = False
        
        self.fusion_pair_dist = 250
            
    def check(self):
        if False:
            die("Error: arg to --num-threads must be greater than 0")

    def parse_options(self, argv):
        try:
            opts, args = getopt.getopt(argv[1:], "hp:o:", 
                                        ["version",
                                         "help",  
                                         "output-dir=",
                                         "num-fusion-reads=",
                                         "num-fusion-pairs=",
                                         "num-fusion-both=",
                                         "max-num-fusions=",
                                         "fusion-read-mismatches=",
                                         "fusion-multireads=",
                                         "non-human",
                                         "num-threads=",
                                         "no-filter-by-annotation",
                                         "skip-fusion-kmer",
                                         "skip-filter-fusion",
                                         "skip-blast",
                                         "skip-read-dist",
                                         "skip-html",
                                         "tex-table",
                                         "gtf-file=",
                                         "fusion-pair-dist="])
        except getopt.error, msg:
            raise Usage(msg)

        for option, value in opts:
            if option in ("-v", "--version"):
                print "TopHat v%s" % (get_version())
                sys.exit(0)
            if option in ("-h", "--help"):
                raise Usage(use_message)
            if option == "--num-fusion-reads":
                self.num_fusion_reads = int(value)
            if option == "--num-fusion-pairs":
                self.num_fusion_pairs = int(value)
            if option == "--num-fusion-both":
                self.num_fusion_both = int(value)
            if option == "--max-num-fusions":
                self.max_num_fusions = int(value)
            if option == "--fusion-read-mismatches":
                self.fusion_read_mismatches = int(value)
            if option == "--fusion-multireads":
                self.fusion_multireads = int(value)
            if option == "--non-human":
                self.is_human = False
            if option in ("-p", "--num-threads"):
                self.num_threads = int(value)
            if option in ("-o", "--output-dir"):
                global output_dir, logging_dir, tmp_dir
                output_dir = value + "/"
                logging_dir = output_dir + "logs/"
                tmp_dir = output_dir + "tmp/"
            if option == "--no-filter-by-annotation":
                self.filter_by_annotation = False
            if option == "--skip-fusion-kmer":
                self.skip_fusion_kmer = True
            if option == "--skip-filter-fusion":
                self.skip_filter_fusion = True
            if option == "--skip-blast":
                self.skip_blast = True
            if option == "--skip-read-dist":
                self.skip_read_dist = True
            if option == "--skip-html":
                self.skip_html = True
            if option == "--tex-table":
                self.tex_table = True
            if option == "--gtf-file":
                self.GTF_file = value
            if option == "--fusion-pair-dist":
                self.fusion_pair_dist = int(value)

        if len(args) < 1:
            raise Usage(use_message)
        
        return args

    
# Returns the current time in a nice format
def right_now():
    curr_time = datetime.now()
    return curr_time.strftime("%c")


def reverse_complement(seq):
    result = ""
    for nt in seq:
        base = nt
        if nt == 'A':
            base = 'T'
        elif nt == 'a':
            base = 't'
        elif nt == 'C':
            base = 'G'
        elif nt == 'c':
            base = 'g'
        elif nt == 'G':
            base = 'C'
        elif nt == 'g':
            base = 'c'
        elif nt == 'T':
            base = 'A'
        elif nt == 't':
            base = 'a'

        result = base + result

    return result


def get_chromosome_order(bowtie_index, chrs):
    bowtie_header_cmd = ['bowtie',
                         '--sam',
                         bowtie_index,
                         '/dev/null']

    bowtie_header_filename = tmp_dir + "sam_header"
    subprocess.call(bowtie_header_cmd,
                    stdout=open(bowtie_header_filename, "w"),
                    stderr=open("/dev/null"))

    bowtie_header_file = open(bowtie_header_filename)
    for line in bowtie_header_file:
        index = string.find(line, "SN:")
        if index != -1:
            SN = line[index+3:].split()
            chrs.append(SN[0])
            
    bowtie_header_file.close()


# Ensures that the output, logging, and temp directories are present. If not, 
# they are created
def prepare_output_dir():
    if os.path.exists(output_dir):
        pass
    else:        
        os.mkdir(output_dir)
        
    if os.path.exists(logging_dir):
        pass
    else:        
        os.mkdir(logging_dir)
        
    if os.path.exists(tmp_dir):
        pass
    else:
        try:
          os.makedirs(tmp_dir)
        except OSError, o:
          die("\nError creating directory %s (%s)" % (tmp_dir, o))


def check_samples():
    sample_list_filename = output_dir + 'sample_list.txt'

    prev_list, curr_list = [], []
    if os.path.exists(sample_list_filename):
        sample_list = open(sample_list_filename, 'r')
        for line in sample_list:
            prev_list.append(line[:-1])
        sample_list.close()

    for dir in sorted(os.listdir('.')):
        if string.find(dir, "tophat_") != 0:
            continue

        fusion = dir + "/fusions.out"
        if not os.path.exists(fusion):
            continue

        curr_list.append(dir[7:])

    if prev_list != curr_list:
        sample_list = open(sample_list_filename, 'w')
        for sample in curr_list:
            print >> sample_list, sample            
        sample_list.close()
        return True
    else:
        return False
    
          
def map_fusion_kmer(bwt_idx_prefix, params, sample_update = False):
    def get_fusion_seq():
        seq_dic = {}
        for dir in sorted(os.listdir('.')):
            if string.find(dir, "tophat_") != 0:
                continue

            fusion = dir + "/fusions.out"
            if not os.path.exists(fusion):
                continue
        
            fusion_file = open(fusion, 'r')
            fusion_file.readline()
            for line in fusion_file:
                left_seq, right_seq = line[:-1].split('\t@\t')[2:4]
                left_seq = left_seq.split(' ')[0]
                right_seq = right_seq.split(' ')[1]

                if len(left_seq) < 23 or len(right_seq) < 23:
                    continue

                seq_dic[left_seq[-23:]] = 1
                seq_dic[right_seq[:23]] = 1
            
            fusion_file.close()

        fusion_seq_fa = open(output_dir + "fusion_seq.fa", 'w')
        for seq in seq_dic.keys():
            print >> fusion_seq_fa, ">%s" % seq
            print >> fusion_seq_fa, seq
        
        fusion_seq_fa.close()

    def convert_bowtie():
        bwt_dic = {}
        bwtout_file = open(output_dir + "fusion_seq.bwtout", 'r')
        for line in bwtout_file:
            seq, temp, chr, coord = line[:-1].split('\t')[0:4]
            if seq in bwt_dic:
                bwt_dic[seq].append(chr + ":" + coord)
            else:
                bwt_dic[seq] = [chr + ":" + coord]

        bwtout_file.close()

        kmer_map = open(fusion_kmer_file_name, 'w')
        for seq, chrs in bwt_dic.items():
            print >> kmer_map, "%s\t%s" % (seq, ','.join(chrs))

        kmer_map.close()

    print >> sys.stderr, "[%s] Extracting 23-mer around fusions and mapping them using Bowtie" % right_now()
    if sample_update:
        print >> sys.stderr, "\tsamples updated"

    fusion_kmer_file_name = output_dir + "fusion_seq.map"

    if not os.path.exists(fusion_kmer_file_name) or \
           os.stat(fusion_kmer_file_name).st_size <= 0 or \
           sample_update:
        get_fusion_seq()
        cmd = ['bowtie', '-p', '8', '-a', '-n', '3', '-m', '100', bwt_idx_prefix, '-f', '%sfusion_seq.fa' % output_dir]
        subprocess.call(cmd, stdout=open(output_dir + 'fusion_seq.bwtout', 'w'), stderr=open('/dev/null', 'w'))
        convert_bowtie()

    
def filter_fusion(bwt_idx_prefix, params):
    chrs = []
    get_chromosome_order(bwt_idx_prefix, chrs)

    chr_order = {}
    for chr in chrs:
        chr_order[chr] = len(chr_order)

    ### Compute number of paired reads ###
    # Helper classes
    class GeneEntry(object):
        fields = [('bin', int),
                  ('name', str), 
                  ('chrom', str), 
                  ('strand', str),
                  ('txStart', int), 
                  ('txEnd', int), 
                  ('cdsStart', int),
                  ('cdsEnd', int), 
                  ('exonCount', int),
                  ('exonStarts', lambda x: [int(y) for y in list(x.split(',')[:-1])]), 
                  ('exonEnds', lambda x: [int(y) for y in list(x.split(',')[:-1])]), 
                  ('score', int), 
                  ('name2', str), 
                  ('cdsStartStat', str), 
                  ('cdsEndStat', str),
                  ('exonFrames', lambda x: [int(y) for y in list(x.split(',')[:-1])])]
        
        '''Representation of one line in the refGene.txt file.'''
        def __init__(self, entry_string):
            tokens = entry_string.split('\t') # Assumes tab delimited.
            for (field, type_), token in zip(self.fields, tokens):
                setattr(self, field, type_(token))
            
        def __str__(self):
            return str(self.__dict__)
        
        def __repr__(self):
            return str(self)
        
    class Fusion(object):
        def __init__(self, info, pairs):
            # args should be info[:4] from the fusions.out entry
            # Parse the chromosome string
            self.chrL, self.chrR = info[0].rstrip().split('-')
            
            # Fusion positions
            self.posL = int(info[1])
            self.posR = int(info[2])
            
            # Strand
            self.strandL = info[3][0]
            self.strandR = info[3][1]
            
            # Pairs
            pairs = pairs.rstrip()
            if pairs:
                self.pairs = [pair.split(':') for pair in pairs.split(' ')]
                self.pairs = [(int(p1), int(p2)) for (p1, p2) in self.pairs]
            else:
                self.pairs = []
                
        def get_sign(self, which):
            switch = which == 'R'
            strand = self.strandL if which == 'L' else self.strandR
            if strand == 'r':
                return -1 if not switch else 1
            else:
                return 1 if not switch else -1
    
    class TransMaps(object):
        def __init__(self, fusion, juncs):
            self.fusion = fusion
            self.chroms = (fusion.chrL, fusion.chrR)
            self.maps = {}
            self.starts = {}
            self.juncs = juncs
    
        def add_map(self, chrom, start, stop, strand, fusion_pos):
            self.maps[chrom, strand] = self.compute_transcript_map(chrom, start, stop, strand, fusion_pos)
            self.starts[chrom, strand] = start
    
        def map(self, chrom, pos, strand):
            pos2 = pos - self.starts[chrom,strand]
            the_map = self.maps[chrom,strand]
            if pos2 < 0 or pos2 >= len(the_map):
                # out of bounds - return distance to boundary
                if pos2 < 0:
                    return the_map[0] - pos2
                else:
                    return the_map[-1] + (pos2 - len(the_map) + 1)
            else:
                # position in the map
                return the_map[pos2]
            
        def compute_transcript_map(self, chrom, start, stop, strand, fusion_pos):
            #return list(range(0, stop-start+1))
            
            chrom = self.chroms[chrom]
            w = stop - start + 1
            
            # Find junctions within the interval
            # strict=True means that only intervals entirely contained are returned
            # The junction dict contains both {end: start} and {start: end}
            junctions = defaultdict(set)
            for junc in self.juncs[chrom].search(start, stop, strict=True):
                if junc[2][0] == strand:
                    junctions[junc[1]-start].add(junc[0]-start)
                    junctions[junc[0]-start].add(junc[1]-start)
    
            # Initialize distance vector
            distance = [abs(ii-fusion_pos) for ii in range(start, stop+1)]
            
            # Working out from fusion position, follow junctions
            # First, get positions in the right order
            fusii = fusion_pos - start
            N = len(distance)
            positions = [fusii]
            up = 1
            down = 1
            while len(positions) < len(distance):
                if fusii - down >= 0:
                    positions.append(fusii-down)
                    down += 1
                if fusii + up < N:
                    positions.append(fusii+up)
                    up += 1
                    
            # Second, compute the transcript distance at each position
            # Skip the first position, which is the fusion break (distance=0)
            for ii in positions[1:]:
                ii_ = ii + (1 if fusii-ii >= 0 else -1)
                if ii in junctions:
                    # If ends of junction are further away, ignore them.
                    # If ends of junction are closer to fusion, shorten distance
                    distance[ii] = min( [distance[ii_]] + [distance[jj] for jj in junctions[ii] 
                                                          if abs(jj-fusii) < abs(ii-fusii)] ) + 1
                else:
                    distance[ii] = distance[ii_] + 1
                    
            # Re-sign the distances
            # Users downstream will need to work out fusion arm orientation
            distance[:fusii] *= -1
            return distance
        
    # Helper functions
    def load_junctions(refgene_file, ensgene_file, juncs_file):
        def _load(gene_file, _junctions):
            for line in open(gene_file):
                entry = GeneEntry(line)
                # Iterate over introns
                for start, stop in zip(entry.exonEnds[:-1], entry.exonStarts[1:]):
                    _junctions[entry.chrom].addi(start, stop+1, (entry.strand, 'intron'))
                    
