Blog
Practical guides on bioinformatics analysis, pipeline best practices, and computational immunology.
April 2026
The Practical Guide to Dimensionality Reduction, Part 4: Which Method Do You Actually Use?
Part 4 of 4. Stop guessing. A practical decision framework for choosing between PCA, t-SNE, and UMAP based on what your analysis actually needs: exploration, communication, downstream quantification, or diagnosis.
March 2026
The Practical Guide to Dimensionality Reduction, Part 3: t-SNE and UMAP
Part 3 of 4. t-SNE and UMAP can find curved, branching structure that PCA misses entirely. But they're also the most misused plots in biology. A practical guide to what they do, what they don't, and the three mistakes to avoid.
March 2026
The Practical Guide to Dimensionality Reduction, Part 2: PCA
Part 2 of 4. PCA is the backbone of every scRNA-seq pipeline, but most people run it without understanding what it keeps, what it throws away, and why those decisions shape everything downstream. A practical guide for biologists.
March 2026
The Practical Guide to Dimensionality Reduction, Part 1: Why Your Data Has Too Many Dimensions
Part 1 of 4. Why high-dimensional biological data is fundamentally hard to work with, what the curse of dimensionality actually means in practice, and why every scRNA-seq and flow cytometry analysis already depends on dimensionality reduction.
March 2026
5 scRNA-seq Analysis Mistakes I See in Almost Every Lab (And How to Fix Them)
QC thresholds, batch effects, pseudoreplication, over-trusted annotation, and UMAP misinterpretation: the five mistakes that quietly degrade results, and how to fix them.