Command-line Based Practical RNA-Seq Data Analysis With Linux & R

The complete RNA-Seq pipeline, on the command line with R

This is the Linux and R route through RNA-Seq, covering about 7 hours across six sections. It is the version most closely matching how a bioinformatics core facility actually runs the analysis, and it assumes no prior knowledge of Linux, R or RNA-Seq — all three are taught as you go.

What you work through

• RNA-Seq and NGS in depth — what the sequencer measures, and what that permits you to claim.
• Genomic databases — finding and retrieving raw public data.
• File formats — FASTQ, SAM/BAM, GTF and count matrices, and how each stage transforms one to the next.
• Linux for RNA-Seq — the command-line skills the pipeline needs, taught against real sequencing files.
• Quality control and trimming — reading QC reports and deciding what to remove.
• Mapping and alignment evaluation — aligning reads and judging the result.
• Differential expression — with DESeq2, edgeR and Ballgown, including where the three disagree and why.
• Functional analysis — Gene Ontology and KEGG enrichment to turn a gene list into biology.

Why three differential expression tools

DESeq2, edgeR and Ballgown make different statistical assumptions, and on the same dataset they will not return identical gene lists. Knowing why — how each models dispersion, how each handles low counts — is what lets you choose defensibly and answer the reviewer who asks. Most courses teach one tool; this one teaches the comparison.

What you can do afterwards

Take raw RNA-Seq data through the full pipeline on the command line: QC, trimming, alignment, quantification, differential expression in R, and pathway enrichment — producing figures and a defensible interpretation.

Python and Galaxy versions of this same analysis are also available if you prefer either route. We also run RNA-Seq analysis directly as an RNA-Seq analysis service.

Who it suits

Biologists with RNA-Seq data and no computational background, and bioinformatics students who want the command-line pipeline rather than a point-and-click one. No prior Linux, R or RNA-Seq experience is required.