runMetaGene {groHMM} | R Documentation |
Supports parallel processing using mclapply in the 'parallel' package. To change the number of processors, set the option 'mc.cores'.
runMetaGene(features, reads, anchorType = "TSS", size = 100L, normCounts = 1L, up = 10000L, down = NULL, sampling = FALSE, nSampling = 1000L, samplingRatio = 0.1, ...)
features |
GRanges A GRanges object representing a set of genomic coordinates, i.e., set of genes. |
reads |
GRanges of reads. |
anchorType |
Either 'TSS' or 'TTS'. Metagene will be centered on the transcription start site(TSS) or transcription termination site(TTS). Default: TSS. |
size |
Numeric. The size of the moving window. Default: 100L |
normCounts |
Numeric. Normalization vector such as average reads. Default: 1L |
up |
Numeric. Distance upstream of each feature to align and histogram. Default: 1 kb |
down |
Numeric. Distance downstream of each feature to align and histogram. If NULL, down is same as up. Default: NULL |
sampling |
Logical. If TRUE, subsampling of Metagene is used. Default: FALSE |
nSampling |
Numeric. Number of subsampling. Default: 1000L |
samplingRatio |
Numeric. Ratio of sampling for features. Default: 0.1 |
... |
Extra argument passed to mclapply. |
A list of integer-Rle for sense and antisene.
Minho Chae
features <- GRanges("chr7", IRanges(start=1000:1001, width=rep(1,2)), strand=c("+", "-")) reads <- GRanges("chr7", IRanges(start=c(1000:1003, 1100:1101), width=rep(1, 6)), strand=rep(c("+","-"), 3)) ## Not run: # mg <- runMetaGene(features, reads, size=4, up=10)