Learn RNA-Seq Analysis with TransXplorer
Free tutorials and concept guides for biologists — from your first DE analysis to advanced network methods. No coding required.
Analyze Your First RNA-Seq Dataset in 10 Minutes
A guided, click-by-click walkthrough using the cardiac differentiation example dataset (GSE151427). You'll load real counts, detect batch effects, run edgeR, interpret a volcano plot, and export publication-ready figures — all in your browser, with zero setup.
Start TutorialWhat's in the Learn section?
Tutorials walk you through a workflow step by step. Concept guides explain a method in depth so you actually understand what's happening.
Getting Started
Analyze Your First RNA-Seq Dataset in 10 Minutes
Step-by-step intro using the cardiac differentiation example dataset. Load counts, run DESeq2, interpret a volcano plot, and discover pathways.
Working with Your Own Data
Format your count matrix and sample metadata, upload to TransXplorer, and avoid the most common pitfalls when bringing your own data.
Concept Guides
Understanding Batch Effects in RNA-Seq
What they are, how to detect them with PVCA / kBET / Silhouette, and how to correct with ComBat-seq without removing your biology.
What is Differential Expression Analysis?
DESeq2, edgeR, and limma compared. How to interpret padj, log2FC, and FDR — what they actually mean.
GSEA vs ORA: Pathway Enrichment Explained
Two ways to turn a gene list into biology. When to use each, with worked examples on the same dataset to show why they sometimes disagree.
WGCNA: A Visual Guide to Co-expression Networks
Modules, hub genes, and soft thresholding made intuitive. Walk through a real dataset to see how modules connect to phenotype traits.
Tutorials & Case Studies
From GEO Accession to Results
Import any GEO study by accession ID and run a full analysis in 15 minutes — no manual downloading or reformatting.
Working with TCGA Cancer Data
Survival analysis and biomarker discovery using TCGA pan-cancer cohorts — from cohort definition to Kaplan-Meier curves.
Your First FASTQ to Results Workflow
Process raw sequencing data with HISAT2 or Salmon, then carry counts straight into the standard TransXplorer workflow.
Why we built the Learn section
Most bioinformatics tutorials assume you already know how to code. TransXplorer's Learn section takes the opposite approach: every concept is explained in plain language, with the point-and-click workflow visible at every step.
Whether you're a first-year grad student running your first DE analysis, or a wet-lab biologist trying to understand what your bioinformatician did, this is the section for you. We focus on what the numbers actually mean, why a method works, and when to use it — not on memorising syntax.
About TransXplorer
TransXplorer is a free, browser-based RNA-seq analysis platform built by Verma, Oler, Syed, Han, Berjanskii, Mason, Wishart, and Wong. It runs DESeq2, edgeR, limma, WGCNA, pathway enrichment, PPI networks, and more — with no installation, no login, and no R required.
If you use TransXplorer in your work, please cite the preprint: