Skill: RNA-seq Transcript Quantification

Use When

User wants fast transcript-level quantification without genome alignment
User wants TPM and count estimates per transcript
User needs input for downstream differential expression analysis (tximport/tximeta in R)
User wants to compare Salmon vs kallisto quantification

Required:
- Trimmed FASTQ file(s) (single-end or paired-end)
- Transcriptome index (Salmon index directory or kallisto index file)
Optional:
- Tool choice: salmon or kallisto (default: salmon)
- Library type for Salmon (default: A for auto-detect)
- Number of threads (default: 4)
- Output directory (default: ./quant_output)
- Number of bootstrap samples (for downstream use with sleuth)

Validate that the transcriptome index exists for the chosen tool.
If Salmon: run salmon quant with --validateMappings, --seqBias, and --gcBias for bias correction.
If kallisto: run kallisto quant.
If bootstraps are requested: add --numBootstraps (Salmon) or -b (kallisto).
Report: total reads processed, mapping rate, number of quantified transcripts.

Quantification file:
- Salmon: quant.sf with columns: Name, Length, EffectiveLength, TPM, NumReads
- kallisto: abundance.tsv with columns: target_id, length, eff_length, est_counts, tpm
Log file with mapping statistics
Auxiliary files (Salmon aux_info/ directory or kallisto run_info.json)

Salmon and kallisto must be installed and available on PATH.
Transcriptome index must be pre-built before running this skill.
Quantification is at the transcript level; use tximport in R to summarize to gene level for DE analysis.
Not suitable for novel transcript or isoform discovery.
For single-end reads with kallisto, fragment length and standard deviation must be provided.
Common failure cases:
- Transcriptome index built from a different annotation version than expected, skewing quantification.
- Salmon library type auto-detection failing on very low-read-count samples.
- kallisto single-end mode missing required --fragment-length and --sd parameters.