rnaseq-read-alignment
Skill4 starsChanged 12 days agoMITView on GitHub
Splice-aware alignment of RNA-seq reads to a reference genome using STAR or HISAT2.
In this repository56 other files it gives its agents.
- bioinformatics-env-setupSkill
- design-thermostable-mutationsSkill
- download-gdcSkill
- download-geoSkill
- download-sraSkill
- source-summarizerSkill
- genome-alignment-qcSkill
- genome-read-alignmentSkill
- genome-variant-annotationSkill
- genome-variant-callingSkill
- genome-variant-filteringSkill
- metagenome-assemblySkill
- metagenome-binningSkill
- metagenome-functional-profilingSkill
- metagenome-host-removalSkill
- metagenome-taxonomic-profilingSkill
- ncbi-eutilities-assistantSkill
- ngs-quality-controlSkill
- ngs-read-preprocessingSkill
- paper-to-briefSkill
- predict-protein-heat-stabilitySkill
- researchSkill
- rnaseq-alignment-qcSkill
- rnaseq-differential-expressionSkill
- rnaseq-functional-enrichmentSkill
- rnaseq-read-countingSkill
- rnaseq-transcript-quantificationSkill
- rpsblast-assistantSkill
- scrnaseq-cellranger-countSkill
- scrnaseq-cell-type-annotationSkill
- scrnaseq-clusteringSkill
- scrnaseq-differential-expressionSkill
- scrnaseq-integrationSkill
- scrnaseq-quality-controlSkill
- scrnaseq-trajectory-analysisSkill
- search-enaSkill
- search-geoSkill
- search-gsaSkill
- search-ncbi-datasetsSkill
- search-sraSkill
- stat-analyze-distributionSkill
- stat-assess-data-qualitySkill
- stat-bayesian-estimationSkill
- stat-cluster-samplesSkill
- stat-compare-multiple-groupsSkill
- stat-compare-two-groupsSkill
- stat-fit-glmSkill
- stat-fit-linear-modelSkill
- stat-learn-bayesian-networkSkill
- stat-logistic-regressionSkill
- stat-nonlinear-embeddingSkill
- stat-pairwise-correlationSkill
- stat-pcaSkill
- stat-survival-analysisSkill
- structured-intelligence-skill-creatorSkill
- <skill-id>Skill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 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.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 32
If STAR: run STAR with --quantMode GeneCounts (also produces per-gene counts) and --outSAMtype BAM SortedByCoordinate.
- Distinctive: line 33
If STAR two-pass: run first pass for junction discovery, generate a new genome index incorporating discovered junctions, then run the …
- Very specific: line 34
If HISAT2: run with --dta flag (downstream transcriptome assembly compatible), pipe output to samtools sort for coordinate-sorted BAM.
≈ “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 Read Alignment
Use When
- User needs splice-aware alignment for RNA-seq data
- User wants to produce genome-aligned BAMs for downstream counting
- User needs two-pass STAR alignment for novel junction discovery
- User wants to compare STAR vs HISAT2 aligners
Inputs
- Required:
- Trimmed FASTQ file(s) (single-end or paired-end)
- Reference genome index (STAR genome directory or HISAT2 index prefix)
- Optional:
- Aligner choice:
starorhisat2(default:star) - GTF annotation file (for STAR splice junction database)
- Reference FASTA path when running STAR in
--two-passmode (--genome-fasta) - Number of threads (default: 4)
- Output directory (default:
./alignment_output) - Two-pass mode for STAR (enables novel junction discovery)
- Maximum intron length
- Aligner choice:
Workflow
- Validate that the genome index exists for the chosen aligner.
- If STAR: run STAR with
--quantMode GeneCounts(also produces per-gene counts) and--outSAMtype BAM SortedByCoordinate. - If STAR two-pass: run first pass for junction discovery, generate a new genome index incorporating discovered junctions, then run the second pass.
- If HISAT2: run with
--dtaflag (downstream transcriptome assembly compatible), pipe output tosamtools sortfor coordinate-sorted BAM. - Index the output BAM with
samtools index. - Report alignment statistics: total reads, uniquely mapped reads, multi-mapped reads, unmapped reads, splice junctions detected.
Output Contract
- Sorted BAM file (
Aligned.sortedByCoord.out.bamfor STAR,aligned.sorted.bamfor HISAT2) - BAM index (
.bai) - Alignment log/summary (
Log.final.outfor STAR,hisat2_summary.txtfor HISAT2) - STAR gene counts file (
ReadsPerGene.out.tab, if STAR) - Splice junction file (
SJ.out.tabfor STAR)
Limits
- STAR requires approximately 32 GB RAM for the human genome; HISAT2 is lighter at approximately 8 GB.
- Genome index must be pre-built before running this skill.
- STAR two-pass mode is slower but recommended for novel junction discovery.
- STAR and HISAT2 must be installed and available on PATH.
- Common failure cases:
- STAR genome index built with an incompatible STAR version, causing segfault or load error.
- Insufficient RAM for STAR genome loading (32 GB for human; job killed by OOM).
- GTF annotation file missing or mismatched with the genome build, producing zero splice junctions.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

