read_counts {recount} | R Documentation

## Compute read counts

### Description

As described in the recount workflow, the counts provided by the recount2 project are base-pair counts. You can scale them using scale_counts or compute the read counts using the area under coverage information (AUC). We use the AUC because Rail-RNA soft clips some reads.

### Usage

    read_counts(rse, use_paired_end = TRUE, round = FALSE)

### Arguments

`rse` | A RangedSummarizedExperiment-class object as downloaded with download_study.
`use_paired_end` | A logical vector. When `TRUE` it uses the paired-end flag (`colData(rse)$paired_end`) to determine whether the sample is paired-end or not. If it's paired-end, then it divides the counts by 2 to return paired-end read counts instead of fragment counts. When `FALSE`, this information is ignored.
`round` | Whether to round the counts to integers or not.

### Details

Check the recount workflow for details about the counts provided by the recount2 project. Note that this function should not be used after scale_counts or it will return non-sensical results.

### Value

Returns a RangedSummarizedExperiment-class object with the read counts.

### Author(s)

Leonardo Collado-Torres

### References

Collado-Torres L, Nellore A and Jaffe AE. recount workflow: Accessing over 70,000 human RNA-seq samples with Bioconductor [version 1; referees: 1 approved, 2 approved with reservations]. F1000Research 2017, 6:1558 (doi: 10.12688/f1000research.12223.1)

### See Also

scale_counts

### Examples

    ## Difference between read counts and reads downloaded by Rail-RNA
    colSums(assays(read_counts(rse_gene_SRP009615))$counts) / 1e6 -
        colData(rse_gene_SRP009615)$reads_downloaded /1e6

    ## Paired-end read counts vs fragment counts (single-end counts)
    download_study('DRP000499')
    load('DRP000499/rse_gene.Rdata')
    colSums(assays(read_counts(rse_gene, use_paired_end = FALSE))$counts) /
        colSums(assays(read_counts(rse_gene))$counts)

    ## Difference between paired-end read counts vs paired-end reads downloaded
    colSums(assays(read_counts(rse_gene))$counts) / 1e6 -
        colData(rse_gene)$reads_downloaded / 1e6 /2

[Package recount version 1.6.3 Index]