Harshini Suresha

RNA-Seq Data Analysis and Transcriptomics Workflow

Differential Expression Analysis

Year2025
LocationPES University
TagsGalaxy, Cutadapt, STAR, MultiQC

An end-to-end paired-end RNA-seq workflow on Galaxy: Cutadapt trimming, STAR alignment to DM6, MultiQC, FeatureCounts, DESeq2 / edgeR differential expression and IGV inspection.

Oct 2024 – Jan 2025 at PES University, Bangalore.

Workflow figureOpen full size ↗
Figure for RNA-Seq Data Analysis and Transcriptomics Workflow: Differential Expression Analysis
Methods
  1. 01
    Pre-processing

    Adapter trimming of paired-end RNA-seq reads on the Galaxy platform.

    Galaxy, Cutadapt
  2. 02
    Alignment

    Splice-aware alignment to the DM6 (Drosophila) genome using GTF annotations.

    STAR, DM6 genome
  3. 03
    Quality control

    Read quality, mapping efficiency, uniquely mapped reads, splice junctions and coverage across samples.

    MultiQC
  4. 04
    Quantification

    Gene-level counts with strandedness checks and tuned counting parameters.

    FeatureCounts
  5. 05
    Differential expression

    Count matrices into differential expression to find condition-specific signatures.

    DESeq2, edgeR
  6. 06
    Visual checks

    Inspected BAM files for coverage, exon alignment, splice junctions and transcript structure.

    IGV, BAM files
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