rnaseq-alignment-qc
Skill4 starsChanged 12 days agoMITView on GitHub
RNA-seq-specific alignment quality assessment using RSeQC and Qualimap for gene body coverage, strandedness, and rRNA contamination.
In this repository56 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
6 rules. About 0 are common, 1 is distinctive, and 5 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 28
Run RSeQC infer_experiment.py to determine library strandedness.
- Very specific: line 29
Run RSeQC geneBody_coverage.py for 5'-to-3' coverage profile across gene bodies.
- Very specific: line 30
Run RSeQC read_distribution.py for read distribution across genomic features (CDS, UTR, intron, intergenic).
- Very specific: line 31
Run RSeQC inner_distance.py for insert size distribution (paired-end data).
- Very specific: line 32
Run Qualimap rnaseq for comprehensive RNA-seq QC metrics.
- Distinctive: line 41
Read distribution table (text)
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Skill: RNA-seq Alignment QC
Use When
- User wants to assess RNA-seq alignment quality beyond basic mapping stats
- User needs to check strandedness of a library
- User wants to evaluate gene body coverage (5'-to-3' bias)
- User wants to measure rRNA contamination rate
- User needs to verify read distribution across genomic features (CDS, UTR, intron, intergenic)
Inputs
- Required:
- BAM file with index (
.bam+.bai)
- BAM file with index (
- Optional:
- BED file of gene models (for RSeQC; available from UCSC or RSeQC downloads)
- GTF annotation file (for Qualimap)
- Output directory (default:
./alignment_qc_output) - Species/genome build for rRNA intervals
Workflow
- Run RSeQC
infer_experiment.pyto determine library strandedness. - Run RSeQC
geneBody_coverage.pyfor 5'-to-3' coverage profile across gene bodies. - Run RSeQC
read_distribution.pyfor read distribution across genomic features (CDS, UTR, intron, intergenic). - Run RSeQC
inner_distance.pyfor insert size distribution (paired-end data). - Run Qualimap
rnaseqfor comprehensive RNA-seq QC metrics. - Calculate rRNA rate from Qualimap output or custom rRNA interval overlap.
- Compile summary: strandedness, gene body coverage shape, rRNA rate, feature distribution, junction saturation.
- Flag metrics that fall outside recommended thresholds.
Output Contract
- RSeQC strandedness report (text)
- Gene body coverage plot (PDF)
- Read distribution table (text)
- Inner distance plot (PDF, paired-end only)
- Qualimap HTML report
- Compiled QC summary (text)
Limits
- RSeQC and Qualimap must be installed and available on PATH.
- BED gene model file is required for most RSeQC modules (downloadable from UCSC or RSeQC site).
- Qualimap requires Java to be installed.
- Qualimap memory scales with BAM size (approximately 2-4 GB for human genome BAMs).
- Common failure cases: missing BED file, BAM without index, Java not available for Qualimap.
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