        # junctions are Interval(start, stop, (strand, ...))
        _junctions = defaultdict(IntervalTree)
    
        # Load exons from refGene.txt and ensGene.txt
        if refgene_file is not None:
            _load(refgene_file, _junctions)
        
        if ensgene_file is not None:
            _load(ensgene_file, _junctions)
        
        # Load junctions from junctions.bed
        if juncs_file is not None:
            for line in open(juncs_file):
                if line[:5] == 'track':
                    continue
                chrom, start, stop, _, _, strand, _, _, _, _, overhangs, _ = line.split('\t')
                a,b = overhangs.split(',')
                _junctions[chrom].addi( int(start)+int(a), int(stop)-int(b)+2, (strand, 'intron') )
    
        return _junctions

    def get_transcript_maps(fusion, junctions):
        # Find left side range
        p1s = [p1 for p1, _ in fusion.pairs]
        dL = max([0, max(p1s)])
        dL2 = min([0, min(p1s)])
        
        s = fusion.get_sign('L')
        startL = fusion.posL - s*dL
        endL = fusion.posL - s*dL2
        if startL > endL:
            startL, endL = endL, startL
            
        # Find right side range
        p2s = [p2 for _, p2 in fusion.pairs]
        dR = max([0, max(p2s)])
        dR2 = min([0, min(p2s)])
        
        s = fusion.get_sign('R')
        startR = fusion.posR - s*dR
        endR = fusion.posR - s*dR2
        if startR > endR:
            startR, endR = endR, startR
        
        # Make maps
        tmaps = TransMaps(fusion, junctions)
        tmaps.add_map(0, startL, endL, '-', fusion.posL)
        tmaps.add_map(0, startL, endL, '+', fusion.posL)
        tmaps.add_map(1, startR, endR, '-', fusion.posR)
        tmaps.add_map(1, startR, endR, '+', fusion.posR)
    
        for m in tmaps.maps.values():
            if len(m)==0:
                raise Exception()
                
        return tmaps    
    
    def pick_short(a, b):
        return a if abs(a) < abs(b) else b
    
    def convert_pair_distances(fusion, junctions):
        # Define transcript maps
        # These map genomic coordinates to transcript coordinates.
        tmaps = get_transcript_maps(fusion, junctions)
        
        # Compute inner distances
        # Because we don't know which strand, we'll take the min of the
        # transcript distances on each strand.
        pairs = []
        for p1, p2 in fusion.pairs:
            s1 = fusion.get_sign('L')
            p1 = p1 * s1
            d1 = s1* pick_short( tmaps.map(0, fusion.posL, '-') - tmaps.map(0, fusion.posL - p1, '-'), 
                                 tmaps.map(0, fusion.posL, '+') - tmaps.map(0, fusion.posL - p1, '+') )
            
            s2 = fusion.get_sign('R')
            p2 = p2 * s2
            d2 = s2* pick_short( tmaps.map(1, fusion.posR, '-') - tmaps.map(1, fusion.posR - p2, '-'), 
                                 tmaps.map(1, fusion.posR, '+') - tmaps.map(1, fusion.posR - p2, '+') )
            
            pairs.append((d1,d2)) 
    
        return pairs
    
    def get_valid_pairs(info, pairs, junctions):
        # This method converts the distances from spanning pairs to the fusion
        #  from genomic to transcript coordinates - i.e. how far are the pairs
        #  in the processed transcript.
        # Parse fusion
        fusion = Fusion(info, pairs)
        
        if len(fusion.pairs) == 0:
            return []
        
        # Convert pairs to transcript coordinates
        tpairs = convert_pair_distances(fusion, junctions)
        
        # Return pairs with inner distance less than the threshold
        
        pairs = [(a,b) for (a,b) in tpairs if abs(a)+abs(b) <= params.fusion_pair_dist]
        return pairs
    
    ## Filter fusion implementation ##
    def filter_fusion_impl(fusion, junctions, refGene_list, ensGene_list, seq_chr_dic, fusion_gene_list):
        def gene_exists(gene_list, chr, coord, dir, is_left):
            min = 0
            max = len(gene_list) - 1
            while max - min >= 0:
                mid = (min + max) / 2
                gene = gene_list[mid]
                ref_chr = gene[1]

                if chr != ref_chr:
                    if chr_order[chr] < chr_order[ref_chr]:
                        max = mid - 1
                    else:
                        min = mid + 1
                    continue

                left_coord = gene[2]
                right_coord = gene[3]

                if coord >= left_coord and coord <= right_coord:
                    left_coords = gene[5]
                    right_coords = gene[6]
                    sense = gene[7]

                    belong = False
                    where = "outside"
                    for i in range(len(left_coords)):
                        # gives some relax!
                        relax = 3

                        left = int(left_coords[i]) - 1
                        right = int(right_coords[i]) - 1
                        if coord <= right + relax:
                            if coord < left - relax:
                                where = "intron%d(%d-%d)" % (i, int(right_coords[i-1]), left - 1)
                            else:
                                if ((is_left and dir == "f") or (not is_left and dir == "r")) and abs(coord - right) <= relax:
                                    belong = True

                                if ((is_left and dir == "r") or (not is_left and dir == "f")) and abs(coord - left) <= relax:
                                    belong = True

                                where = "exon%d(%d-%d)" % (i + 1, left, right)
                            break

                    return [gene[0], gene[4], where, belong, sense]
                elif coord < left_coord:
                    max = mid - 1
                else:
                    min = mid + 1

            return ["N/A", "N/A", "N/A", False, "N/A"]

        def how_diff(first, second):
            seq_len = len(first)

            min_value = 10000
            prev, curr = [0 for i in range(seq_len)], [0 for i in range(seq_len)]
            for j in range(seq_len):
                for i in range(seq_len):
                    value = 10000
                    if first[i] == second[j]:
                        match = 0
                    else:
                        match = 1

                    # right
                    if i == 0:
                        value = j * 2 + match
                    elif j > 0:
                        value = prev[i] + 2

                    temp_value = 10000

                    # down
                    if j == 0:
                        temp_value = i * 2 + match
                    elif i > 0:
                        temp_value = curr[i-1] + 2

                    if temp_value < value:
                        value = temp_value

                    # match
                    if i > 0 and j > 0:
                        temp_value = prev[i-1] + match

                    if temp_value < value:
                        value = temp_value

                    curr[i] = value

                    if (i == seq_len - 1 or j == seq_len - 1) and value < min_value:
                        min_value = value

                prev, curr = curr, prev

            return min_value

        kmer_len = len(seq_chr_dic.keys()[0])
        sample_name = fusion.split("/")[0][len("tophat_"):]

        data = os.getcwd().split('/')[-1]

        fusion_file = open(fusion, 'r')
        fusion_file.readline()
        for line in fusion_file:
            # Parse the fusion entry
            info, sim, left_seq_org, right_seq_org, left_dist, right_dist, pair_list = line[:-1].split('\t@\t')[:7]
            info = info.split('\t')
            if sim.strip() == "":
                continue
            sim = sim.split(' ')
            left_seq = left_seq_org.replace(' ', '')
            right_seq = right_seq_org.replace(' ', '')

            num_reads = int(info[4])
            
            # Correct the number of spanning pairs by filtering on the inner distance
            #  based on transcript coordinates instead of genomic coordinates
            pairs = get_valid_pairs(info[:4], pair_list, junctions)
            num_pair_ends = len(pairs)
            
            # Format pairs for usage downstream
            pairs = ['{0}:{1}'.format(a,b) for (a,b) in pairs]
            
            num_pair_ends_fusion = int(info[6])
            num_pair_ends_both = int(num_pair_ends + num_pair_ends_fusion * 0.5)
            num_contracting_reads = int(info[7])
            left_ext = int(info[8])
            right_ext = int(info[9])
            sym = float(info[10])

            half_len = len(left_seq) / 2
            chr1, chr2 = info[0].split('-')[:2]
            coord1, coord2 = int(info[1]), int(info[2])
            dir = info[3]

            if string.find(sample_name, "single") != -1:
                single = True
            else:
                single = False

            # Begin fusion filters
            if left_ext < 16 or right_ext < 16:
                continue

            both = num_reads + num_pair_ends_both
            all = both

            if num_pair_ends > num_reads * 50:
                continue

            if num_reads < params.num_fusion_reads or \
                    num_pair_ends < params.num_fusion_pairs or \
                    both < params.num_fusion_both:
                continue

            """
            if (chr1 != chr2 and num_contracting_reads > num_reads) or \
                    (chr1 == chr2 and num_contracting_reads > all + num_pair_ends + 5):
                continue
            """

            # are the sequences around the breakpoint different enough?
            if int(sim[0]) < 8:
                continue

            # are the reads distributed symmetrically?
            if sym >= 22 + max(0, 6 - num_reads):
                continue
            
            max_intron_len = 100000
            if chr1 == chr2 and dir == "ff":
                coord_dif = coord2 - coord1
                if coord_dif > 0 and coord_dif < max_intron_len:
                    continue
            
            if not left_seq[half_len-kmer_len:half_len] in seq_chr_dic or not right_seq[half_len:half_len+kmer_len] in seq_chr_dic:
                continue

            left_chrs = seq_chr_dic[left_seq[half_len-kmer_len:half_len]]
            right_chrs = seq_chr_dic[right_seq[half_len:half_len+kmer_len]]

            if chr1 == chr2:
                max_intron_len = min(max_intron_len, abs(coord1 - coord2) * 9 / 10)

            same = False
            for chr_coord in left_chrs:
                chr, coord = chr_coord.split(':')
                coord = int(coord)
                if chr == chr2 and abs(coord - coord2) < max_intron_len:
                    same = True
                    break

            if same:
                continue
            
            for chr_coord in right_chrs:
                chr, coord = chr_coord.split(':')
                coord = int(coord)
                if chr == chr1 and abs(coord - coord1) < max_intron_len:
                    same = True
                    break

            if same:
                continue

            def find_gene(chr, coord, one_dir, is_left):
                result = []
                for gene_list in [refGene_list, ensGene_list]:
                    result.append(gene_exists(gene_list, chr, coord, one_dir, is_left))

                if result[0][0] == "N/A":
                    return result[1] + result[1][:2]
                else:
                    return result[0] + result[1][:2]

            dir = info[3]
            gene1, gene1_name, gene1_where, gene1_belong, gene1_sense, ens_gene1, ens_gene1_name = find_gene(chr1, coord1, dir[0], True)
            gene2, gene2_name, gene2_where, gene2_belong, gene2_sense, ens_gene2, ens_gene2_name = find_gene(chr2, coord2, dir[1], False)
            if params.filter_by_annotation:
                if gene1_name == gene2_name or ens_gene1_name == ens_gene2_name or ens_gene1 == ens_gene2:
                    continue

                if gene1 == "N/A" or gene2 == "N/A" or (string.find(gene1, "ENS") == 0 and string.find(gene2, "ENS") == 0):
                    continue

            left_diff = how_diff(left_seq[half_len - 20:half_len], right_seq[half_len - 20:half_len])
            if left_diff <= 8:
                continue

            right_diff = how_diff(left_seq[half_len:half_len+20], right_seq[half_len:half_len+20])
            if right_diff <= 8:
                continue

            if left_diff + right_diff < 20:
                continue

            left_dist = left_dist.strip().split(' ')
            right_dist = right_dist.strip().split(' ')

            for i in range(len(left_dist)):
                left_dist[i] = '%d' % min(9, int(left_dist[i]))
                right_dist[i] ='%d' % min(9, int(right_dist[i]))

            swap = False
            if (dir == 'ff' and gene1_sense == '-' and gene2_sense == '-') or \
                   (dir == 'rr' and gene1_sense == '+' and gene2_sense == '+') or \
                   (dir == 'fr' and gene1_sense == '-' and gene2_sense == '+') or \
                   (dir == 'rf' and gene1_sense == '+' and gene2_sense == '-'):
                swap = True

            if swap:
                if dir == 'ff':
                    dir = 'rr'
                elif dir == 'rr':
                    dir = 'ff'

                info[0] = "%s-%s" % (chr2, chr1)
                info[1:3] = info[1:3][::-1]
                info[3] = dir
                info[8:10] = info[8:10][::-1]
                left_seq_org, right_seq_org = reverse_complement(right_seq_org), reverse_complement(left_seq_org)
                left_dist, right_dist = right_dist, left_dist
                gene1_name, gene1_where, gene1_sense, gene2_name, gene2_where, gene2_sense = \
                    gene2_name, gene2_where, gene2_sense, gene1_name, gene1_where, gene1_sense
                for j in range(len(pairs)):
                    pair = pairs[j].split(':')
                    pairs[j] = ':'.join(pair[::-1])

