# nf-core/rnaseq

RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.

Repository: https://github.com/nf-core/rnaseq
Canonical: https://ross.abutalabs.com/products/rnaseq
Homepage: https://nf-co.re/rnaseq
Language: Nextflow
License: MIT
License Family: permissive
Topics: nf-core, nextflow, workflow, rna-seq, rna, pipeline
Last push: 2026-08-26T17:25:09+00:00

## Health v2 (maintenance only)
Score: 94/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 83, longevity 100
- inputs: {"age_days": 3079, "days_push": 7, "days_rel": 118, "gap_med": 15, "n_releases_24m": 16}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1357, forks 891 (observed 2026-08-28T04:04:29.429726+00:00)

## What it is
nf-core/rnaseq is a Nextflow-based bioinformatics pipeline for analyzing RNA sequencing data, performing QC, trimming, (pseudo-)alignment with STAR, HISAT2, or Salmon, and producing gene/isoform count matrices with extensive QC reporting. It runs with Docker, Singularity, or Conda and is part of the nf-core community pipeline collection.

## Use cases
- analyze RNA-seq FASTQ files and get gene counts
- run a reproducible RNA sequencing pipeline
- align RNA-seq reads with STAR or HISAT2
- quantify transcript expression with Salmon or RSEM
- generate MultiQC quality reports for RNA-seq data
- process bulk RNA-seq samples at scale on HPC or cloud
- reprocess BAM files to regenerate expression matrices

## When to choose
- you need a community-maintained, best-practice RNA-seq analysis workflow
- you want reproducible results with containerized software on HPC or cloud
- you need extensive QC reporting and multiple alignment/quantification options
- you have a reference genome and annotation for your organism

## When to avoid
- you lack a reference genome (de novo transcriptome assembly is out of scope)
- you need single-cell RNA-seq analysis (use nf-core/scrnaseq instead)
- you want a lightweight one-off alignment without a full pipeline
- you cannot install Nextflow or a container runtime

## Facets
- artifact type: application
- maturity: active
- function: workflow-automation, etl, data-science, analytics
- domain: bioinformatics
- platform: cloud, cli, self-hosted
- tags: nextflow, nf-core, rna-seq, bioinformatics-pipeline, star, salmon, hisat2, rsem, quality-control, multiqc, genomics, transcriptomics, fastq, alignment, gene-expression, data-engineering, automation, linux, macos, docker

## Member repositories
- nf-core/rnaseq (main) score 94

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:29.429726+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:41:50.745180+00:00, confidence not recorded.
  - readme: https://github.com/nf-core/rnaseq (fetched 2026-08-28T04:04:29.429726+00:00, sha 0ece4a9beb0c)
  - homepage: https://nf-co.re/rnaseq (fetched 2026-08-29T12:00:12.575229+00:00, sha d2d42b62a3d2)
  - site_page: https://nf-co.re/docs (fetched 2026-08-29T12:00:12.617983+00:00, sha 0fc2e71d95c3)
  - site_page: https://nf-co.re/about (fetched 2026-08-29T12:00:12.620460+00:00, sha ceb91d80a890)
  - site_page: https://nf-co.re/rnaseq/3.26.0/docs/usage (fetched 2026-08-29T12:00:12.622655+00:00, sha b2b9f66fb3ee)
  - site_page: https://nf-co.re/rnaseq/3.26.0/docs/output (fetched 2026-08-29T12:00:12.628232+00:00, sha 4ce6b6428604)
  - site_page: https://nf-co.re/docs/get_started/environment_setup/overview (fetched 2026-08-29T12:00:12.639357+00:00, sha c79ed61f7063)
  - site_page: https://nf-co.re/docs/get_started/run-your-first-pipeline (fetched 2026-08-29T12:00:12.641201+00:00, sha 801ad7ddc99b)
  - site_page: https://nf-co.re/rnaseq/releases_stats (fetched 2026-08-29T12:00:12.633258+00:00, sha 62381308d7a6)
- Data as of 2026-08-30T08:39:29.467469+00:00.