Genomics tips

Rank transcription factors by evidence, not only by enrichment

A practical way to prioritize transcription factors by combining motif enrichment, expression, chromatin accessibility, timing and network position.

Make enhancer analyses gene-aware, but not gene-blind

A practical framework for integrating enhancer states, chromatin signal and gene expression without pretending that nearest gene assignment solves everything.

ATAC-seq is more than a peak list

How to get more biological information from ATAC-seq by looking at fragments, nucleosomes, TSS profiles, footprints and genomic signal.

Use pseudoreplicates to make peak sets less fragile

A generic strategy for using pseudoreplicates and IDR-like thinking to build more robust ChIP-seq and ATAC-seq peak sets.

A QC checklist before trusting ChIP-seq or ATAC-seq peaks

A compact checklist for deciding whether ChIP-seq or ATAC-seq peak calls are biologically interpretable.

Think in trajectories, not only in contrasts

A reusable strategy for extracting dynamic programs from time-course transcriptomic data with splines, clustering and module-level interpretation.