            # check if this is due to trans-splicing.
            if gene1_sense in "+-" and gene2_sense in "+-":
                if ((dir == 'ff' or dir == 'rr') and gene1_sense != gene2_sense) or \
                    (dir == 'fr' and (gene1_sense != '+' or gene2_sense != '-')) or \
                    (dir == 'rf' and (gene1_sense != '-' or gene2_sense != '+')):
                    # print >> sys.stderr, "fusion due to trans-splicing", info
                    # print >> sys.stderr, gene1, gene1_name, gene1_where, gene1_sense
                    # print >> sys.stderr, gene2, gene2_name, gene2_where, gene2_sense
                    None

            fusion_gene = []
            info[5] = str(num_pair_ends)
            fusion_gene.append(sample_name + ' ' + ' '.join(info[:10]))
            fusion_gene.append(left_seq_org)
            fusion_gene.append(right_seq_org)
            fusion_gene.append("%s %s" % (''.join(left_dist[::-1]), ''.join(right_dist)))

            fusion_gene.append("%s %s %s %s" % (gene1_name, gene1_where, gene2_name, gene2_where))
            fusion_gene.append(" ".join(pairs))

            fusion_gene_list.append(fusion_gene)
            
        fusion_file.close()

    print >> sys.stderr, "[%s] Filtering fusions" % right_now()
    
    seq_chr_dic = {}
    seq_chr_file = open(output_dir + "fusion_seq.map", 'r')
    for line in seq_chr_file:
        seq, chrs = line[:-1].split('\t')
        chrs = chrs.split(',')
        seq_chr_dic[seq] = chrs
    
    seq_chr_file.close()

    re_mir = re.compile(r'^(MIR)')
    def read_genes(gene_file_name, offset = 1, id = -4):
        gene_list, temp_gene_list = [], []
        if not os.path.exists(gene_file_name):
            return gene_list
        
        gene_file = open(gene_file_name, 'r')
        for line in gene_file:
            line = line[:-1].split('\t')[offset:]
            num_exons = int(line[7])
            left_coords = line[8].split(',')[:num_exons]
            right_coords = line[9].split(',')[:num_exons]
            
            if line[1] in chr_order and not re_mir.findall(line[id]):
                temp_gene_list.append([line[0], line[1], int(line[3]), int(line[4]), line[id], left_coords, right_coords, line[2]])

        gene_file.close()

        def my_cmp(a, b):
            if a[1] != b[1]:
                if chr_order[a[1]] < chr_order[b[1]]:
                    return -1
                else:
                    return 1
            else:
                if a[2] != b[2]:
                    if a[2] < b[2]:
                        return -1
                    else:
                        return 1
                else:
                    if a[3] > b[3]:
                        return -1
                    else:
                        return 1                   

        temp_gene_list = sorted(temp_gene_list, cmp=my_cmp)
        gene_list = []
        if len(temp_gene_list) >= 1:
            gene_list.append(temp_gene_list[0])

        # remove overlapping genes, that is, the longest genes are preferred
        for i in range(1, len(temp_gene_list)):
            gene1 = temp_gene_list[i-1]
            gene2 = temp_gene_list[i]

            if gene1[1] == gene2[1] and gene1[3] >= gene2[3]:
                continue

            gene_list.append(gene2)
            
        return gene_list

    refGene_list, ensGene_list = [], []
    if os.path.exists("refGene.txt"):
        refGene_list = read_genes("refGene.txt")
    if os.path.exists("ensGene.txt"):
        ensGene_list = read_genes("ensGene.txt")

    fusion_gene_list = []
    for file in sorted(os.listdir(".")):
        if string.find(file, "tophat_") != 0:
            continue

        fusion_file = file + "/fusions.out"
        if not os.path.exists(fusion_file):
            continue

        juncs_file = file + '/junctions.bed'
        if not os.path.exists(juncs_file):
            juncs_file = None
            print >> sys.stderr, 'Warning: could not find juctions.bed (%s).' % (juncs_file)
            
        ref_file = "refGene.txt"
        if not os.path.exists(ref_file):
            ref_file = None
        
        ens_file = "ensGene.txt"
        if not os.path.exists(ens_file):
            ens_file = None
        
        if juncs_file is None and ref_file is None and ens_file is None:
            print >> sys.stderr, 'Warning: neither junctions.bed nor ref/ensGene.txt found.'

        junctions = load_junctions(ref_file, ens_file, juncs_file)
        
        print >> sys.stderr, "\tProcessing:", fusion_file
        filter_fusion_impl(fusion_file, junctions, refGene_list, ensGene_list, seq_chr_dic, fusion_gene_list)

    fusion_out_file = output_dir + "potential_fusion.txt"
    output_file = open(fusion_out_file, 'w')
    for fusion_gene in fusion_gene_list:
        for line in fusion_gene:
            print >> output_file, line
    output_file.close()
    print >> sys.stderr, '\t%d fusions are output in %s' % (len(fusion_gene_list), fusion_out_file)
    


def parallel_work(pids, work):
    child = -1
    for i in range(len(pids)):
        if pids[i] == 0:
            child = i
            break

    while child == -1:
        status = os.waitpid(0, 0)
        for i in range(len(pids)):
            if status[0] == pids[i]:
                child = i
                pids[i] = 0
                break

    child_id = os.fork()
    if child_id == 0:
        work()
        os._exit(os.EX_OK)
    else:
        # print >> sys.stderr, '\t\t>> thread %d: %d' % (child, child_id)
        pids[child] = child_id


def wait_pids(pids):
    for pid in pids:
        if pid > 0:
            os.waitpid(pid, 0)
            
    
def do_blast(params):
    print >> sys.stderr, "[%s] Blasting 50-mers around fusions" % right_now()

    file_name = output_dir + "potential_fusion.txt"
    blast_genomic_out = output_dir + "blast_genomic"
    blast_nt_out = output_dir + "blast_nt"

    if not os.path.exists(blast_genomic_out):
        os.system("mkdir %s" % blast_genomic_out);

    if not os.path.exists(blast_nt_out):
        os.system("mkdir %s" % blast_nt_out)

    pids = [0 for i in range(params.num_threads)]

    count = 0
    line_no = 0
        
    check_list = []
    output_list = []
    output = ""
    file = open(file_name, 'r')
    for line in file:
        if line_no % 6 == 0:
            count += 1
            
        if line_no % 6 == 1:
            left_seq = line[:-1].split(" ")[0]

        if line_no % 6 == 2:
            right_seq = line[:-1].split(" ")[1]

        if line_no % 6 == 4:
            def blast(database, seq, outdir):
                file_name = "%s/%s" % (outdir, seq)
                if os.path.exists(file_name):
                    return

                blast_cmd = "echo %s | blastn -db %s -evalue 1e-10 -word_size 28"
                # blast_cmd = "echo %s | blastall -p blastn -d %s -e 1e-10 -W 28"
                output = os.popen(blast_cmd % (seq, database)).read()

                if str.find(output, "No hits found") != -1:
                    blast_cmd = "echo %s | blastn -db %s -evalue 1e-5"
                    # blast_cmd = "echo %s | blastall -p blastn -d %s -e 1e-5"
                    output = os.popen(blast_cmd % (seq, database)).read()
                
                pos1 = str.find(output, ">ref|")
                pos2 = str.find(output, "Database: ", pos1)

                if pos1 != -1 and pos1 < pos2:
                    output = output[pos1:pos2].rstrip()
                else:
                    output = ""

                file = open(file_name, "w")
                file.write(output)
                file.close()

            seq = left_seq + right_seq

            def work():
                if params.is_human:
                    blast_genomic = "blast/human_genomic"
                else:
                    blast_genomic = "blast/other_genomic"
                    
                blast_nt = "blast/nt"
                
                blast(blast_genomic, left_seq, blast_genomic_out)
                blast(blast_genomic, right_seq, blast_genomic_out)
                blast(blast_genomic, seq, blast_genomic_out)
                blast(blast_nt, left_seq, blast_nt_out)
                blast(blast_nt, right_seq, blast_nt_out)
                blast(blast_nt, seq, blast_nt_out)
            
            if not os.path.exists(output_dir + "blast_nt/" + seq ):
                print >> sys.stderr,  "\t%d. %s" % (count, line[:-1])
                if params.num_threads <= 1:
                    work()
                else:
                    parallel_work(pids, work)
                
        line_no += 1

    if params.num_threads > 1:
        wait_pids(pids)

        
def read_dist(params):
    def alignments_region(sample_name, bam, alignments_list):
        def output_region(sample_name, fusion, reads):
                chr_ref, pos1_ref, pos2_ref, dir_ref = fusion
                chr1_ref, chr2_ref = chr_ref.split('-')

                if len(reads) <= 0:
                    return

                alignments_file_name = "%s/%s_%s_%d_%d_%s" % (alignments_dir, sample_name, chr_ref, pos1_ref, pos2_ref, dir_ref)
                alignments_file = open(alignments_file_name, "w")

                def my_cmp(a, b):
                    if a[3] and not b[3]:
                        return -1
                    elif not a[3] and b[3]:
                        return 1

                    if a[3]:
                        if dir_ref[0] == "f":
                            return a[4] - b[4]
                        else:
                            return b[4] - a[4]
                    else:
                        if dir_ref[1] == "f":
                            return a[4] - b[4]
                        else:
                            return b[4] - a[4]

                reads = sorted(reads, cmp=my_cmp)
                begin_pos = reads[0][4]
                dist_to_breakpoint = abs(pos1_ref - begin_pos)
                for read in reads:
                    seq_pos = 0
                    read_id, chr1, chr2, before, left_pos, right_pos, cigars, seq, qual, mismatch, left = read[:-1]
                    space_len = 0
                    if before:
                        space_len = abs(left_pos - begin_pos)
                    else:
                        space_len = abs(pos1_ref - begin_pos) + 2
                        if dir_ref[1] == "f":
                            space_len += (left_pos - pos2_ref)
                        else:
                            space_len += (pos2_ref - left_pos)

                    qual_str = seq_str = ' ' * space_len

                    saw_fusion = False
                    for cigar in cigars:
                        length = int(cigar[:-1])
                        cigar_op = cigar[-1]

                        if cigar_op in "Mm":
                            seq_str += seq[seq_pos:seq_pos + length]
                            qual_str += qual[seq_pos:seq_pos + length]
                            seq_pos += length

                        if cigar_op in "Nn":
                            seq_str += ('|' * length)
                            qual_str += ('|' * length)

                        if cigar_op in "Dd":
                            seq_str += ("D" * length)
                            qual_str += ("D" * length)

                        if cigar_op in "Ii":
                            seq_pos += length

                        if cigar_op in "F":
                            seq_str += " "
                            qual_str += " "

                    cigar_str = ''.join(cigars)
                    prefix_str = '%s %s %d %d %s' % (chr1, chr2, left_pos, right_pos, cigar_str)
                    prefix_str += ' ' * (60 - len(prefix_str))

                    L = "L"
                    if not left:
                        L = "R"

                    begin, end = max(0, dist_to_breakpoint - within), dist_to_breakpoint + within
                    output = '%s %s\n' % (prefix_str, seq_str[begin:end])
                    alignments_file.write(output)
                    
                alignments_file.close()

        
        cigar_re = re.compile('\d+\w')
        within = 300

        old_chr = ""
        reads_list = [[] for i in range(len(alignments_list))]
        reads_compress_list = [[1, 0] for i in range(len(alignments_list))]

        cmd = ['samtools', 'view', '-h', bam]
        popen = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=open('/dev/null'))

        contigs = {}
        for line in popen.stdout:
            if line[0] == '@':
                if line[1:3] == 'SQ':
                    line = line[:-1].split('\t')
                    contig = line[1].split(':')[1]
                    if contig not in contigs:
                        contigs[contig] = len(contigs)

                continue

            line = line[:-1].split('\t')
                
            read_id, chr1, left_pos, cigar_str, seq, qual = line[0], line[2], int(line[3]) - 1, line[5], line[9], line[10]

            if chr1 != old_chr:
                old_chr = chr1
                # print "%s - %s" % (sample_name, chr1)

            secondary_fusion_alignment = False
            num_hits = 0
            for field in line[10:]:
                if field[:5] == "XF:Z:":
                    if field[5] == '2':
                        secondary_fusion_alignment = True

                    chr1, left_pos, cigar_str, seq, qual = field[7:].split()
                    left_pos = int(left_pos) - 1

                if field[:5] == "NM:i:":
                    mismatch = int(field.split(':')[-1])

                if field[:5] == "NH:i:":
                    num_hits = int(field.split(':')[-1])
                    
            if num_hits > params.fusion_multireads:
                continue

            if secondary_fusion_alignment:
                continue

            flag = int(line[1])
            left = (flag & 64 != 0)
            antisense = (flag & 16 != 0)

            if '-' in chr1:
                chr1, chr2 = chr1.split('-')
            else:
                chr2 = chr1

            right_pos = left_pos
            cigars = cigar_re.findall(cigar_str)
            dir = "ff"
            saw_fusion = False
            for cigar in cigars:
                length = int(cigar[:-1])
                cigar_op = cigar[-1]

                if cigar_op in "MDN":
                    right_pos += length

                    if saw_fusion:
                        dir = dir[0] + "f"
                    else:
                        dir = "f" + dir[1]

                if cigar_op in "mdn":
                    right_pos -= length

                    if saw_fusion:
                        dir = dir[0] + "r"
                    else:
                        dir = "r" + dir[1]

                if cigar_op in "F":
                    if dir[0] == "f":
                        pos1 = right_pos - 1
                    else:
                        pos1 = right_pos + 1

                    pos2 = right_pos = length - 1
                    saw_fusion = True

                if cigar_op in "iIdD":
                    mismatch -= length

            if not saw_fusion:
                report_idx = -1
                for i in range(len(alignments_list)):
                    chr_ref, pos1_ref, pos2_ref = alignments_list[i][:3]
                    chr1_ref, chr2_ref = chr_ref.split('-')

