Tag: visualization

A practical guide to genome visualization tools for your own sequencing data, from IGV and the UCSC browser to igv.js, with the files each one needs.

A working guide to loading your own BAM/CRAM, VCF, and RNA-seq files into IGV and igv.js: reference builds, indexing, annotation tracks, batch screenshots, and the visual checks that catch bad variant calls.

A working guide to building the handful of plots that matter for a personal molecular dataset: coverage tracks, variant pileups, copy-number profiles, expression MA and volcano plots, and a genome-wide circular summary. With real commands, file formats, and the failure modes that produce misleading pictures.

A working pipeline from FASTQ to a publication-grade expression heatmap. Covers salmon quantification, gene selection, row scaling and clustering.

A step-by-step guide to turning transcript quantifications into plots that tell you something: sample-level QC, longitudinal gene trajectories, differential expression views, and pathway summaries, with the R and command-line code to produce them.

A step-by-step guide to producing a volcano plot from a count matrix with DESeq2 and ggplot2, choosing thresholds that mean something, and reading the resulting shape correctly, including the single-cell and mass-spectrometry variants.

A working guide to turning RNA-seq FASTQs into the handful of plots that matter: sample PCA, distance heatmaps, MA and volcano plots, and longitudinal gene trajectories, with the commands, parameters, and failure modes.

A practical guide to building violin plots from bulk and single-cell RNA-seq counts: which normalization to plot, how to set kernel bandwidth and trimming, and how to read the shapes without fooling yourself.