bulk-rnaseq

A bulk RNA-seq analysis pipeline automates quality control, alignment, quantification, differential expression, and pathway enrichment. This Skill orchestrates the entire workflow from raw reads to publication figures, reducing manual errors in large-scale studies.

Comprehensive differential expression and pathway enrichment require STAR, Salmon, featureCounts, pydeseq2, and pathway-enrichment. These dependencies provide robust alignment, quantification, and statistical analysis for bulk RNA-seq data.

Yes, this bulk RNA-seq pipeline uses both STAR and Salmon for alignment and quantification. It integrates these tools with featureCounts to provide robust read mapping and transcript counting for downstream analysis.

To identify differentially expressed genes in large-scale RNA-seq studies, this pipeline applies pydeseq2 after alignment and quantification. It provides a robust analysis framework with built-in quality control and reproducibility.

Yes, this RNA-seq pipeline integrates quality control steps like FastQC and trimming. These integrated steps ensure data integrity by processing raw reads before proceeding to alignment and quantification.