counts {TCseq} | R Documentation |
counts
extract raw read counts stored in a TCA
object or
compute normalized counts.
## S4 method for signature 'TCA' counts(object, normalization = "none", lib.norm = TRUE, log = FALSE, ...) ## S4 replacement method for signature 'TCA' counts(object) <- value
object |
a |
normalization |
character string giving the normalization method.
Options are ' |
lib.norm |
logical indicating whether or not use effective library
size (see 'Details' below) when |
log |
logical if |
... |
|
value |
an integer matrix |
when calculating normalized counts, library size can be rescaled to minimize the log-fold changes between samples for most genomic features (e.g. genes, binding sites) by multiplying a scale factor. The rescaled library size is called effective library size. In this function, the scale factor is calculated using the weighted trimmed mean of M-values (TMM, Robinson et al (2010))
If log2 values are computed, a small count would be added to avoid logarithm of zero. a small count is set proportional to the library size, the average value of such small counts of all libraries counts is set to 0.25 by default.
An integer matrix
Mengjun Wu
Robinson, M. D., & Oshlack, A. (2010). A scaling normalization method for differential expression analysis of RNA-seq data. Genome biology, 11(3), 1.
data(tca_ATAC) c <- counts(tca_ATAC) # normalized counts table c_norm <- counts(tca_ATAC, normalization='rpkm')