TMM normalization is recommended for RNA-seq data generally when the majority of genes are not differentially expressed.
Usage
tmm(object, ...)
# S4 method for matrix
tmm(object)
# S4 method for SummarizedExperiment
tmm(object)Examples
## bcbioRNASeq ====
data(bcb)
x <- tmm(bcb)
#> → Applying trimmed mean of M-values (TMM) normalization.
summary(x)
#> control_rep1 control_rep2 control_rep3 fa_day7_rep1
#> Min. : 0 Min. : 0.0 Min. : 0.0 Min. : 0
#> 1st Qu.: 0 1st Qu.: 0.0 1st Qu.: 0.0 1st Qu.: 0
#> Median : 704 Median : 288.6 Median : 702.1 Median : 1028
#> Mean : 10258 Mean : 12269.0 Mean : 10550.9 Mean : 9055
#> 3rd Qu.: 6999 3rd Qu.: 8546.9 3rd Qu.: 6738.5 3rd Qu.: 9298
#> Max. :166465 Max. :278610.6 Max. :141166.6 Max. :129852
#> fa_day7_rep2 fa_day7_rep3
#> Min. : 0.00 Min. : 0.00
#> 1st Qu.: 25.84 1st Qu.: 0.14
#> Median : 1031.48 Median : 866.33
#> Mean : 8927.31 Mean : 9316.41
#> 3rd Qu.: 8121.07 3rd Qu.: 6703.86
#> Max. :170067.05 Max. :141567.97