Feature Counts

feature-counts

Quick Start

• Command: featureCounts
• Local executable: /home/vimalinx/miniforge3/envs/bio/bin/featureCounts
• Version: 2.1.1
• Full options: see references/help.md

When To Use This Tool

• Convert aligned RNA-seq BAM/SAM files into gene-level count matrices.
• Count reads at exon level with -f, or junction-supporting reads with -J.
• Handle stranded, paired-end, and multi-mapping policies explicitly.
• Prefer this after STAR or subjunc when you need a simple, transparent counting step.

Common Patterns

# 1) Standard gene-level counting for paired-end, reversely stranded RNA-seq
featureCounts \
  -a genes.gtf \
  -o counts.txt \
  -T 8 \
  -p --countReadPairs \
  -s 2 \
  sample.bam

# 2) Exon-level counting instead of gene-level summarization
featureCounts \
  -a genes.gtf \
  -o exon_counts.txt \
  -T 8 \
  -f \
  -t exon \
  -g gene_id \
  sample.bam

# 3) Count exon-exon junction support
featureCounts \
  -a genes.gtf \
  -G genome.fa \
  -o counts.txt \
  -J \
  sample.bam

Recommended Workflow

1. Start from coordinate-sorted BAM files aligned to the same assembly as the annotation.
2. Decide gene-level vs feature-level summarization and set -f, -t, and -g accordingly.
3. Set library-specific flags explicitly: -p, --countReadPairs, -s, -M, --fraction, -Q.
4. Review both counts.txt and counts.txt.summary before downstream DE analysis.

Guardrails

• Chromosome names must match between BAM and annotation; use -A alias mapping if they do not.
• For paired-end libraries, -p alone assumes paired reads, but --countReadPairs is what switches counting from reads to fragments.
• Strandness is easy to invert; verify whether the library is 0, 1, or 2 before counting the whole cohort.
• -M uses the NH tag to detect multi-mappers; do not enable it blindly if aligner tags are inconsistent.
• Annotation format defaults to GTF; specify -F SAF when using SAF input.