                    """
                    # a fusion point can be given like "chr9-chr1"
                    if (contigs[chr1_ref] < contigs[chr1] or (contigs[chr1_ref] == contigs[chr1] and left_pos - pos1_ref > 1000000)) and \
                            (contigs[chr2_ref] < contigs[chr1] or (contigs[chr2_ref] == contigs[chr1] and left_pos - pos2_ref > 1000000)):
                        report_idx = i
                    else:
                        break
                    """

                if report_idx >= 0:
                    for j in range(report_idx+1):
                        output_region(sample_name, alignments_list[j], reads_list[j])

                    alignments_list = alignments_list[report_idx+1:]
                    reads_list = reads_list[report_idx+1:]

                    if len(alignments_list) <= 0:
                        break

            fusion_read = saw_fusion
            if mismatch > params.fusion_read_mismatches:
                continue

            for i in range(len(alignments_list)):
                chr_ref, pos1_ref, pos2_ref, dir_ref = alignments_list[i]
                chr1_ref, chr2_ref = chr_ref.split('-')

                def reverse_read(fusion_read, dir, antisense, left_pos, right_pos, fusion_left, seq, qual, cigars):
                    if dir == 'ff' or not fusion_read:
                        left_pos, right_pos = right_pos - 1, left_pos - 1
                    elif dir == 'fr':
                        left_pos, right_pos = right_pos + 1, left_pos - 1
                    elif dir == 'rf':
                        left_pos, right_pos = right_pos - 1, left_pos + 1
                    elif dir == 'rr':
                        left_pos, right_pos = right_pos + 1, left_pos + 1

                    reversed_cigars = []
                    cigars.reverse()
                    for i in range(len(cigars)):
                        cigar = cigars[i]
                        opcode = cigar[-1]

                        if opcode == 'F':
                            reversed_cigars.append("%dF" % fusion_left)                  
                        else:
                            if str.islower(opcode):
                                opcode = str.upper(opcode)
                            else:
                                opcode = str.lower(opcode)

                            cigar = cigar[:-1] + opcode
                            reversed_cigars.append(cigar)

                    if dir == 'ff':
                        dir = 'rr'
                    elif dir == 'rr':
                        dir = 'ff'

                    return dir, antisense == False, left_pos, right_pos, reverse_complement(seq), qual[::-1], reversed_cigars

                if fusion_read and chr1 == chr2_ref and chr2 == chr1_ref and pos1 == pos2_ref and pos2 == pos1_ref:
                    dir, antisense, left_pos, right_pos, seq, qual, cigars = \
                        reverse_read(fusion_read, dir, antisense, left_pos, right_pos, pos1, seq, qual, cigars)

                    chr1, chr2 = chr2, chr1
                    pos1, pos2 = pos2, pos1

                if (fusion_read and chr1 == chr1_ref and chr2 == chr2_ref) or \
                        (not fusion_read and (chr1 == chr1_ref or chr1 == chr2_ref)):
                    if not fusion_read:
                        do_not_continue = False
                        if chr1 == chr1_ref:
                            if abs(left_pos - pos1_ref) <= 10000 or abs(right_pos - pos1_ref) <= 10000:
                                do_not_continue = True

                        if chr1 == chr2_ref:
                            if abs(left_pos - pos2_ref) <= 10000 or abs(right_pos - pos2_ref) <= 10000:
                                do_not_continue = True

                        if not do_not_continue:
                            continue

                    seq_temp = seq
                    qual_temp = qual
                    cigars_temp = cigars
                    left_pos_temp, right_pos_temp = left_pos, right_pos

                    before = True
                    if fusion_read:
                        if dir != dir_ref:
                            continue

                        if pos1 != pos1_ref or pos2 != pos2_ref:
                            continue
                    else:
                        do_not_continue = False
                        if chr1 == chr1_ref:
                            if dir_ref[0] == "f" and not (right_pos - pos1_ref >= 10 or pos1_ref - right_pos >= within):
                                do_not_continue = True
                            if dir_ref[0] == "r" and not (pos1_ref - left_pos >= 10 or left_pos - pos1_ref >= within):
                                do_not_continue = True

                        if chr1 == chr2_ref:
                            if dir_ref[1] == "f" and not (pos2_ref - left_pos >= 10 or left_pos - pos2_ref >= within):
                                do_not_continue = True
                                before = False
                            if dir_ref[1] == "r" and not (right_pos - pos2_ref >= 10 or pos2_ref - right_pos >= within):
                                do_not_continue = True
                                before = False

                        if not do_not_continue:
                            continue                    

                        if (before and dir_ref[0] == "r") or (not before and dir_ref[1] == "r"):
                            dir, antisense, left_pos_temp, right_pos_temp, seq_temp, qual_temp, cigars_temp = \
                                reverse_read(fusion_read, dir, antisense, left_pos_temp, right_pos_temp, 0, seq_temp, qual_temp, cigars_temp)
        
                    reads_list[i].append([read_id, chr1, chr2, before, left_pos_temp, right_pos_temp, cigars_temp, seq_temp, qual_temp, mismatch, left, line])
                    reads_compress_list[i][1] += 1


        for i in range(len(alignments_list)):
            output_region(sample_name, alignments_list[i], reads_list[i])

    print >> sys.stderr, "[%s] Generating read distributions around fusions" % right_now()

    file_name = output_dir + "potential_fusion.txt"
    file = open(file_name, 'r')

    alignments_dir = output_dir + "read_alignments"
    alignments_list = {}
    line_no = 0
    for line in file:
        if line_no % 6 == 0:
            temp_list = line[:-1].split(' ')
            sample_name = temp_list[0]

            if not sample_name in alignments_list:
                alignments_list[sample_name] = []

            if not os.path.exists("%s/%s_%s" % (alignments_dir, sample_name, "_".join(temp_list[1:5]))):
                alignments_list[sample_name].append(' '.join(temp_list[1:5]))                
            
        line_no += 1

    file.close()

    if not os.path.exists(alignments_dir):
        os.system("mkdir %s" % alignments_dir)

    pids = [0 for i in range(params.num_threads)]

    for sample_name, list in alignments_list.items():
        bam_file_name = 'tophat_%s/accepted_hits.bam' % sample_name
        if not os.path.exists(bam_file_name):
            continue

        increment = 50
        for i in range((len(list) + increment - 1) / increment):
            temp_list = list[i*increment:(i+1)*increment]
            print >> sys.stderr, '\t%s (%d-%d)' % (sample_name, i*increment + 1, min((i+1)*increment, len(list)))

            alignments_list = []
            for fusion in temp_list:
                print >> sys.stderr, '\t\t%s' % fusion
                fusion = fusion.split()
                alignments_list.append([fusion[0], int(fusion[1]), int(fusion[2]), fusion[3]])

            def work():
                if len(alignments_list) > 0:
                    alignments_region(sample_name, bam_file_name, alignments_list)

            if params.num_threads <= 1:
                work()
            else:
                parallel_work(pids, work)

    if params.num_threads > 1:
        wait_pids(pids)


                
def generate_html(params):
    def blast_output(database, seq):
        blast_output_filename = "%s/%s" % (database, seq)
        if os.path.exists(blast_output_filename):
            file = open(blast_output_filename, "r")
            return file.read() + "\n"

        return ""

    def read_fusion_genes(fusion_gene_list):
        sample_names = []
        sample_list_filename = output_dir + 'sample_list.txt'
        if not os.path.exists(sample_list_filename):
            return

        sample_list_file = open(sample_list_filename, "r")
        for line in sample_list_file:
            sample_names.append(line[:-1])
        sample_list_file.close()
            
	for sample_name in sample_names:
            sample_isoform_filename = "tophat_" + sample_name + "/transfuse.txt"
            if not os.path.exists(sample_isoform_filename):
                continue

            fusion_gene_begin_index = len(fusion_gene_list)
            sample_isoform_file = open(sample_isoform_filename, "r")
            for line in sample_isoform_file:
                line = line[:-1].lstrip()
                fields = line.split('\t')

                def read_coords(value_dic, value_str):
                    chr1, chr2 = "", ""
                    if ' ' in value_str:
                        chr1, chr2 = value_str.split(' ')
                    else:
                        chr1 = value_str
                        
                    chr1, chr1_coord = chr1.split(':')
                    chr1_left, chr1_right = chr1_coord.split('-')
                    chr1_left, chr1_right = int(chr1_left), int(chr1_right)
                    value_dic["chr1"] = chr1
                    value_dic["chr1_left"] = chr1_left
                    value_dic["chr1_right"] = chr1_right
                    
                    if chr2:
                        chr2, chr2_coord = chr2.split(':')
                        chr2_left, chr2_right = chr2_coord.split('-')
                        chr2_left, chr2_right = int(chr2_left), int(chr2_right)
                        value_dic["chr2"] = chr2
                        value_dic["chr2_left"] = chr2_left
                        value_dic["chr2_right"] = chr2_right
                    
                def read_values(value_dic, value_str):
                    values = fields[-1].split(';')

                    for value in values:
                        value = value.strip()
                        if not value:
                            continue
                        
                        name, value = value.split(' ')

                        value_dic[name] = value[1:-1]

                type = fields[0]
                if type == "gene":
                    value_dic = {}
                    read_coords(value_dic, fields[1])
                    read_values(value_dic, fields[-1])

                    fusion_gene_list.append([sample_name, value_dic, []])

                elif type == "transcript":
                    value_dic = {}
                    read_coords(value_dic, fields[1])
                    read_values(value_dic, fields[-1])

                    # daehwan - for debugging purposes
                    if float(value_dic["FPKM"]) >= 1.0:
                        skip_transcript = False
                        curr_gene = fusion_gene_list[-1]
                        transcript_list = curr_gene[-1]
                        transcript_list.append([value_dic, []])
                    else:
                        skip_transcript = True

                elif type in ["exon", "fusion"]:
                    if skip_transcript:
                        continue
                    
                    curr_gene = fusion_gene_list[-1]
                    transcript_list = curr_gene[-1]
                    curr_transcript = transcript_list[-1]
                    exon_list = curr_transcript[-1]
                    
                    if type == "exon":
                        chr, chr_coord = fields[1].split(':')
                        chr_left, chr_right = chr_coord.split('-')
                        chr_left, chr_right = int(chr_left), int(chr_right)
                        exon_list.append(["exon", chr, chr_left, chr_right])
                    else:
                        fusion_left, fusion_right = fields[1].split(' ')
                        chr1, chr1_pos = fusion_left.split(':')
                        chr2, chr2_pos = fusion_right.split(':')

                        chr1_pos, chr2_pos = int(chr1_pos), int(chr2_pos)
                        exon_list.append(["fusion", chr1, chr1_pos, chr2, chr2_pos])

            transcript_coverage_dic = {}
            sample_isoform_cov_filename = "tophat_" + sample_name + "/transfuse_cov.txt"
            if os.path.exists(sample_isoform_cov_filename):
                sample_isoform_cov_file = open(sample_isoform_cov_filename, "r")
                for line in sample_isoform_cov_file:
                    if line[0] == "C":
                        transcript_id = line.split("\t")[0]
                        transcript_coverage_dic[transcript_id] = []
                    else:
                        last_value = line.strip().split()[-1]
                        base_cov_float = float(last_value)
                        if math.isnan(base_cov_float):
                            base_cov_float = 0.1
                        base_cov = int(base_cov_float + 0.99)
                        transcript_coverage_dic[transcript_id].append(base_cov)

                sample_isoform_cov_file.close()
                    

            for fusion_gene in fusion_gene_list[fusion_gene_begin_index:]:
                sample_name, gene_value_dic, transcripts = fusion_gene
                max_base_cov = 0

                saw_fusion_transcript = False
                for transcript in transcripts:
                    transcript_value_dic, exons = transcript
                    transcript_id = transcript_value_dic["transcript_id"]

                    if transcript_id in transcript_coverage_dic:
                        transcript_coverage = transcript_coverage_dic[transcript_id]
                    else:
                        transcript_coverage = None
                    
                    saw_fusion = False
                    exon_offset = 0
                    for exon in exons:
                        if exon[0] == "fusion":
                            saw_fusion = True
                            continue

