/usr/lib/R/site-library/Biostrings/unitTests/test_matchDNAPattern.R.FIXME is in r-bioc-biostrings 2.42.1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 | ## ============================ Utility functions ============================
## Check that the offsets and substrings in Biostring object 'matches'
## are the expected ones.
## subject: BioString object of length 1
## expected_roffsets: matrix of the expected relative offsets of the matches
## matches: BioString object returned by matchDNAPattern("findme", subject)
checkBioStringMatches <- function(subject, expected_roffsets, matches)
{
expected_aoffsets <- expected_roffsets + subject@offsets[1,1] - 1
checkEquals(expected_aoffsets, matches@offsets)
## We need to check for this particular case because surprinsingly,
## substring() doesn't work with 'first' and 'last' of zero length
if (dim(expected_roffsets)[1] != 0) {
first <- expected_roffsets[,1]
last <- expected_roffsets[,2]
expected_substrings <- substring(as.character(subject), first, last)
checkEquals(expected_substrings, as.character(matches))
}
}
checkExactMatches <- function(pattern, subject, expected_pos=numeric(0))
{
matches <- matchDNAPattern(pattern, subject)
expected_roffsets <- cbind(expected_pos, expected_pos+nchar(pattern)-1, deparse.level=0)
checkBioStringMatches(subject, expected_roffsets, matches)
expected_length <- length(expected_pos)
checkEquals(logical(expected_length), as.character(matches) != pattern)
}
## =================== Tests that should PASS (fixed bugs) ===================
## Checks that the fix in the matchIndexToBioString() C-function
## for the "wrong offset" bug works for every cases this function
## deals with.
test_matchIndexToBioString <- function()
{
seq <- c("CCCC", "TTAATT")
subject <- DNAString(seq)[2]
## CASE 'nmatch == 0'
checkExactMatches("AAA", subject)
## CASE 'nmatch == 1'
checkExactMatches("AA", subject, c(3))
## CASE 'nmatchIndex == 2*nmatch'
checkExactMatches("TT", subject, c(1,5))
## DEFAULT CASE
checkExactMatches("A", subject, c(3,4))
}
## Checks the ShiftOr_matchInternal() C-function.
test_ShiftOr_matchInternal_A1 <- function()
{
pattern <- DNAString("CAG")
subject <- DNAString("CAGTTT")
expected_roffsets <- rbind(c(1, 3))
matches <- matchDNAPattern(pattern, subject, mis=1)
checkBioStringMatches(subject, expected_roffsets, matches)
}
test_ShiftOr_matchInternal_A2 <- function()
{
pattern <- DNAString("AKADAKA")
subject <- DNAString("ATATGAATAAAGA")
expected_roffsets <- rbind(c(7, 13))
matches <- matchDNAPattern(pattern, subject, mis=0)
checkBioStringMatches(subject, expected_roffsets, matches)
}
test_ShiftOr_matchInternal_A3 <- function()
{
pattern <- DNAString("AKADAKA")
subject <- DNAString("ATATGAATAAAGA")
expected_roffsets <- rbind(c(3, 9),
c(7, 13))
matches <- matchDNAPattern(pattern, subject, mis=1)
checkBioStringMatches(subject, expected_roffsets, matches)
}
test_ShiftOr_matchInternal_A4 <- function()
{
pattern <- DNAString("AKADAKA")
subject <- DNAString("ATATGAATAAAGA")
expected_roffsets <- rbind(c(1,7),
c(3, 9),
c(7, 13))
matches <- matchDNAPattern(pattern, subject, mis=2)
checkBioStringMatches(subject, expected_roffsets, matches)
}
test_ShiftOr_matchInternal_B1 <- function()
{
pattern <- DNAString("AAAA")
subject <- DNAString("AAAAC")
expected_roffsets <- rbind(c(-1, 2),
c( 0, 3),
c( 1, 4),
c( 2, 5),
c( 3, 6))
matches <- matchDNAPattern(pattern, subject, mis=2)
checkBioStringMatches(subject, expected_roffsets, matches)
}
test_ShiftOr_matchInternal_B2 <- function()
{
pattern <- DNAString("ATC")
subject <- DNAString("CATCACTCA")
expected_roffsets <- rbind(c(-1, 1),
c( 2, 4),
c( 4, 6),
c( 5, 7),
c( 6, 8),
c( 9, 11))
matches <- matchDNAPattern(pattern, subject, mis=2)
checkBioStringMatches(subject, expected_roffsets, matches)
}
test_ShiftOr_matchInternal_B3 <- function()
{
pattern <- DNAString("AAAA")
subject <- DNAString("AAAAC")
expected_roffsets <- rbind(c(-2, 1),
c(-1, 2),
c( 0, 3),
c( 1, 4),
c( 2, 5),
c( 3, 6),
c( 4, 7))
## Provoques an error
matches <- matchDNAPattern(pattern, subject, mis=3)
checkBioStringMatches(subject, expected_roffsets, matches)
}
test_ShiftOr_matchInternal_B4 <- function()
{
pattern <- DNAString("AAAA")
subject <- DNAString("AAAAC")
