Introduction and Workflow

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Introduction to RNA-seq

RNA-seq measures the transcript landscape of a sample by sequencing RNA-derived libraries. It is used to study gene expression, discover transcripts, compare biological conditions, and support downstream functional interpretation. The method is widely used because it scales well and provides high-resolution expression information.

Experimental workflow summary

• RNA is extracted from the biological sample.
• Library preparation converts RNA into sequence-ready fragments.
• The sequencer generates raw reads, typically FASTQ files.
• These reads enter the computational workflow for QC, preprocessing, alignment, and quantification.

Types of RNA-seq

• Bulk RNA-seq for average expression across a sample
• Single-cell RNA-seq for cell-level expression patterns
• Strand-specific workflows for transcript orientation clarity
• Paired-end and single-end designs depending on experimental goals

Computational workflow

The computational path usually includes quality assessment of raw reads, trimming or adapter removal when needed, preparation of the reference genome and annotation, alignment or pseudoalignment, BAM processing, and quantification. For the current tutorial series, Part 2 takes this workflow from FASTQ files through gene-level counting.

Short notes