Bioinformatics for Next Generation Sequencing Quick Start Guide

Exploring Bioinformatics for Genomic and Transcriptomic Sequencing Data: A Quick Start Guide for WGS and RNA-Seq Analysis

Analyzing the massive amounts of data generated by next generation sequencing (NGS) experiments can be intimidating, especially for researchers who are new to bioinformatics. This Quick Start Guide provides a practical introduction to Illumina short read sequencing data analysis, walking through the fundamentals of whole genome sequencing (WGS) and RNA sequencing (RNA-Seq) workflows from raw FASTQ files to interpretable results.

Inside, you will find a step by step overview of common analysis stages including quality control, read trimming, alignment to a reference genome, variant calling for WGS, and gene expression and differential expression analysis for RNA-Seq. The guide also includes recommended hardware, software tools, and skills to help you build confidence and avoid common sources of bias or misinterpretation when working with genomic and transcriptomic datasets.

What You'll Learn

• The hardware, software, and foundational skills needed to run WGS and RNA-Seq bioinformatics analysis in a Linux environment, including scripting basics and compute considerations
• Step by step guidance for analyzing Illumina WGS data, including FastQC quality checks, Trimmomatic read trimming, BWA alignment, and introductory variant calling and annotation workflows/li>
• Step by step guidance for analyzing Illumina RNA-Seq data, including STAR alignment, FeatureCounts gene hit counting, and DESeq2 differential expression analysis
• A curated set of resources, workshops, and communities to support deeper exploration of genomic and transcriptomic sequencing data