Bulk RNA-seq Pipeline (rnaseq-pipeline)

An interactive, terminal-based pipeline for bulk RNA-seq: from public accessions (SRA, GEO, ENA) or local FASTQ files to differential-expression results, plots and an HTML report.

• Python does everything up to the gene count matrix: download/import, FASTQ validation, FastQC/MultiQC, the quality gate, fastp, reference preparation, HISAT2, BAM validation and QC, strandedness, StringTie2 and featureCounts.
• R runs DESeq2 and everything after it: normalisation, tests, up/down genes, and plots.
• Every stage validates its outputs independently (for example, FASTQ reads = HISAT2 reads = BAM primary records; count-matrix column sums = featureCounts assigned reads; up/down tables re-derived from the full result table).
• Checkpoints make interrupted runs resumable. A changed input, output or scientific setting re-runs exactly the affected stages.
• Scientific decisions (trimming, strandedness, experimental design) are never guessed; you confirm each one, with an explanation.

New to RNA-seq or to this tool? Read the illustrated User Guide and Learning Book (PDF · Word): installation step by step, every stage and tool explained in plain language with flowcharts, how to read the results and plots, a worked example, troubleshooting, a glossary and how to cite. No programming knowledge needed.

DATA (SRA / GEO / ENA / local, or search NCBI) -> FASTQ validation -> FastQC + MultiQC -> quality gate
  -> [fastp -> validation -> FastQC + MultiQC]  (only if you decide to trim)
  -> reference (catalog, any organism from NCBI, or your own FASTA + GTF; validated; HISAT2 index)
  -> HISAT2 | samtools sort -> BAM validation -> BAM QC -> strandedness (inferred, confirmed)
  -> StringTie2 (transcript TPM)   and   featureCounts (gene counts)      <- independent
  -> count matrix -> experimental design (you confirm) -> DESeq2 -> plots -> validated HTML report + manifest

Install

pipx install git+https://github.com/vipin839/rnaseq_pipeline.git         # the command
mamba env create -f "$(rnaseq-pipeline --runtime-env tools)"               # FastQC, HISAT2, samtools, ...
mamba env create -f "$(rnaseq-pipeline --runtime-env r)"                   # R + DESeq2
rnaseq-pipeline --check                                                    # functional health check

See docs/INSTALLATION.md for conda setup, the Bioconda recipe (one-command install after it is published), user settings and upgrading from 1.0.0.

Use

rnaseq-pipeline                              # interactive menu
rnaseq-pipeline --project ~/rnaseq_projects/RNAseq_MyStudy   # resume a project
rnaseq-pipeline --validate-project DIR       # re-verify a project: PROJECT HEALTH PASS / WARNING / FAIL
rnaseq-pipeline --dry-run --project DIR      # show what would run, execute nothing
rnaseq-pipeline --check                      # installation health check

What is supported

Documentation

How to cite

Vipin (2026). rnaseq-pipeline: an interactive, validated and resumable bulk RNA-seq pipeline (version 1.1.2) [Computer software]. GitHub. https://github.com/vipin839/rnaseq_pipeline

Please also cite the tools the pipeline runs (FastQC, MultiQC, fastp, HISAT2, SAMtools, RSeQC, StringTie2, featureCounts, DESeq2, apeglm). Full references and an example methods paragraph are in chapter 22 of the User Guide.

Developer and contact

Developed and maintained by Vipin (github.com/vipin839).

• Website: www.vipin.social
• E-mail: sainivipin839@gmail.com
• Questions and bug reports: GitHub issues

License: MIT.