What is 001_rnaseq_downstream_pipeline?

This repository is a step by step recipe, written in the R programming language, for analyzing RNA sequencing data after the raw counting has already been done. RNA sequencing is a lab method that measures which genes are active in a cell or tissue sample. This project takes that starting data and walks through the process of figuring out which genes changed, and what those changes might mean biologically. The pipeline runs through seven stages in order: quality control checks, finding differentially expressed genes (genes that turned on or off between two conditions), converting gene ID formats so different databases can talk to each other, and then three kinds of enrichment analysis that group genes into known biological pathways to look for patterns. Each stage lives in its own folder with its own scripts and its own README explaining that step. To make the example realistic without using anyone's private data, the project uses a public, published dataset from a 2014 scientific paper. That dataset compares airway muscle cells that were treated with a steroid drug against cells that were not treated, and the pipeline demonstrates how to find which genes and pathways the drug affects. Running it requires installing R and a handful of specific R packages, then running a setup script to prepare the starting files, then running each stage's scripts in order since later steps depend on the output of earlier ones. The scripts currently point to a specific folder path on the original author's computer, so a new user needs to edit that path before running anything. This is best suited for people who already work with RNA sequencing data and know some R, such as biology researchers or bioinformatics students, rather than complete beginners to coding or to genomics.