                        exon_length = exon[3] - exon[2] + 1

                        if transcript_coverage:
                            coverage = transcript_coverage[exon_offset:exon_offset + exon_length]
                        else:
                            coverage = [0 for z in range(exon_length)]

                        exon.append(coverage)
                            
                        for base_cov in exon[-1]:
                            if base_cov > max_base_cov:
                                max_base_cov = base_cov

                        exon_offset += exon_length

                    transcript_value_dic["is_fusion_transcript"] = saw_fusion
                    if saw_fusion:
                        saw_fusion_transcript = True

                    if not saw_fusion and saw_fusion_transcript:
                        transcript_value_dic["is_after_fusion"] = True
                    else:
                        transcript_value_dic["is_after_fusion"] = False

                for transcript in transcripts:
                    transcript_value_dic, exons = transcript
                    transcript_value_dic["max_base_cov"] = max_base_cov

            sample_isoform_file.close()

    def find_fusion_gene(fusion_gene_list, sample_name, chr1, chr1_coord, chr2, chr2_coord):
        # slow linear search through fusion_gene_list
        fusion_gene_info = ""
        for fusion_gene in fusion_gene_list:
            _sample_name = fusion_gene[0]
            value_dic = fusion_gene[1]
            _chr1, _chr1_left, _chr1_right, _chr2, _chr2_left, _chr2_right = \
                   value_dic["chr1"], value_dic["chr1_left"], value_dic["chr1_right"], \
                   value_dic["chr2"], value_dic["chr2_left"], value_dic["chr2_right"]
                   
            if sample_name != _sample_name:
                continue
            
            if chr1 != _chr1 or chr2 != _chr2:
                continue
            
            if chr1_coord < _chr1_left - 2 or chr1_coord > _chr1_right + 2:
                continue
            
            if chr2_coord < _chr2_left -2 or chr2_coord > _chr2_right + 2:
                continue

            transcripts = fusion_gene[-1]
            for transcript in transcripts:
                exons = transcript[-1]
                for exon in exons:
                    if exon[0] != "fusion":
                        continue

                    if chr1_coord == exon[2] and chr2_coord == exon[4]:
                        return fusion_gene

        return None


    def read_fusion_list(fusion_list):
        re_find_chromosomes = re.compile(r'Homo sapiens chromosome (\d+|[XY])')
        re_find_identities = re.compile(r'Identities = (\d+)\/\d+ \((\d+)%\)')
        re_find_exon = re.compile(r'exon\d+\((\d+-\d+)\)')

        line_no = 0
        do_not_add = False
        output = {}
        file_name = output_dir + "potential_fusion.txt"
        file = open(file_name, 'r')
        for line in file:
            if line_no % 6 == 0:
                if output and not do_not_add:
                    fusion_list.append(output)

                do_not_add = False
                temp_list = line[:-1].split(' ')
                sample_name = temp_list[0]

                chr = temp_list[1]
                chr1, chr2 = chr.split('-')
                left = int(temp_list[2])
                right = int(temp_list[3])
                dir = temp_list[4]

                output = {}
                output["sample_name"] = sample_name
                output["chr"] = chr
                output["chr1"] = chr1
                output["chr2"] = chr2
                output["left_coord"] = left
                output["right_coord"] = right
                output["dir"] = dir
                output["stats"] = temp_list[5:]

            elif line_no % 6 == 1:
                output["left_seq"] = line[:-1].split(" ")[0]

            elif line_no % 6 == 2:
                output["right_seq"] = line[:-1].split(" ")[1]

                left_seq = output["left_seq"]
                right_seq = output["right_seq"]
                seq = left_seq + right_seq

                temp_output = blast_output(output_dir + "blast_genomic", left_seq)
                left_chromosomes = set(re_find_chromosomes.findall(temp_output))

                temp_output = blast_output(output_dir + "blast_genomic", right_seq)
                right_chromosomes = set(re_find_chromosomes.findall(temp_output))

                if string.find(output["sample_name"], "single") == -1:
                    chr1, chr2 = output["chr"].split("-")
                    if chr1 != chr2 and left_chromosomes & right_chromosomes:
                        do_not_add = True

                    temp_output = blast_output(output_dir + "blast_genomic", seq) + blast_output(output_dir + "blast_nt", seq)
                    for identity in re_find_identities.findall(temp_output):
                        query = int(identity[0])
                        percent = int(identity[1])
                        if query + percent > 160:
                            do_not_add = True
                            break

            elif line_no % 6 == 3:
                output["depth"] = line[:-1]

            elif line_no % 6 == 4:
                output["gene"] = line[:-1]
                temp = output["gene"].split()
                output["gene1"], output["gene2"] = temp[0], temp[2]

            else:
                pair_str = line.strip()
                if len(pair_str) > 0:
                    pairs = pair_str.split(" ")
                else:
                    pairs = []

                output["pair_coords"] = pairs

                read_output = ""
                read_output_file = output_dir + "read_alignments/%s_%s_%d_%d_%s" % (output["sample_name"], output["chr"],
                                                                                    output["left_coord"], output["right_coord"], output["dir"])

                if not do_not_add and os.path.exists(read_output_file):
                    read_output = open(read_output_file, "r").read()

                    def unique(list, left, right):
                        color_len = 300
                        result, lcolor, rcolor = [], [0 for i in range(color_len)], [0 for i in range(color_len)]
                        keys = []
                        F_start, F_end = 1000000, 0
                        for item in list:
                            key = item.split(" ")
                            if len(key) < 6:
                                continue

                            chr1, chr2, pos1, pos2, cigars = key[:5]
                            pos1, pos2 = int(pos1), int(pos2)

                            def color(list, left, right):
                                for i in range(left, right):
                                    if i >= len(list):
                                        break

                                    list[i] += 1                            

                            if 'F' in cigars:
                                dist1 = abs(pos1 - left)
                                dist2 = abs(pos2 - right)

                                color(lcolor, 0, dist1)
                                color(rcolor, 0, dist2)

                            elif abs(pos2 - left) < color_len:
                                color(lcolor, abs(pos2 - left), abs(pos1 - left))

                            elif abs(pos1 - right) < color_len:
                                color(rcolor, abs(pos1 - right), abs(pos2 - right))

                            if "F" in key[4] or len(keys) == 0 or key[:2] != keys[-1][:2] or abs(int(key[2]) - int(keys[-1][2])) >= 3:
                                keys.append(key[:3])
                                result.append(item)

                                if "F" in key[4]:
                                    index = len(result) - 1
                                    if index < F_start:
                                        F_start = index

                                    if F_end < index:
                                        F_end = index

                        if F_end == 0:
                            F_start, F_end = 0, len(result)

                        temp_result = result[max(0, F_start - 50):(F_end+50)]
                        result = []
                        for i in range(len(temp_result)):
                            item = temp_result[i].split(" ")
                            if i == 0:
                                trim = 0
                                for ch in item[40:-1]:
                                    trim += 1

                            item = item[:40] + item[40 + trim:]
                            result.append(" ".join(item))

                        return result, lcolor, rcolor

                    if len(read_output) < 1024 * 1024 * 1024:
                        read_output = read_output.split("\n")
                        read_output, lcolor, rcolor = unique(read_output, output["left_coord"], output["right_coord"])

                        def stat(lcolor, rcolor, dist):
                            lcount, lsum, rcount, rsum = 1, 0, 1, 0
                            lgap, lpass, rgap, rpass = 0, False, 0, False
                            for i in range(dist):
                                if lcolor[i] > 0:
                                    lcount += 1
                                    lsum += lcolor[i]

                                    if lgap > 0:
                                        lpass = True
                                else:
                                    if not lpass:
                                        lgap += 1

                                if rcolor[i] > 0:
                                    rcount += 1
                                    rsum += rcolor[i]

                                    if rgap > 0:
                                        rpass = True
                                else:
                                    if not rpass:
                                        rgap += 1

                            if not lpass:
                                lgap = 0

                            if not rpass:
                                rgap = 0

                            return lcount, lsum / lcount, lgap, rcount, rsum / rcount, rgap

                        temp =  output["gene"].split()
                        gene1_loc, gene2_loc = temp[1], temp[3]

                        def find_exon_len(gene_loc, coord, dir, is_left):
                            exon_len = 1000000
                            for loc in re_find_exon.findall(gene_loc):
                                start, end = loc.split('-')
                                start, end = int(start), int(end)
                                if (is_left and dir == 'f') or (not is_left and dir == 'r'):
                                    exon_len = coord - start + 1
                                else:
                                    exon_len = end - coord + 1
                                return exon_len

                            return exon_len

                        lcount_min, rcount_min, diff_max = 150, 150, 120

                        lcount_exon_min = find_exon_len(gene1_loc, output["left_coord"], output["dir"][0], True)
                        rcount_exon_min = find_exon_len(gene2_loc, output["right_coord"], output["dir"][1], False)

                        lcount_min = min(lcount_min, lcount_exon_min - 20)
                        rcount_min = min(rcount_min, rcount_exon_min - 20)
                        diff_max = min(diff_max, abs(lcount_min - rcount_min) + 20)

                        if lcount_exon_min < 1000 and rcount_exon_min < 1000:
                            diff_max = max(diff_max, abs(lcount_exon_min - rcount_exon_min) + 20)                        

                        lcount, lavg, lgap, rcount, ravg, rgap = stat(lcolor, rcolor, len(lcolor))
                        if lcount <= lcount_min or rcount <= rcount_min or lgap / lcount > 0.1 or rgap / rcount > 0.1:
                            if abs(min(lcount, lcount_exon_min) - min(rcount, rcount_exon_min)) > diff_max or lcount < 60 or rcount < 60:
                                do_not_add = True

                        def derivation(color, length, avg):
                            der = 0.0
                            for i in range(length):
                                diff = 1.0 - float(color[i]) / float(max(1, avg))
                                der += diff * diff

                            return math.sqrt(der / max(1, length))

                        output["read_output"] = read_output
                        output["lcount"] = lcount
                        output["lavg"] = lavg
                        output["lgap"] = lgap
                        output["lder"] = lder = derivation(lcolor, lcount_min, lavg)
                        output["rcount"] = rcount
                        output["ravg"] = ravg
                        output["rgap"] = rgap
                        output["rder"] = rder = derivation(rcolor, rcount_min, ravg)

                        stats = output["stats"]
                        num_read = int(stats[0])
                        pair = int(stats[1])
                        pair_fusion = int(stats[2])
                        anti_read = int(stats[3])
                        anti_pair = int(stats[4])
                        pair_coords = output["pair_coords"]

                        dist = 1000000
                        if len(pair_coords) > 0:
                            pair = 0
                            for pair_coord in pair_coords:
                                pair_coord = pair_coord.split(":")
                                temp_dist = abs(int(pair_coord[0])) + abs(int(pair_coord[1]))
                                if temp_dist < dist:
                                    dist = temp_dist

                                if temp_dist < 2000:
                                    pair += 1


                        anti_read += 0.5
                        if pair == 0:
                            rate = num_read / anti_read
                        else:
                            rate = pair / anti_read

                        fusion_gene = find_fusion_gene(fusion_gene_list, \
                                                       output["sample_name"], \
                                                       output["chr1"], output["left_coord"], \
                                                       output["chr2"], output["right_coord"])

                        output["assembled"] = False
                        fusion_dic = {}
                        left_normal_transcript, right_normal_transcript = 0, 0
                        if fusion_gene:
                            sample_name, gene_value_dic, transcripts = fusion_gene
                            for transcript in transcripts:
                                transcript_value_dic, exons = transcript
                                if not transcript_value_dic["is_fusion_transcript"]:
                                    if transcript_value_dic["is_after_fusion"]:
                                        right_normal_transcript = 1
                                    else:
                                        left_normal_transcript = 1

                                    continue
                                    
                                for exon in exons:
                                    if exon[0] == "fusion":
                                        fusion_item = "%d-%d" % (exon[2], exon[4])

                                        if output["left_coord"] == exon[2] and output["right_coord"] == exon[4]:
                                            assembled = True
                                            output["assembled"] = True
                                            
                                        if fusion_item not in fusion_dic:
                                            fusion_dic[fusion_item] = 0

                                        fusion_dic[fusion_item] += 1


                        num_fusions = 0
                        num_alternative_splicing_with_same_fusion = 0
                            
                        for key, value in fusion_dic.items():
                            num_fusions += 1
                            num_alternative_splicing_with_same_fusion += (value - 1)

