The segmentSeq package is intended to take multiple samples of high-throughput data (together with replicate information) and identify regions of the genome which have a (reproducibly) high density of tags aligning to them. The package was developed for use in identifying small RNA precursors from small RNA sequencing data, but may also be useful in some mRNA-Seq and chIP-Seq applications.
To use the package, we construct an
from sets of alignment files using either the
function to read text files or the
readBAM function to
read from BAM format files.
We then use the
processAD function to identify all
potential subsegments of the data and the number of tags that align to
these subsegments. We then use either a heuristic or empirical Bayesian
approach to segment the genome into ‘loci’ and ‘null’ regions. We can then
acquire posterior likelihoods for each set of replicates which tell us
whether a region is likely to be a locus or a null in that replicate group.
The segmentation is designed to be usable by the
baySeq package to allow
differential expression analyses to be carried out on the discovered loci.
The package (optionally) makes use of the 'snow' package for parallelisation of computationally intensive functions. This is highly recommended for large data sets.
See the vignette for more details.
Thomas J. Hardcastle
Maintainer: Thomas J. Hardcastle <[email protected]>
Hardcastle T.J., Kelly, K.A. and Balcombe D.C. (2011). Identifying small RNA loci from high-throughput sequencing data. In press.
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# Define the files containing sample information. datadir <- system.file("extdata", package = "segmentSeq") libfiles <- c("SL9.txt", "SL10.txt", "SL26.txt", "SL32.txt") # Establish the library names and replicate structure. libnames <- c("SL9", "SL10", "SL26", "SL32") replicates <- c(1,1,2,2) # Process the files to produce an 'alignmentData' object. alignData <- readGeneric(file = libfiles, dir = datadir, replicates = replicates, libnames = libnames) # Process the alignmentData object to produce a 'segData' object. sD <- processAD(alignData, gap = 100, cl = NULL)
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