read_counts: Compute read counts
In recount: Explore and download data from the recount project

Description Usage Arguments Details Value Author(s) References See Also Examples

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.

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

`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.

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.

Returns a RangedSummarizedExperiment-class object with the read counts.

Leonardo Collado-Torres

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.

scale_counts

## 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