Wrap Up

Last updated on 2026-09-03 | Edit this page

Estimated time: 10 minutes

Overview

Questions

  • What have I learned, and where can I go next with IGV?

Objectives

  • Summarize the IGV skills covered in this lesson.
  • Identify further IGV features and resources to explore independently.

What we covered

Across this lesson you have:

  • loaded reference genomes both from IGV’s hosted server and from your own local FASTA file,
  • navigated between whole-genome, chromosome, region, and base-pair resolution views,
  • combined two numeric tracks with a simple arithmetic operation,
  • inspected aligned sequencing reads and used sorting, coloring, and BLAT to distinguish a likely real SNP from a likely artifact,
  • precomputed coverage data with igvtools so it remains visible at every zoom level,
  • explored RNA-seq coverage, splice junctions, and Sashimi plots to identify alternative splicing between tissues, and
  • explored population variant data from a VCF file, including grouping genotypes by sample attributes, and
  • used paired-end insert size and pair orientation to confirm a structural variant (an inversion) by eye, and
  • if you covered the optional episode, filtered raw long-read errors and used mapping quality, split reads, and haplotype tags to interpret PacBio and Nanopore data.

These are the same core skills — load data, navigate, and use track-specific display options to interrogate a signal — that apply to almost any data type IGV can display.

Where to go next

  • Dedicated SV callers. The previous episode showed you the raw evidence by eye at one locus; tools like Delly, Manta, and Lumpy automate the same search genome-wide and output a VCF you can load and view exactly as you did in Viewing Variants and Genotypes.
  • igv.js and IGV-Web. If you want to embed genome browser views in a web page or share a specific view with collaborators without asking them to install anything, look at igv.js and IGV-Web, which share much of the same track and navigation model as the desktop application you used here.
  • Batch scripting. IGV supports batch scripts (Tools > Run Batch Script…) for automating repetitive tasks, such as generating snapshot images across many loci — useful if you find yourself repeating the same manual steps for many regions or samples.
  • The full IGV user guide. https://igv.org/doc/desktop/ documents every track type and display option, well beyond what a single workshop can cover.
  • Video tutorials. The IGV YouTube channel has short, focused videos on specific features (data navigation, sequencing data, VCF files, RNA-seq) if you would rather watch a feature demonstrated than read about it.
Callout

Feedback

If anything in this lesson was unclear, or you found a mistake, please let your instructor know — lessons like this one improve with feedback from the people who work through them.

Key Points
  • The core IGV workflow — load a genome and tracks, navigate to a region of interest, then use track-specific sort/color/display options — applies broadly across data types.
  • IGV has many features beyond this lesson, including a web-embeddable sibling (igv.js) and batch scripting.