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Ultra-fast RNA-seq transcript/gene quantification via quasi-mapping (no BAM). Builds a k-mer index from transcriptome FASTA, quantifies in minutes. Outputs TPM/count tables (quant.sf) with optional GC- and sequence-bias correction. Integrates with tximeta/tximport for DESeq2/edgeR. Use STAR when a genome-aligned BAM is needed.
Passed 0 of 21 test cases with the skill, and 21 of 21 without it.
2 fixed19 passed either way0 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
A test case the skill fixed. Same model, same prompt, with and without the skill.
I have created `gentrome.fa` and `decoys.txt`. I want to run `salmon index` to generate a decoy-aware index folder at `salmon_decoy_index/`. What exact command parameters pass the concatenated sequence file, the decoy list file, and the output index directory?
| Checked | Without skill | With skill |
|---|---|---|
| Pass `gentrome.fa` as the transcripts input parameter via `-t`. | Passed | Passed |
| Pass `decoys.txt` as the decoy list parameter via `-d`. | Passed | Passed |
| Pass `salmon_decoy_index/` as the index output path via `-i`. | Missed | Passed |
The instructions your model reads when the skill loads.
Salmon quantifies transcript abundance from RNA-seq reads using quasi-mapping — matching reads to a k-mer index of the transcriptome without full genome alignment. This makes Salmon 20–50× faster than alignment-based tools while producing accurate TPM and estimated count values. Salmon corrects for sequence-specific bias (--seqBias), GC-content bias (--gcBias), and fragment length distribution automatically. Output quant.sf files integrate directly with tximeta (R) or pydeseq2 (Python) for differential expression analysis. For improved accuracy, decoy-aware indexing uses the full genome to identify spurious quasi-mappings.
--gcBias --seqBias--numBootstrapspandas for parsing output; pydeseq2 for differential expressionCheck before installing: The tool may already be available in the current environment (e.g., inside a
pixi/condaenv). Runcommand -v salmonfirst and skip the install commands below if it returns a path. When running inside a pixi project, invoke the tool viapixi run salmonrather than baresalmon.
# Install with conda (recommended)
conda install -c bioconda salmon
# Verify
salmon --version
# salmon 1.10.3
# Or download pre-compiled binary
wget https://github.com/COMBINE-lab/salmon/releases/download/v1.10.0/salmon-1.10.0_linux_x86_64.tar.gz
tar xzvf salmon-1.10.0_linux_x86_64.tar.gz
export PATH="$PWD/salmon-latest_linux_x86_64/bin:$PATH"
test cases passed, vs 21 / 21 without
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