Trimmed mean of M-values

Source: R/tmm-methods.R

TMM normalization is recommended for RNA-seq data generally when the majority of genes are not differentially expressed.

tmm(object, ...)

# S4 method for matrix
tmm(object)

# S4 method for SummarizedExperiment
tmm(object)

Arguments

object

Object.
...

Additional arguments.

Value

matrix.

Note

Updated 2019-08-20.

References

Robinson and Oshlack (2010).

See also

Examples

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