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Last data update: 2014.03.03 |
function to predict transcription factor binding sites using the method matchPWM from package BiostringsDescriptionfunction to predict transcription factor binding sites using the method matchPWM from package Biostrings Usage## S4 method for signature 'cobindr' search.pwm(x, min.score = "80%", append = FALSE, background_scan = FALSE, n.cpu = NA) Arguments
Value
Author(s)Robert Lehmann <r.lehmann@biologie.hu-berlin.de Referencesuses matchPWM from package "Biostrings" (http://www.bioconductor.org/packages/release/bioc/html/Biostrings.html) See Also
Examples
############################################################
# use simulated sequences
library(Biostrings)
n <- 400 # number of input sequences
l <- 500 # length of sequences
n.hits <- 250 # number of 'true' binding sites
bases <- c("A","C","G","T") # alphabet
# generate random input sequences with two groups with differing GC content
seqs <- sapply(1:(3*n/4), function(x) paste(sample(bases, l, replace=TRUE,
prob=c(.3,.22,.2,.28)), collapse=""))
seqs <- append(seqs, sapply(1:(n/4), function(x) paste(sample(bases, l, replace=TRUE,
prob=c(.25,.25,.25,.25)), collapse="")))
path <- system.file('extdata/pfms/myod.tfpfm',package='cobindR')
motif <- read.transfac.pfm(path)[[1]] # get PFM of binding site
# add binding sites with distance specificity
for(position in c(110, 150)) {
hits <- apply(apply(motif, 2, function(x) sample(x=bases, size=n.hits, prob=x,
replace=TRUE)), 1, paste, collapse='')
pos.hits <- round(rnorm(n.hits, mean=position, sd=8))
names(pos.hits) <- sample(1:n, n.hits)
for(i in 1:n.hits) substr(seqs[as.integer(names(pos.hits)[i])], start=pos.hits[i],
stop=pos.hits[i]+ncol(motif)) <- hits[i]
}
#save sample sequences in fasta file
tmp.file <- tempfile(pattern = "cobindr_sample_seq", tmpdir = tempdir(), fileext = ".fasta")
writeXStringSet(DNAStringSet(seqs), tmp.file)
#run cobindr
cfg <- cobindRConfiguration()
sequence_type(cfg) <- 'fasta'
sequence_source(cfg) <- tmp.file
sequence_origin(cfg) <- 'artificial sequences'
pfm_path(cfg) <- system.file('extdata/pfms',package='cobindR')
pairs(cfg) <- 'V$MYOD_01 V$MYOD_01'
runObj <- cobindr(cfg, name='cobindr test using sampled sequences')
# perform tfbs prediction using matchPWM
runObj.bs <- search.pwm(runObj, min.score = '90')
# show results
plot.positionprofile(runObj.bs)
# clean up
unlink(tmp.file)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(cobindR)
Attaching package: 'cobindR'
The following object is masked from 'package:base':
sequence
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/cobindR/search.pwm.Rd_%03d_medium.png", width=480, height=480)
> ### Name: search.pwm
> ### Title: function to predict transcription factor binding sites using the
> ### method matchPWM from package Biostrings
> ### Aliases: search.pwm search.pwm-method search.pwm,cobindr-method
> ### Keywords: manip iteration methods
>
> ### ** Examples
>
> ############################################################
> # use simulated sequences
> library(Biostrings)
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Loading required package: S4Vectors
Loading required package: stats4
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
colMeans, colSums, expand.grid, rowMeans, rowSums
Loading required package: IRanges
Loading required package: XVector
>
> n <- 400 # number of input sequences
> l <- 500 # length of sequences
> n.hits <- 250 # number of 'true' binding sites
> bases <- c("A","C","G","T") # alphabet
> # generate random input sequences with two groups with differing GC content
> seqs <- sapply(1:(3*n/4), function(x) paste(sample(bases, l, replace=TRUE,
+ prob=c(.3,.22,.2,.28)), collapse=""))
> seqs <- append(seqs, sapply(1:(n/4), function(x) paste(sample(bases, l, replace=TRUE,
+ prob=c(.25,.25,.25,.25)), collapse="")))
> path <- system.file('extdata/pfms/myod.tfpfm',package='cobindR')
> motif <- read.transfac.pfm(path)[[1]] # get PFM of binding site
[1] "ES_Sox2_1_c1058"
[1] "ES_Klf4_3_c1373"
> # add binding sites with distance specificity
> for(position in c(110, 150)) {
+ hits <- apply(apply(motif, 2, function(x) sample(x=bases, size=n.hits, prob=x,
+ replace=TRUE)), 1, paste, collapse='')
+ pos.hits <- round(rnorm(n.hits, mean=position, sd=8))
+ names(pos.hits) <- sample(1:n, n.hits)
+ for(i in 1:n.hits) substr(seqs[as.integer(names(pos.hits)[i])], start=pos.hits[i],
+ stop=pos.hits[i]+ncol(motif)) <- hits[i]
+ }
> #save sample sequences in fasta file
> tmp.file <- tempfile(pattern = "cobindr_sample_seq", tmpdir = tempdir(), fileext = ".fasta")
> writeXStringSet(DNAStringSet(seqs), tmp.file)
> #run cobindr
> cfg <- cobindRConfiguration()
Warning message:
In .local(.Object, ...) :
no config-file defined, generating configuration-object with default values
> sequence_type(cfg) <- 'fasta'
> sequence_source(cfg) <- tmp.file
> sequence_origin(cfg) <- 'artificial sequences'
> pfm_path(cfg) <- system.file('extdata/pfms',package='cobindR')
> pairs(cfg) <- 'V$MYOD_01 V$MYOD_01'
> runObj <- cobindr(cfg, name='cobindr test using sampled sequences')
[1] "Creating a new experiment!"
reading file /tmp/RtmpF7tCZz/cobindr_sample_seq6cb4619ec069.fasta ...
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reading pfm files: /home/ddbj/local/lib64/R/library/cobindR/extdata/pfms ...
[1] "ES_Sox2_1_c1058"
[1] "ES_Klf4_3_c1373"
[1] "ES_Oct4_1_c570"
[1] "ES_Sox2_1_c1058"
ignored files:
Using the parallel (multicore) version of cobindR - function cpg.gc.content with 4 cores
There were 50 or more warnings (use warnings() to see the first 50)
> # perform tfbs prediction using matchPWM
> runObj.bs <- search.pwm(runObj, min.score = '90')
finding binding sites for 4 PWMs...
Using the parallel (multicore) version of cobindR - function make.character with 4 cores
Using the parallel (multicore) version of cobindR - function find.hits with 4 cores
finding hits for PWM ES_Sox2_1_c1058 ...
finding hits for PWM ES_Klf4_3_c1373 ...
finding hits for PWM ES_Oct4_1_c570 ...
finding hits for PWM ES_Sox2_1_c1058 ...
found 0 hits for PWM ES_Klf4_3_c1373 ...
found 5 hits for PWM ES_Oct4_1_c570 ...
found 356 hits for PWM ES_Sox2_1_c1058 ...
found 356 hits for PWM ES_Sox2_1_c1058 ...
found 717 hits in total.
> # show results
> plot.positionprofile(runObj.bs)
> # clean up
> unlink(tmp.file)
>
>
>
>
>
> dev.off()
null device
1
>
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Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and