This task provides a convenience wrapper around RSEM. It computes gene and isoform quantifications given a BAM file of reads mapped to a transcriptome.
We encourage running this task as a Docker image, which is publicly available through GitHub packages. To pull the image, first install Docker, then run
docker pull docker.pkg.github.com/krews-community/rnaseq-rsem-task/rnaseq-rsem:latest
The task requires a pre-built RSEM index to be provided as a tarball. The RSEM indexes available at ENCODE (for example ENCFF940ABZ) are compatible with this task. Alternatively, you can package a RSEM index you have built into a compatible tarball by running
tar -cf index.tar -C /path/to/directory/with/index/files .
Then, to perform quantifications, simply run:
docker run \
--volume /path/to/inputs:/input \
--volume /path/to/outputs:/output \
docker.pkg.github.com/krews-community/rnaseq-rsem-task/rnaseq-rsem:latest \
java -jar /app/rsem.jar --bam /input/alignments.bam \
--index /input/index.tar --output-directory /output
If your data are paired-end, run the above command with --paired-end added.
This will produce an output directory containing gene quantifications (output.genes.results) and isoform quantifications (output.isoforms.results).
This task supports several parameters:
| name | description | default |
|---|---|---|
| bam | BAM file containing alignments to a transcriptome | (required) |
| index | path to index tarball; may be gzipped or not | (required) |
| output-directory | directory in which to write output | (required) |
| paired-end | must be specified if reads are paired-end | false |
| strand | set if reads are from one strand; forward, reverse, or unstranded | unstranded |
| seed | random seed to use | (random) |
| output-prefix | prefix to use when naming output files | output |
| cores | number of cores available to the task | 1 |
| ram-gb | gigabytes of RAM available to the task | 16 |
The task provides integrated unit testing, which quantifies a small number of reads aligned to a human mitochondrial index and checks that the outputs match expected values. To run the tests, first install Docker and Java, then clone this repo, then run
scripts/test.sh
Contributions to the code are welcome via pull request.