## Here: mis >= nchar(pattern). So you get a match
## whatever the relative position of the pattern is!
## However, a reasonable expectation is to have
## matchDNAPattern only return the following matches:
expected_roffsets <- rbind(c(-2, 1),
c(-1, 2),
c( 0, 3),
c( 1, 4),
c( 2, 5),
c( 3, 6),
c( 4, 7),
c( 5, 8))
matches <- matchDNAPattern(pattern, subject, mis=4)
checkBioStringMatches(subject, expected_roffsets, matches)
}
## ========== Tests that should PASS on 64-bit platform (fixed bugs) =========
## ================= and FAIL on 32-bit platform (not a bug) =================
## This test uses a big subject (10 millions of characters)
## in order to test the speed of the ShiftOr algorithm.
test_ShiftOr_matchInternal_C1 <- function()
{
f <- file(system.file("extdata", "bigrandomTGCA.txt", package="Biostrings"))
big <- scan(file=f, what="")
subject <- DNAString(big)
## Simple pattern, mis=5
pattern <- DNAString("TTTTTTTTTTTTTTTTTTTTT")
expected_roffsets <- rbind(c(2725443, 2725463),
c(6535062, 6535082),
c(6535064, 6535084),
c(7765179, 7765199),
c(8491897, 8491917),
c(8491898, 8491918),
c(8491899, 8491919),
c(9233437, 9233457))
matches <- matchDNAPattern(pattern, subject, mis=5)
checkBioStringMatches(subject, expected_roffsets, matches)
## With a 32 char long pattern, mis=10
pattern32 <- DNAString(substr(big, 1, 32)) #substr(subject, 1, 32)
expected_roffsets <- rbind(c(1,32),
c(3807182, 3807213),
c(9926155, 9926186))
matches <- matchDNAPattern(pattern32, subject, mis=10)
checkBioStringMatches(subject, expected_roffsets, matches)
## With a 64 char long pattern (works on 64-bit platforms only)
pattern64 <- DNAString(substr(big, 1, 64)) #substr(subject, 1, 64)
expected_roffsets <- rbind(c(1,64),
c(1049302, 1049365))
matches <- matchDNAPattern(pattern64, subject, mis=24)
checkBioStringMatches(subject, expected_roffsets, matches)
}
## =================== Tests that should FAIL (open bugs) ====================
## ===========================================================================
test_openbug1 <- function()
{
pattern <- DNAString("CAG")
subject <- DNAString("GTTCA")
matches <- matchDNAPattern(pattern, subject, mis=2)
multi <- DNAString(c("TTT", "GTTCA", "TT"))
subject2 <- multi[2]
matches2 <- matchDNAPattern(pattern, subject2, mis=2)
checkEquals(as.character(matches), as.character(matches2))
}
# TODO: Move this test to another file. Has nothing to do
# with testing the matchDNAPattern() function...
# Not sure this one is a bug. Are we supposed to always
# be allowed to change a value in a matrix? What "says" R?
test_openbug2 <- function()
{
s <- DNAString("ACGT")
s@offsets[1,1] <- 2
## Provoques an error
show(s)
}
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