# griffithlab/rnaseq_tutorial

Informatics for RNA-seq: A web resource for analysis on the cloud. Educational tutorials and working pipelines for RNA-seq analysis including an introduction to: cloud computing, critical file formats, reference genomes, gene annotation, expression, differential expression, alternative splicing, data visualization, and interpretation.

Repository: https://github.com/griffithlab/rnaseq_tutorial
Canonical: https://ross.abutalabs.com/products/rnaseq_tutorial
Language: R
License: NOASSERTION
License Family: other
Last push: 2023-05-31T18:45:10+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4416, "days_push": 1190, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1435, forks 613 (observed 2026-08-28T04:04:43.404506+00:00)

## What it is
An educational web resource and working pipeline for RNA-seq analysis on the cloud, covering file formats, reference genomes, expression and differential expression analysis, splicing, and visualization. This repository hosts code and materials for the tutorial, which is maintained for consistency with the published 2015 paper while the current version lives at rnabio.org.

## Use cases
- learn RNA-seq analysis from scratch
- run an RNA-seq pipeline on AWS
- learn cloud computing for bioinformatics
- understand differential expression analysis
- learn alternative splicing analysis
- teach a genomics bioinformatics course
- review RNA-seq file formats and gene annotation

## When to choose
- you want a structured, citable RNA-seq tutorial with a working cloud pipeline
- you need course materials for teaching RNA-seq informatics
- you want to learn Unix and AWS basics alongside RNA-seq analysis

## When to avoid
- you need the up-to-date version of the course (use rnabio.org instead)
- you need production-ready RNA-seq software rather than educational materials
- you need a maintained tool with active development

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, data-visualization, etl
- domain: bioinformatics, education, tutorials, cloud-computing
- platform: cloud, cli
- tags: rna-seq, bioinformatics, genomics, tutorial, aws, differential-expression, r, linux

## Member repositories
- griffithlab/rnaseq_tutorial (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:43.404506+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 2026-08-30T04:36:51.509849+00:00, confidence not recorded.
  - readme: https://github.com/griffithlab/rnaseq_tutorial (fetched 2026-08-28T04:04:43.404506+00:00, sha fb97bb45e0fd)
- Data as of 2026-08-30T08:39:29.467469+00:00.