search.gadem {cobindR} | R Documentation |
function performs TFBS prediction denovo or based on transfac / jaspar matrices pwms using rGADEM. If append=T, predicted hits are appended to the hits in the input object.
## S4 method for signature 'cobindr' search.gadem(x, deNovo = FALSE, append = F, background_scan = FALSE)
x |
an object of the class "cobindr", which will hold all necessary information about the sequences and the hits. |
deNovo |
logical flag, if deNOVO=TRUE a denovo search is startet. Otherwise the given PFMs are used as seed. |
append |
logical flag, if append=TRUE the binding sites will be appended to already existing results |
background_scan |
logical flag, if background_scan=TRUE the function will search for binding sites in the set of background sequences |
x |
an object of the class "cobindr" including the predicted transcription factor binding sites |
Robert Lehmann <r.lehmann@biologie.hu-berlin.de>
uses package "rGADEM" (http://www.bioconductor.org/packages/release/bioc/html/rGADEM.html)
############################################################ # use simulated sequences library(Biostrings) n <- 600 # number of input sequences l <- 150 # length of sequences n.hits <- 600 # 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(70, 90)) { 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 rGADEM - commented out due to long time required # runObj.bs <- search.gadem(runObj) # show results # plot.positions(runObj.bs) #clean up unlink(tmp.file)