Automating RNA-Seq Downstream Analysis with DESeq2 and ClusterProfiler

In the realm of transcriptomics, RNA-Seq has become a powerful tool for understanding gene expression patterns. However, the journey from raw data to meaningful biological insights involves several intricate steps of data processing and analysis. In this tutorial, we will walk through a comprehensive RNA-Seq downstream analysis workflow using DESeq2 and ClusterProfiler, split into distinct stages for clarity and automation.

A Comprehensive RNA-Seq Upstream Pipeline in Bash with FastQC, MultiQC, Trimmomatic, HISAT2, SAMtools, and FeatureCounts

With the advent of next-generation sequencing technology, biological data proliferation has soared dramatically. This surge encompasses data generated across various biological scales. This tutorial specifically targets the transcriptomic scale, which encompasses diverse RNA molecules and encapsulates the intricate control mechanisms of gene expression.

NGS Data Trimming and Filtering with Trimmomatic

Trimmomatic serves as a versatile preprocessing tool tailored for the trimming and filtering needs of Illumina next-generation sequencing (NGS) data. It excels in handling paired-end data accurately and efficiently, standing out for its adaptability and performance across various scenarios. Developed by Anthony M. Bolger, Marc Lohse, and Bjoern Usadel, Trimmomatic emerged to meet the demand for a tool that offers flexibility, precise handling of paired-end data, and robust performance.

Quality Control with MultiQC

MultiQC streamlines the consolidation of bioinformatics analysis results across multiple samples into a unified, detailed report. This tool proves invaluable for researchers and bioinformaticians handling substantial data volumes from high-throughput sequencing experiments. By automating the aggregation and summarization of data, MultiQC eliminates the laborious and error-prone manual tasks associated with this process.