                        # lcount and rcount both are in [0, 300]
                        max_avg = 300
                        score = lcount + rcount + (min(max_avg, lavg) + min(max_avg, ravg)) - abs(lcount - rcount) \
                            - min(max_avg, abs(lavg - ravg)) - (lgap + rgap) - (lder + rder) * max_avg - min(dist, 1000) \
                            + rate

                        if output["assembled"]:
                            score += 300 + min(num_fusions - 1, 5) * 200 + min(num_alternative_splicing_with_same_fusion, 5) * 100 \
                                     + left_normal_transcript * 50 + right_normal_transcript * 50

                        output["score"] = score
                        output["test"] = "lcount: %d, lavg: %d, lgap: %d, lder: %f, rcount: %d, ravg: %d, rgap: %d, rder: %f, dist: %d, score: %f num_fusions: %d num_alternative_splicing_with_same_fusion: %d left_normal_transcript: %d right_normal_transcript: %d" % \
                            (lcount, lavg, lgap, lder, rcount, ravg, rgap, rder, dist, score, num_fusions, num_alternative_splicing_with_same_fusion, left_normal_transcript, right_normal_transcript)

                    else:
                        read_output = [r"too many - not shown"]

                if not "read_output" in output:
                    output["read_output"] = ""
                    output["lcount"] = 0
                    output["lavg"] = 0
                    output["lgap"] = 0
                    output["lder"] = 0
                    output["rcount"] = 0
                    output["ravg"] = 0
                    output["rgap"] = 0
                    output["rder"] = 0
                    output["score"] = 0
                    output["assembled"] = False

            line_no += 1

        if output and not do_not_add:
            fusion_list.append(output)

        file.close()

        
    def cluster_fusion(fusion_list, fusion_gene_list, cluster_list):
        cluster_dist = 500000

        cluster_temp_list = []
        parent = [i for i in range(len(fusion_list))]

        for i in range(len(fusion_list)):
            fusion = fusion_list[i]

            cluster = {}
            cluster["index"] = [i]
            cluster["chr"] = fusion["chr"]
            cluster["left1"] = cluster["left2"] = fusion["left_coord"]
            cluster["right1"] = cluster["right2"] = fusion["right_coord"]
            cluster["dir"] = fusion["dir"]

            cluster_temp_list.append(cluster)

        def parent_index(parent, i):
            parent_i = parent[i]
            if i == parent_i:
                return i
            else:
                parent[i] = parent[parent_i]
                return parent_index(parent, parent[i])

        for i in range(len(fusion_list) - 1):
            parent_i = parent_index(parent, i)
            for j in range(i+1, len(fusion_list)):
                parent_j = parent_index(parent, j)

                if parent_i == parent_j:
                    continue

                cluster_i = cluster_temp_list[parent_i]
                cluster_j = cluster_temp_list[parent_j]

                if cluster_i["chr"] != cluster_j["chr"] or cluster_i["dir"] != cluster_j["dir"]:
                    continue

                i_left1 = cluster_i["left1"]
                i_left2 = cluster_i["left2"]

                j_left1 = cluster_j["left1"]
                j_left2 = cluster_j["left2"]

                if abs(i_left1 - j_left1) > cluster_dist or abs(i_left2 - j_left2) > cluster_dist or \
                        abs(i_left2 - j_left1) > cluster_dist or abs(i_left1 - j_left2) > cluster_dist:
                    continue

                i_right1 = cluster_i["right1"]
                i_right2 = cluster_i["right2"]

                j_right1 = cluster_j["right1"]
                j_right2 = cluster_j["right2"]

                if abs(i_right1 - j_right1) > cluster_dist or abs(i_right2 - j_right2) > cluster_dist or\
                        abs(i_right2 - j_right1) > cluster_dist or abs(i_right1 - j_right2) > cluster_dist:
                    continue

                cluster_i["left1"] = min(i_left1, j_left1)
                cluster_i["left2"] = max(i_left2, j_left2)

                cluster_i["right1"] = min(i_right1, j_right1)
                cluster_i["right2"] = max(i_right2, j_right2)

                parent[j] = i
                cluster_i["index"].extend(cluster_j["index"])


        cluster_temp_list2 = []
        for i in range(len(parent)):
            if i == parent[i]:
                cluster_temp_list2.append(cluster_temp_list[i])

        def num_samples(indices):
            samples = []
            for i in indices:
                sample = fusion_list[i]["sample_name"]
                if not sample in samples:
                    samples.append(sample)

            return len(samples)                    

        def cmp(a, b):
            def pair_count(indices):
                final_score = -1000000.0
                for index in indices:
                    score = fusion_list[index]["score"]
                    if score > final_score:
                        final_score = score

                return int(final_score)

            a_indices = a["index"]
            b_indices = b["index"]

            a_gene, b_gene = 0, 0
            def known_genes(indices):
                num = 0
                for index in indices:
                    temp_num = 0
                    fusion = fusion_list[index]

                    if fusion["gene1"] != "N/A":
                        temp_num += 1

                    if fusion["gene2"] != "N/A":
                        temp_num += 1

                    if temp_num > num:
                        num = temp_num

                return num

            a_gene = known_genes(a_indices)
            b_gene = known_genes(b_indices)

            if a_gene != b_gene:
                return b_gene - a_gene

            a_num_sample, b_num_sample = num_samples(a_indices), num_samples(b_indices)
            a_score = pair_count(a_indices)
            b_score = pair_count(b_indices)

            return b_score - a_score

        cluster_temp_list = sorted(cluster_temp_list2, cmp=cmp)

        for i in range(min(params.max_num_fusions, len(cluster_temp_list))):
            do_not_add = False
            indices = cluster_temp_list[i]["index"]
            if not do_not_add:
                def cmp(a, b):
                    return int(fusion_list[b]["score"] - fusion_list[a]["score"])

                cluster_temp_list[i]["index"] = sorted(cluster_temp_list[i]["index"], cmp=cmp)
                cluster_list.append(cluster_temp_list[i])

    def generate_html_impl(fusion_list, cluster_list, fusion_gene_list):
        html_file_name = output_dir + 'result.html'
        txt_file_name = output_dir + 'result.txt'
        html_file = open(html_file_name, 'w')
        txt_file = open(txt_file_name, 'w')

        html_prev = []
        javascript = []
        html_body = []
        html_post = []

        def cmp(i, j):
            i_left = fusion_list[i]["left_coord"]
            j_left = fusion_list[j]["left_coord"]
            if i_left == j_left:
                return i - j
            else:
                return i_left - j_left

        indices_list = []
        for c in cluster_list:
            indices_list += c["index"]

        indices_list = sorted(indices_list)
        print >> sys.stderr, "\tnum of fusions: %d" % len(cluster_list)

        if params.tex_table:
            tex_table_file_name = output_dir + 'table.tex'
            tex_table_file = open(tex_table_file_name, 'w')
            print >> tex_table_file, r'\documentclass{article}'
            print >> tex_table_file, r'\usepackage{graphicx}'
            print >> tex_table_file, r'\begin{document}'
            print >> tex_table_file, r'\pagestyle{empty}'
            print >> tex_table_file, r"\center{\scalebox{0.7}{"
            print >> tex_table_file, r"\begin{tabular}{| c | c | c | c | c | c | c |}"
            print >> tex_table_file, r"\hline"
            print >> tex_table_file, r"SAMPLE ID & Fusion genes (left-right) & Chromosomes (left-right) & " + \
                r"5$'$ position & 3$'$ position & Spanning reads & Spanning pairs \\"

        html_prev.append(r'<HTML>')
        html_prev.append(r'<HEAD>')
        html_prev.append(r'<TITLE>result</TITLE>')
        html_prev.append(r'<META NAME="description" CONTENT="result">')
        html_prev.append(r'<META NAME="keywords" CONTENT="result">')
        html_prev.append(r'<META NAME="resource-type" CONTENT="document">')
        html_prev.append(r'<META NAME="distribution" CONTENT="global">')
        html_prev.append(r'<META HTTP-EQUIV="Content-Style-Type" CONTENT="text/css">')
        html_prev.append(r'<!--[if IE]><script src="excanvas.js"></script><![endif]-->')
        html_prev.append(r'<style type="text/css">')
        # html_prev.append(r'canvas { border: 1px solid black; }')
        html_prev.append(r'H1 { margin: 0 0 0 0; }')
        html_prev.append(r'</style>')
        html_body.append(r'</HEAD>')

        html_post.append(r'<H1><BR>Candidate fusion list</H1>')
        html_post.append(r'The following tables show fusion candidates where fusions are grouped based on their genomic locations (<a href="#detail">table description</a>).<BR>')

        num_fusions = 0
        for c in range(len(cluster_list)):
            cluster = cluster_list[c]
            indices = cluster["index"]

            num_fusions += len(indices)

            top_index = indices[0]
            indices = sorted(indices, cmp=cmp)

            chr1, chr2 = cluster["chr"].split('-')

            if params.tex_table:
                print >> tex_table_file, r'\hline'

            html_post.append(r'<P><P><P><BR>')
            html_post.append(r'%d. %s %s' % (c+1, cluster["chr"], cluster["dir"]))

            html_post.append(r'<TABLE CELLPADDING=3 BORDER="1">')
            for i in indices:
                fusion = fusion_list[i]
                sample_name = fusion["sample_name"]
                # sample_name = string.split(sample_name, '_')[0]

                output = ""
                stats = fusion["stats"]
                stats = [int(stat) for stat in stats]

                if stats[1] > 0:
                    pair_support_html = r"\htmlref{%d}{pair_%d}" % (stats[1], i)
                else:
                    pair_support_html = r"0"

                if params.tex_table:
                    if sample_name == "lane1":
                        sample_name2 = "thyroid"
                    else:
                        sample_name2 = "testes"
                        
                    print >> tex_table_file, r'%s & %s & %s & %d & %d & %d & %d \\' % \
                        (sample_name2,
                         fusion["gene1"] + "-" + fusion["gene2"],
                         chr1[3:] + "-" + chr2[3:],
                         fusion["left_coord"],
                         fusion["right_coord"],
                         stats[0],
                         stats[1] + stats[2])

                print >> txt_file, '%s\t%s\t%s\t%d\t%s\t%s\t%d\t%d\t%d\t%d\t%.2f' % \
                      (sample_name,
                       fusion["gene1"],
                       chr1,
                       fusion["left_coord"],
                       fusion["gene2"],
                       chr2,
                       fusion["right_coord"],
                       stats[0],
                       stats[1],
                       stats[2],
                       fusion["score"])

                html_post.append(r'<TR><TD ALIGN="LEFT"><a href="#fusion_%d">%s</a></TD>' % (i, sample_name))
                html_post.append(r'<TD ALIGN="LEFT">%s</TD>' % fusion["gene1"])
                html_post.append(r'<TD ALIGN="LEFT">%s</TD>' % chr1)
                html_post.append(r'<TD ALIGN="RIGHT">%d</TD>' % fusion["left_coord"])
                html_post.append(r'<TD ALIGN="LEFT">%s</TD>' % fusion["gene2"])
                html_post.append(r'<TD ALIGN="LEFT">%s</TD>' % chr2)
                html_post.append(r'<TD ALIGN="RIGHT">%d</TD>' % fusion["right_coord"])
                html_post.append(r'<TD ALIGN="RIGHT"><a href="#read_%d">%d</a></TD>' % (i, stats[0]))
                html_post.append(r'<TD ALIGN="RIGHT"><a href="#pair_%d">%d</a></TD>' % (i, stats[1]))
                html_post.append(r'<TD ALIGN="RIGHT">%d</TD>' % stats[2])

                # daehwan - for debugging purposes
                # html_post.append(r'<TD ALIGN="RIGHT">%.2f</TD>' % fusion["score"])
                # html_post.append(r'<TD ALIGN="RIGHT">%s</TD>' % fusion["test"])

                fusion_gene = find_fusion_gene(fusion_gene_list, sample_name, chr1, fusion["left_coord"], chr2, fusion["right_coord"])
                fusion["fusion_gene"] = fusion_gene
                if fusion_gene and fusion["assembled"]:
                    html_post.append(r'<TD ALIGN="RIGHT"><a href="#fusion_gene_%d">isoforms</a></TD>' % i)

                html_post.append(r'</TR>')
                
                
            html_post.append(r'</TABLE>')

