pegi3s/feature-counts repository overview

⁠This image belongs to a larger project called Bioinformatics Docker Images Project (http://pegi3s.github.io/dockerfiles⁠)

⁠(Please note that the original software licenses still apply)

This image facilitates the usage of featureCounts⁠, a general-purpose read summarization function.

To see the featureCounts⁠ help, just run docker run --rm pegi3s/feature-counts featureCounts -h.

⁠Using the featureCounts image in Linux

You should adapt and run the following command: docker run --rm -v /your/data/dir:/data pegi3s/feature-counts featureCounts -a /data/file.gff -o /output/output.txt /data/input.bam

In this command, you should replace:

• /your/data/dir to point to the directory that contains the input file you want to process.
• file.gff to the actual name of your annotation file in gff format.
• output.txt to the actual name of your output file.
• input.bam to the actual name of your alignment file in bam format.

⁠Test data

To test the previous command, you can download the following files:

• annotation file⁠ (12MB)
• bam file⁠ (292MB).

The test BAM file contains paired-end reads, so the -p option is required, and -g locus_tag matches the gene identifier used in the annotation file. After replacing /your/data/dir by the actual working directory, run:

docker run --rm -v /your/data/dir:/data pegi3s/feature-counts featureCounts -p -a /data/saccharomyces.gff -g locus_tag -o /data/saccharomyces_output.txt /data/saccharomyces_data.sorted.bam

⁠Using the featureCounts image in Windows

Please note that data must be under the same drive than the Docker Toolbox installation (usually C:) and in a folder with write permissions (e.g. C:/Users/User_name/).

You should adapt and run the following command: docker run --rm -v "/c/Users/User_name/dir/":/data pegi3s/feature-counts featureCounts -a /data/file.gff -o /output/output.txt /data/input.bam