[Bioc-sig-seq] Short demo of some recent additions to Biostrings
hpages at fhcrc.org
hpages at fhcrc.org
Fri May 30 21:13:42 CEST 2008
Hi,
There are some recent additions to Biostrings and to the BSgenome data
packages that I'd like to illustrate here with a small script. This script
will focus on the following recent features:
- injecting SNPs in the chromosome sequences
- countPDict() and matchPDict() supporting IUPAC ambiguity letters
in the subject
- masking regions of the chromosome sequences
This will only work with the latest version of Biostrings i.e.
v 2.8.11 in release and v 2.9.16 in devel, which are not online yet but
will be in the next 24 hours. Also you need the latest version of the
BSgenome data package for hg18 (v 1.3.7) which contains 3 built-in
masks for each chromosome sequence, and the SNPlocs.Hsapiens.dbSNP.20071016
package which contains the basic SNP information for hg18.
In order to keep this short, I give the commands only, not the output they
produce. I've tested this on a 64-bit Linux machine (see sessionInfo() at
the end for the details). For more details, please look at the GenomeSearching
vignette in the BSgenome package (used to be in Biostrings) and at the man
pages for the individual functions. Please note that this is still a work
in progress and that the vignette and the man pages are not complete yet
(I'm actively working on the vignette though). Feedback and bug reports
are welcome. Thanks!
H.
library(Biostrings)
### Load the probe sequences (25-mers) for chip hgu95av2 (Affymetrix) and
### store them in a PDict object that will allow us to do fast searching.
library(hgu95av2probe)
dict0 <- hgu95av2probe$sequence
length(dict0) # 201800 probes
pdict <- PDict(dict0)
### Load Human genome from UCSC (version hg18) and load the chr1 sequence.
library(BSgenome.Hsapiens.UCSC.hg18)
Hsapiens
chr1 <- Hsapiens$chr1
chr1 # note the 3 inactive built-in masks
alphabetFrequency(chr1)
### Count the number of hits per probe (exact matching).
c1 <- countPDict(pdict, chr1) # takes about 20 sec.
sum(c1) # 209980 (total number of hits)
sum(c1 == 0) # 191209 (number of probes with no hit)
### Inject the known SNPs (from dbSNP) in the hg18 genome and load chr1
### again (now with the SNPs embedded in the sequence). Note that the
### SNPs are really injected when the sequence is loaded (on-the-fly
### injection at sequence load time).
available.SNPs()
library(SNPlocs.Hsapiens.dbSNP.20071016)
hg18snp <- injectSNPs(Hsapiens, 'SNPlocs.Hsapiens.dbSNP.20071016')
hg18snp # note the additional line "with SNPs injected from..."
chr1snp <- hg18snp$chr1 # load the sequence and inject the SNPs
chr1snp
alphabetFrequency(chr1snp) # note the IUPAC ambiguity letters
### By default countPDict()/matchPDict() do exact matching so they
### don't treat these ambiguity letters as ambiguities.
c1snp <- countPDict(pdict, chr1snp) # about 20 sec. again
sum(c1snp) # 197165
sum(c1snp == 0) # 192165
### To treat the ambiguity letters in the subject as ambiguities,
### use the 'fixed=c(pattern=TRUE, subject=FALSE)' option (or its
### shorter form 'fixed="pattern"').
c1snpN <- countPDict(pdict, chr1snp, fixed="pattern") # doesn't work!
### The above didn't work because the internal algorithm cannot deal
### with regions with a high density of ambiguity letters, and the
### N-blocks are such regions! The solution is too mask these regions
### by activating the mask of assembly gaps (built-in mask).
active(masks(chr1snp))[1] <- TRUE
alphabetFrequency(chr1snp)
chr1snp # about 9% of the sequence is masked now
c1snpN <- countPDict(pdict, chr1snp, fixed="pattern") # takes about 22 sec.
sum(c1snpN) # 217121 (the total number of hits has increased...)
sum(c1snpN == 0) # 191137 (... and there are less probes with no hit)
### Just a sanity check: the number of hits per probe can only increase!
all(c1snpN >= c1)
sum(c1snpN > c1) # 248
which(c1snpN > c1)[1:10] # the first 10 probes that match at SNP locations
which(c1snp == max(c1snp)) # the probe with the greatest number of hits...
c1snpN[201534] - c1[201534] # ... gains 199 hits with the SNP version of chr1
### Let's try to "see" some SNPs
probe0 <- dict0[201534] # the probe with the greatest number of hits
hits0 <- matchPattern(probe0, chr1snp, fixed="pattern")
hits0
snpperhit <- alphabetFrequency(hits0, baseOnly=TRUE)[ , 'other']
hits0[snpperhit != 0] # hits containing at least 1 SNP
max(snpperhit) # there are at most 4 SNPs per hit
hits0[snpperhit == 4] # display them
> sessionInfo()
R version 2.7.0 (2008-04-22)
x86_64-unknown-linux-gnu
locale:
LC_CTYPE=en_CA.UTF-8;LC_NUMERIC=C;LC_TIME=en_CA.UTF-8;LC_COLLATE=en_CA.UTF-8;LC_MONETARY=C;LC_MESSAGES=en_CA.UTF-8;LC_PAPER=en_CA.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_CA.UTF-8;LC_IDENTIFICATION=C
attached base packages:
[1] tools stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] SNPlocs.Hsapiens.dbSNP.20071016_0.99.1
[2] BSgenome.Hsapiens.UCSC.hg18_1.3.7
[3] BSgenome_1.8.3
[4] Biostrings_2.8.11
[5] hgu95av2probe_2.2.0
[6] matchprobes_1.12.0
[7] affy_1.18.1
[8] preprocessCore_1.2.0
[9] affyio_1.8.0
[10] Biobase_2.0.1
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