        """
        # sample
        html_post.append(r'<H1><A NAME="sample"></A><BR>sample list</H1>')
        html_post.append(r'<TABLE CELLPADDING=3 BORDER="1">')
        html_post.append(r'<TR><TD ALIGN="LEFT">sample name</TD>')
        html_post.append(r'<TD ALIGN="RIGHT">fragment length</TD>')
        html_post.append(r'<TD ALIGN="RIGHT">read length</TD>')
        html_post.append(r'<TD ALIGN="RIGHT"># of fragments</TD></TR>')

        if os.path.exists("sample_info.txt"):
            sample_file = open("sample_info.txt", "r")
            for line in sample_file:
                line = line[:-1].split("\t")
                html_post.append(r'<TR><TD ALIGN="LEFT">%s</TD>' % line[0])
                html_post.append(r'<TD ALIGN="RIGHT">%s</TD>' % line[1])
                html_post.append(r'<TD ALIGN="RIGHT">%s</TD>' % line[2])
                html_post.append(r'<TD ALIGN="RIGHT">%s</TD></TR>' % line[3])

            sample_file.close()

        html_post.append(r'</TABLE>')
        """

        # description
        html_post.append(r'<H1><A NAME="detail"></A><BR>table description</H1>')
        html_post.append(r'1. Sample name in which a fusion is identified <BR>')
        html_post.append(r'2. Gene on the "left" side of the fusion <BR>')
        html_post.append(r'3. Chromosome ID on the left <BR>')
        html_post.append(r'4. Coordinates on the left <BR>')
        html_post.append(r'5. Gene on the "right" side <BR>')
        html_post.append(r'6. Chromosome ID on the right <BR>')
        html_post.append(r'7. Coordinates on the right <BR>')
        html_post.append(r'8. Number of spanning reads - this is the number of reads that span a fusion point all on their own.  In other words, the read itself has a fusion break point within it. <BR>')
        html_post.append(r'9. Number of spanning mate pairs -  this is the number of pairs of reads where one read maps entirely on the left and the other read maps entirely on the right of the fusion break point.  Neither read is split, so these pairs are not counted at all in (8). <BR>')
        html_post.append(r'10. Number of spanning mate pairs where one end spans a fusion (reads spanning fusion with only a few bases are included). <BR>')
        html_post.append(r'If you follow the the 9th column, it shows coordinates "number1:number2" where one end is located at a distance of "number1" bases from the left genomic coordinate of a fusion and "number2" is similarly defined.')
        html_post.append(r'<BR/><BR/><BR/>')

        fusion_gene_drawn = [False for i in range(len(cluster_list))]

        fusion_gene_indices = []
        for i in indices_list:
            cluster_index = -1
            for c in range(len(cluster_list)):
                cluster_indices = cluster_list[c]["index"]
                if i in cluster_indices:
                    cluster_index = c
                    break
                
            fusion = fusion_list[i]
            sample_name = fusion["sample_name"]
            chr = fusion["chr"]
            left = fusion["left_coord"]
            right = fusion["right_coord"]
            dir = fusion["dir"]

            chr1, chr2 = chr.split("-")

            left_seq = fusion["left_seq"]
            right_seq = fusion["right_seq"]
            seq = left_seq + right_seq

            pair_coords = fusion["pair_coords"]
            stats = fusion["stats"]
            stats = [int(stat) for stat in stats]

            html_post.append(r'<A NAME="fusion_%d">' % i)
            html_post.append(r'<TABLE CELLPADDING=3 BORDER="1"><TR><TD ALIGN="LEFT"><H1>%s</H1></TD>' % (sample_name))
            html_post.append(r'<TD ALIGN="LEFT"><H1>%s</H1></TD>' % fusion["gene1"])
            html_post.append(r'<TD ALIGN="LEFT"><H1>%s</H1></TD>' % chr1)
            html_post.append(r'<TD ALIGN="RIGHT"><H1>%d</H1></TD>' % fusion["left_coord"])
            html_post.append(r'<TD ALIGN="LEFT"><H1>%s</H1></TD>' % fusion["gene2"])
            html_post.append(r'<TD ALIGN="LEFT"><H1>%s</H1></TD>' % chr2)
            html_post.append(r'<TD ALIGN="RIGHT"><H1>%d</H1></TD>' % fusion["right_coord"])
            html_post.append(r'<TD ALIGN="RIGHT"><H1><a href="#read_%d">%d</a></H1></TD>' % (i, stats[0]))
            html_post.append(r'<TD ALIGN="RIGHT"><H1><a href="#pair_%d">%d</a></H1></TD>' % (i, stats[1]))
            html_post.append(r'<TD ALIGN="RIGHT"><H1>%d</H1></TD>' % stats[2])
            html_post.append(r'</A>')

            dir_str = ""
            if dir[0] == "f":
                dir_str += "-------->"
            else:
                dir_str += "<--------"

            dir_str += " "

            if dir[1] == "f":
                dir_str += "-------->"
            else:
                dir_str += "<--------"
            
            html_post.append(r'<TD ALIGN="RIGHT"><H1>%s</H1></TD>' % dir_str)
            html_post.append(r'</TR></TABLE>')
            html_post.append(r'</BR></BR>')

            """
            html_post.append(r'<PRE>')
            html_post.append(r'%s %s' % (left_seq, right_seq))
            html_post.append(r'%s' % fusion["depth"])
            html_post.append(r'%s' % fusion["gene"])
            html_post.append(r'</PRE>')
            """

            fusion_gene = fusion["fusion_gene"]
            if fusion_gene:
                fusion_gene_indices.append([i, cluster_index])
                
                fg_value_dic, transcripts = fusion_gene[1], fusion_gene[2]
                html_post.append(r'<A NAME="fusion_gene_%d"><H1>%s-%s</H1></A>' % (i, fusion["gene1"], fusion["gene2"]))

                if not fusion_gene_drawn[cluster_index]:
                    javascript.append(r'<script type="text/javascript">')
                    javascript.append(r"function fusion_gene_draw%d(isoform_index){" % cluster_index)
                    # javascript.append(r"alert('message')")
                    javascript.append(r"var canvas = document.getElementById('fusion_gene_canvas' + isoform_index.toString());")
                    javascript.append(r"if (canvas.getContext){")
                    javascript.append(r"var ctx = canvas.getContext('2d');")
                    # javascript.append(r"ctx.fillStyle = 'rgba(0, 0, 200, 0.5)';")
                    # javascript.append(r"ctx.fillRect (30, 30, 55, 50);")

                chr1, chr1_left, chr1_right = fg_value_dic["chr1"], fg_value_dic["chr1_left"], fg_value_dic["chr1_right"]
                chr2, chr2_left, chr2_right = fg_value_dic["chr2"], fg_value_dic["chr2_left"], fg_value_dic["chr2_right"]

                html_post.append(r'<TABLE CELLSPACING=0 CELLPADDING=3 BORDER="1">')
                html_post.append(r'<TR>')
                html_post.append(r'<TD ALIGN="LEFT">Type</TD>')
                html_post.append(r'<TD ALIGN="LEFT">Left Chromosome</TD>')
                html_post.append(r'<TD ALIGN="LEFT">Range</TD>')
                html_post.append(r'<TD ALIGN="LEFT">Right Chromosome</TD>')
                html_post.append(r'<TD ALIGN="LEFT">Range</TD>')
                html_post.append(r'<TD ALIGN="LEFT">Pairs</TD>')
                html_post.append(r'<TD ALIGN="RIGHT">Reads (singleton)</TD>')
                html_post.append(r'<TD ALIGN="RIGHT">FPKM</TD>')
                html_post.append(r'</TR>')

                """
                html_post.append(r'<TR>')
                html_post.append(r'<TD ALIGN="LEFT">fusion gene</TD>')
                html_post.append(r'<TD ALIGN="CENTER">%s</TD>' % chr1)
                html_post.append(r'<TD ALIGN="LEFT">%d-%d</TD>' % (chr1_left, chr1_right))
                html_post.append(r'<TD ALIGN="CENTER">%s</TD>' % chr2)
                html_post.append(r'<TD ALIGN="LEFT">%d-%d</TD>' % (chr2_left, chr2_right))
                html_post.append(r'<TD ALIGN="RIGHT">%s</TD>' % fg_value_dic["num_pairs"])
                html_post.append(r'<TD ALIGN="RIGHT">%s</TD>' % fg_value_dic["num_reads"])
                html_post.append(r'<TD ALIGN="RIGHT">%.2f</TD>' % float(fg_value_dic["FPKM"]))
                html_post.append(r'</TR>')
                """

                chr1_exon_list, chr2_exon_list = [], []
                for transcript in transcripts:
                    t_value_dic, exons = transcript
                    """
                    chr1, chr1_left, chr1_right = t_value_dic["chr1"], t_value_dic["chr1_left"], t_value_dic["chr1_right"]
                    chr2, chr2_left, chr2_right = None, None, None

                    if "chr2" in t_value_dic:
                        chr2, chr2_left, chr2_right = t_value_dic["chr2"], t_value_dic["chr2_left"], t_value_dic["chr2_right"]
                    """

                    is_fusion_transcript, is_after_fusion = t_value_dic["is_fusion_transcript"], t_value_dic["is_after_fusion"]
                    saw_fusion = False
                    for exon in exons:
                        type = exon[0]
                        if type == "fusion":
                            saw_fusion = True
                            continue

                        if is_after_fusion or saw_fusion:
                            chr2_exon_list.append([exon[2], exon[3]])
                        else:
                            chr1_exon_list.append([exon[2], exon[3]])

                def my_cmp(a, b):
                    if a[0] != b[0]:
                        return a[0] - b[0]
                    else:
                        return a[1] - b[1]
                
                chr1_exon_list = sorted(chr1_exon_list, cmp=my_cmp)
                chr2_exon_list = sorted(chr2_exon_list, cmp=my_cmp)

                def combine_exon_list(exon_list):
                    new_exon_list = []
                    new_exon_list.append(exon_list[0])
                    for exon in exon_list[1:]:
                        last_exon = new_exon_list[-1]

                        if last_exon[1] + 1 >= exon[0]:
                            if last_exon[1] < exon[1]:
                                last_exon[1] = exon[1]
                        else:
                            new_exon_list.append(exon)

                    return new_exon_list

                chr1_exon_list = combine_exon_list(chr1_exon_list)
                chr2_exon_list = combine_exon_list(chr2_exon_list)

                max_intron_length = 100
                def calculate_chr_coord(exon_list, x = sys.maxint):
                    exon = exon_list[0]
                    chr_length = exon[1] - exon[0] + 1
                    if x <= exon[1]:
                        return x - exon[0]
                    
                    for e_idx in range(1, len(exon_list)):
                        last_exon, exon = exon_list[e_idx-1], exon_list[e_idx]
                        intron_length = exon[0] - last_exon[1] - 1

                        chr_length += min(intron_length, max_intron_length)

                        if x <= exon[1]:
                            return chr_length + x - exon[0]
                        
                        chr_length += (exon[1] - exon[0] + 1)

                    return chr_length

                chr1_length = calculate_chr_coord(chr1_exon_list)
                chr2_length = calculate_chr_coord(chr2_exon_list)
                chr_length = chr1_length + chr2_length

                begin_x, begin_y = 130, 0
                height_unit = 80
                max_width = 900.0
                scale_x = min(max_width / chr_length, 1)

                html_post.append(r'<canvas id="fusion_gene_canvas%d" width="%d" height="%d" name="%s_%s-%s"></canvas>' % (i, begin_x + min(chr_length, max_width), height_unit * (len(transcripts) + 1), sample_name, fusion["gene1"], fusion["gene2"]))

                def get_coord(chr1_exon_list, chr2_exon_list, x, is_after_fusion):
                    if is_after_fusion:
                        coord = calculate_chr_coord(chr2_exon_list, x)
                        if dir[1] == "r":
                            coord = chr2_length - coord - 1
                        coord += chr1_length
                    else:
                        coord = calculate_chr_coord(chr1_exon_list, x)
                        if dir[0] == "r":
                            coord = chr1_length - coord - 1

                    return coord

                curr_y = begin_y
                for t_idx in range(len(transcripts)):
                    transcript = transcripts[t_idx]
                    t_value_dic, exons = copy.deepcopy(transcript)
                    chr1, chr1_left, chr1_right = t_value_dic["chr1"], t_value_dic["chr1_left"], t_value_dic["chr1_right"]
                    chr2, chr2_left, chr2_right = None, None, None
                    num_pairs, num_reads, FPKM = t_value_dic["num_pairs"], t_value_dic["num_reads"], t_value_dic["FPKM"]

                    html_post.append(r'<TR>')
                    if "chr2" in t_value_dic:
                        chr2, chr2_left, chr2_right = t_value_dic["chr2"], t_value_dic["chr2_left"], t_value_dic["chr2_right"]
                        html_post.append(r'<TD ALIGN="CENTER">%d. fusion transcript</TD>' % (t_idx + 1))
                    else:
                        html_post.append(r'<TD ALIGN="CENTER">%d. normal transcript</TD>' % (t_idx + 1))

                    html_post.append(r'<TD ALIGN="CENTER">%s</TD>' % chr1)
                    html_post.append(r'<TD ALIGN="LEFT">%d-%d</TD>' % (chr1_left, chr1_right))

                    if chr2:
                        html_post.append(r'<TD ALIGN="CENTER">%s</TD>' % chr2)
                        html_post.append(r'<TD ALIGN="LEFT">%d-%d</TD>' % (chr2_left, chr2_right))
                    else:
                        html_post.append(r'<TD ALIGN="LEFT"></TD>')
                        html_post.append(r'<TD ALIGN="LEFT"></TD>')                       

                    html_post.append(r'<TD ALIGN="RIGHT">%s</TD>' % num_pairs)
                    html_post.append(r'<TD ALIGN="RIGHT">%s</TD>' % num_reads)
                    html_post.append(r'<TD ALIGN="RIGHT">%.2f</TD>' % float(FPKM))
                    html_post.append(r'</TR>')

                    if t_value_dic["is_after_fusion"]:
                        if dir[1] == "r":
                            exons = exons[::-1]
                    elif not t_value_dic["is_fusion_transcript"]:
                        if dir[0] == "r":
                            exons = exons[::-1]

                    is_after_fusion = False
                    if t_value_dic["is_after_fusion"]:
                        is_after_fusion = True
                
                    if not fusion_gene_drawn[cluster_index]:
                        javascript.append(r"ctx.font = '10pt Helvetica';")
                        javascript.append(r"ctx.fillStyle = 'rgb(0 ,0 , 0)';")

