getRPKM {recount} | R Documentation

## Compute an RPKM matrix based on a RangedSummarizedExperiment object

### Description

For some analyses you might be interested in transforming the counts into RPKMs which you can do with this function.

### Usage

    getRPKM(rse, length_var = "bp_length", mapped_var = NULL)

### Arguments

`rse` | A RangedSummarizedExperiment-class object as downloaded with download_study.
`length_var` | A length 1 character vector with the column name from `rowData(rse)` that has the coding length. For gene level objects from recount this is `bp_length`. If `NULL`, then it will use `width(rowRanges(rse))` which should be used for exon RSEs.
`mapped_var` | A length 1 character vector with the column name from `colData(rse)` that has the number of reads mapped. For recount RSE object this would be `mapped_read_count`. If `NULL` (default) then it will use the column sums of the counts matrix. The results are different because not all mapped reads are mapped to exonic segments of the genome.

### Details

For gene RSE objects, you will want to specify the `length_var` because otherwise you will be adjusting for the total gene length instead of the total exonic sequence length of the gene.

### Value

A matrix with the RPKM values.

### Author(s)

Andrew Jaffe, Leonardo Collado-Torres

### See Also

scale_counts

### Examples

    ## get RPKM matrix
    rpkm <- getRPKM(rse_gene_SRP009615)

    ## You can also get an RPKM matrix after running scale_counts()
    ## with similar RPKM values
    rpkm2 <- getRPKM(scale_counts(rse_gene_SRP009615))
    rpkm3 <- getRPKM(scale_counts(rse_gene_SRP009615, by = 'mapped_reads'))

    summary(rpkm - rpkm2)
    summary(rpkm - rpkm3)
    summary(rpkm2 - rpkm3)

[Package recount version 1.10.13 Index]