FeatureCounts

Use of FeatureCounts tool on PRJNA630433 datasets

Before using FeatureCounts ensure that you have ready:

• A bam dataset, or a collection of bam file.
• A GTF file corresponding to your reference genome
• The knowledge of you library design (strandness, single or paired-ends and orientation of reads)

and

• Copy the appropriate datasets (or collections) in a new history which you will name PRJNA630433 FeatureCounts Counting on HISAT2 bam alignments In the PRJNA630433 use case, this corresponds to 3 collections (Dc, Mo and Oc HISAT2 alignments), as well as the GTF Mus_musculus.GRCm38.102.chr.gtf, all present in your history HISAT alignments

FeatureCounts settings

• Alignment file

  → Click on the collection icon and select Dc HISAT2 alignments (BAM)

• Specify strand information

  → Standed (Reverse)

• Gene annotation file → A GFF/GTF file in your history

  → Mus_musculus.GRCm38.102.chr.gtf

• GFF feature type filter

  → exon - GFF gene identifier

  → gene_id_

• On feature level

  → No (keep default). If you select "yes", the counting will be done at the exon level, since your GFF feature type filter is exon

• Output format *

  → Gene-ID "\t" read-count (MultiQC/DESeq2/edgeR/limma-voom compatible)

• Create gene-length file

  → Yes

• Does the input have read pairs?

  → No, single-end

• Advanced options

  → Leave folded, no advanced options !

• Run Tool

Repeat the exact same operation twice for the collections Mo and Oc HISAT2 alignments

use the rerun functionality !

MultiQC

The MultiQC tool can use to nicely summarise the FeatureCounts countings

MultiQC settings

• 1: Results/ Which tool was used generate logs?

  → FeatureCounts

• 1: Results/ Output of FeatureCounts

  → Click on the collection icon, then select the three collections generated by featureCounts and suffixed with : Summary

• click Execute(or Run Tool in the latest Galaxy version)

examine the results by clicking the eye icon of the generated collection MultiQC... ...others:Webpage

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