                        if t_value_dic["is_fusion_transcript"]:
                            transcript_name = "fusion"
                        else:
                            transcript_name = "normal"

                        transcript_name += ("_transcript_%d" % (t_idx + 1))
                        javascript.append(r"ctx.fillText('%s', %d, %d);" % (transcript_name, 0, curr_y + 55))

                    last_left, last_right = -1, -1
                    fusion_idx_offset = 0
                    for e_idx in range(len(exons)):
                        exon = exons[e_idx]
                        type = exon[0]

                        html_post.append(r'<TR>')

                        if type == "fusion":
                            is_after_fusion = True
                            fusion_idx_offset = -1

                            html_post.append(r'<TD ALIGN="RIGHT">fusion</TD>')
                            html_post.append(r'<TD ALIGN="CENTER">%s</TD>' % exon[1])
                            html_post.append(r'<TD ALIGN="LEFT">%d</TD>' % exon[2])
                            html_post.append(r'<TD ALIGN="CENTER">%s</TD>' % exon[3])
                            html_post.append(r'<TD ALIGN="LEFT">%d</TD>' % exon[4])
                            html_post.append(r'</TR>')
                            continue

                        org_left = left = get_coord(chr1_exon_list, chr2_exon_list, exon[2], is_after_fusion)
                        org_right = right = get_coord(chr1_exon_list, chr2_exon_list, exon[3], is_after_fusion)

                        left = int(left * scale_x)
                        right = int(right * scale_x)

                        if left > right:
                            left, right = right, left

                        left += begin_x
                        right += begin_x

                        html_post.append(r'<TD ALIGN="RIGHT">%d. exon</TD>' % (e_idx + 1 + fusion_idx_offset))
                        html_post.append(r'<TD ALIGN="CENTER">%s</TD>' % exon[1])
                        html_post.append(r'<TD ALIGN="LEFT">%d-%d</TD>' % (exon[2], exon[3]))
                        html_post.append(r'</TR>')

                        if not fusion_gene_drawn[cluster_index]:
                            # draw intron line
                            if e_idx > 0 and left - last_right > 1:
                                javascript.append(r"ctx.strokeStyle = 'rgb(0, 0, 0)';")
                                javascript.append(r"ctx.beginPath ();")
                                javascript.append(r"ctx.moveTo (%d, %d);" % (last_right + 1, curr_y + 65))
                                javascript.append(r"ctx.lineTo (%d, %d);" % (left, curr_y + 65))
                                javascript.append(r"ctx.closePath ();")
                                javascript.append(r"ctx.stroke ();")

                            # draw exon
                            if is_after_fusion:
                                javascript.append(r"ctx.fillStyle = 'rgb(0, 0, 200)';")
                            else:
                                javascript.append(r"ctx.fillStyle = 'rgb(200, 0, 0)';")

                            width = right - left + 1
                            javascript.append(r"ctx.fillRect (%d, %d, %d, 12);" % (left, curr_y + 59, width))
                            javascript.append(r"ctx.fillText('%d', %d, %d);" % (e_idx + 1 + fusion_idx_offset, left, curr_y + 82))

                            # draw base coverage
                            coverage = copy.deepcopy(exon[-1])
                            if is_after_fusion:
                                coverage = coverage[::-1]

                            max_base_cov = t_value_dic["max_base_cov"]
                            max_cov_height = 35
                            javascript.append(r"ctx.strokeStyle = 'rgb(0, 200, 0)';")
                            javascript.append(r"var cov_array = [")
                            cov_string = ""

                            coverage_width = len(coverage)
                            for scaled_cov_idx in range(width):
                                cov_idx = int(scaled_cov_idx * coverage_width / float(width))
                                if cov_idx < coverage_width:
                                    base_cov = coverage[cov_idx]
                                elif coverage_width > 0:
                                    base_cov = coverage[-1]
                                else:
                                    base_cov = 1

                                if max_base_cov > 0:
                                    rescaled_cov = max(base_cov * max_cov_height / max_base_cov, 1)
                                else:
                                    rescaled_cov = 0

                                cov_string += ("%d" % rescaled_cov)
                                if cov_idx + 1 < len(coverage):
                                    cov_string += ","

                            javascript.append(cov_string)
                            javascript.append(r"];")

                            javascript.append("for (var i = 0; i < cov_array.length; ++i) {")
                            javascript.append(r"ctx.beginPath ();")
                            javascript.append(r"ctx.moveTo (i + %d, %d);" % (left, curr_y + 55))
                            javascript.append(r"ctx.lineTo (i + %d, %d - cov_array[i]);" % (left, curr_y + 55))
                            javascript.append(r"ctx.closePath ();")
                            javascript.append(r"ctx.stroke ();")
                            javascript.append("}")

                        last_left, last_right = left, right

                    curr_y += height_unit
                        
                html_post.append(r'</TR></TABLE>')
                html_post.append(r'</BR></BR>')
                
                if not fusion_gene_drawn[cluster_index]:
                    javascript.append(r"}")
                    javascript.append(r"}")
                    javascript.append(r'</script>')

                    fusion_gene_drawn[cluster_index] = True

            left_blast_genomic = blast_output(output_dir + "blast_genomic", left_seq)
            right_blast_genomic = blast_output(output_dir + "blast_genomic", right_seq)
            blast_genomic = blast_output(output_dir + "blast_genomic", seq)

            left_blast_nt = blast_output(output_dir + "blast_nt", left_seq)
            right_blast_nt = blast_output(output_dir + "blast_nt", right_seq)
            blast_nt = blast_output(output_dir + "blast_nt", seq)

            html_post.append(r'<TABLE CELLPADDING=3 BORDER="1"><TR><TD ALIGN="CENTER">Left flanking sequence</TD><TD ALIGN="CENTEr">Right flanking sequence</TD></TR>')
            html_post.append(r'<TR><TD>%s</TD><TD>%s</TD></TR></TABLE>' % (left_seq, right_seq))

            html_post.append(r'<H2>blast search - genome</A></H2>')
            html_post.append(r'<H3>left flanking sequence - %s</H3>' % left_seq)
            html_post.append(r'<PRE>%s</PRE>' % left_blast_genomic)
            html_post.append(r'<H3>right flanking sequence - %s</H3>' % right_seq)
            html_post.append(r'<PRE>%s</PRE>' % right_blast_genomic)

            html_post.append(r'<H2>blast search - nt</A></H2>')
            html_post.append(r'<H3>left flanking sequence - %s</H3>' % left_seq)
            html_post.append(r'<PRE>%s</PRE>' % left_blast_nt)
            html_post.append(r'<H3>right flanking sequence - %s</H3>' % right_seq)
            html_post.append(r'<PRE>%s</PRE>' % right_blast_nt)

            html_post.append(r'<H2><A NAME="read_%d"></A><BR>reads</H2>' % i)
            read_output = fusion["read_output"]
            html_post.append(r'<PRE>%s</PRE>' % '\n'.join(read_output))

            html_post.append(r'<H2><A NAME="pair_%d"></A><BR>%d pairs</H2>' % (i, len(pair_coords)))
            html_post.append(r'<PRE>%s</PRE>' % '\n'.join(pair_coords))
            html_post.append(r'<BR/><BR/><BR/>')

        html_post.append(r'</BODY>')
        html_post.append(r'</HTML>')

        fusion_gene_draw_str = ""
        for index in fusion_gene_indices:
            isoform_index, cluster_index = index
            fusion_gene_draw_str += "fusion_gene_draw%d(%d);" % (cluster_index, isoform_index)
            
        html_body.append(r'<BODY text="#000000" bgcolor="#FFFFFF" onload="%s">' % fusion_gene_draw_str)

        for line in html_prev + javascript + html_body + html_post:
            print >> html_file, line

        html_file.close()
        txt_file.close()
        
        if params.tex_table:
            print >> tex_table_file, r"\hline"
            print >> tex_table_file, r"\end{tabular}}}"
            print >> tex_table_file, r'\end{document}'
            tex_table_file.close()
            os.system("pdflatex --output-directory=%s %s" % (output_dir, tex_table_file_name))

    print >> sys.stderr, "[%s] Reporting final fusion candidates in html format" % right_now()

    # Cufflinks-Fusion
    fusion_gene_list = []
    read_fusion_genes(fusion_gene_list)

    fusion_list = []
    read_fusion_list(fusion_list)

    cluster_list = []
    cluster_fusion(fusion_list, fusion_gene_list, cluster_list)

    generate_html_impl(fusion_list, cluster_list, fusion_gene_list)



# Format a DateTime as a pretty string.  
# FIXME: Currently doesn't support days!
def formatTD(td):
  hours = td.seconds // 3600
  minutes = (td.seconds % 3600) // 60
  seconds = td.seconds % 60
  return '%02d:%02d:%02d' % (hours, minutes, seconds) 


# Generate a new temporary filename in the user's tmp directory
def tmp_name():
    tmp_root = tmp_dir
    if os.path.exists(tmp_root):
        pass
    else:        
        os.mkdir(tmp_root)
    return tmp_root + os.tmpnam().split('/')[-1] 


def die(msg=None):
 if msg is not None: 
    print >> sys.stderr, msg
    sys.exit(1)

    
# rough equivalent of the 'which' command to find external programs
# (current script path is tested first, then PATH envvar)
def which(program):
    def is_executable(fpath):
        return os.path.exists(fpath) and os.access(fpath, os.X_OK)
    fpath, fname = os.path.split(program)
    if fpath:
        if is_executable(program):
            return program
    else:
        progpath = os.path.join(bin_dir, program)
        if is_executable(progpath):
           return progpath
        for path in os.environ["PATH"].split(os.pathsep):
           progpath = os.path.join(path, program)
           if is_executable(progpath):
              return progpath
    return None


def prog_path(program):
    progpath = which(program)
    if progpath == None:
        die("Error locating program: "+program)
    return progpath


def get_version():
   return "2.1.1"


def main(argv=None):
    warnings.filterwarnings("ignore", "tmpnam is a potential security risk")
    
    # Initialize default parameter values
    params = TopHatFusionParams()
    try:
        if argv is None:
            argv = sys.argv
            args = params.parse_options(argv)
            params.check()

        bwt_idx_prefix = args[0]

        print >> sys.stderr, "[%s] Beginning TopHat-Fusion post-processing run (v%s)" % (right_now(), get_version())
        print >> sys.stderr, "-----------------------------------------------" 
        
        start_time = datetime.now()
        prepare_output_dir()
        sample_updated = check_samples()

        if not params.skip_fusion_kmer:
            map_fusion_kmer(bwt_idx_prefix, params, sample_updated)

        if not params.skip_filter_fusion:
            filter_fusion(bwt_idx_prefix, params)

        if not params.skip_blast:
            do_blast(params)

        if not params.skip_read_dist:
            read_dist(params)

        if not params.skip_html:
            generate_html(params)
        
        global run_log
        run_log = open(logging_dir + "run.log", "w", 0)
        global run_cmd
        run_cmd = " ".join(argv)
        print >> run_log, run_cmd

        finish_time = datetime.now()
        duration = finish_time - start_time
        print >> sys.stderr,"-----------------------------------------------"
        print >> sys.stderr, "[%s] Run complete [%s elapsed]" %  (right_now(), formatTD(duration))
        
    except Usage, err:
        print >> sys.stderr, sys.argv[0].split("/")[-1] + ": " + str(err.msg)
        print >> sys.stderr, "\tfor detailed help see http://tophat-fusion.sourceforge.net/manual.html"
        return 2


if __name__ == "__main__":
    sys.exit(main())