Welcome to the NotchBio Blog
We’re excited to launch the NotchBio blog! This is where we’ll share insights on RNA-seq analysis, bioinformatics best practices, platform updates, and tutorials to help you get the most out of your research data. If you are starting from scratch, begin with What Actually Happens to Your RNA Sample Before It Becomes Data and Raw Reads to Counts: The Bulk RNA-Seq Pipeline Explained.
What to Expect
Our blog will cover a range of topics designed to help both new and experienced researchers:
- Platform updates — New features, improvements, and what’s coming next
- RNA-seq tutorials — Step-by-step guides for common analysis workflows
- Bioinformatics insights — Tips, best practices, and deep dives into methods
- Research highlights — How teams are using NotchBio in their work
Our Mission
NotchBio was built to make bulk RNA-seq analysis accessible, reproducible, and fast. We believe researchers should spend their time on science — not wrestling with command-line tools, dependency issues, or infrastructure management.
What Makes NotchBio Different
Our platform handles the entire RNA-seq pipeline in the cloud:
- Quality Control — Automated QC reports for your raw FASTQ files
- Preprocessing — fastp-powered trimming with configurable parameters
- Quantification — Salmon for fast, accurate transcript quantification
- Differential Expression — DESeq2 with interactive volcano plots and heatmaps
- Gene Set Enrichment — GSEA to identify enriched biological pathways
Everything is versioned, reproducible, and shareable with your team.
Start Here
A few strong entry points if you want the most useful posts first:
- How to Run FastQC and MultiQC on Raw RNA-Seq Reads for practical QC workflows
- Experimental Design Mistakes That Kill Your Differential Expression Analysis for study design risks
- Batch Effects Will Ruin Your RNA-Seq Results for troubleshooting technical variation
- What Is a Count Matrix and Why Does It Matter for the downstream data object that drives DE analysis
We’re looking forward to building this resource with you. If there’s a topic you’d like us to cover, don’t hesitate to reach out.
Happy analyzing! — The NotchBio Team
Further reading
Read another related post
Batch Effects Will Ruin Your RNA-Seq Results
Batch effects silently corrupt bulk RNA-seq data. Learn how to detect them, why they happen, and which correction methods actually work.
BioinformaticsWhat FastQC Reports Actually Tell You (And What Beginners Miss)
A senior bioinformatician walks through the FastQC sections that real beginners miss, with screenshots and decisions to make at each step.
Research GuideFrom Wet Lab to Dry Lab: A Realistic Map of What to Learn First
A practical skill sequence for wet-lab biologists learning RNA-seq analysis: what to prioritise, what to safely skip, and what to outsource while you build.