Visualization using Integrated Genome Viewer (IGV)

Overview

The Integrative Genomics Viewer (IGV) from the Broad Center allows you to view several types of data files involved in any NGS analysis that employs a reference genome, including how reads from a dataset are mapped, gene annotations, and predicted genetic variants.

Get your data

We are going to look at two mapping results- for samples C1_R1 and C2_R2. We can download the corresponding bam files and index files by either scping them over the server to your computer. Or I have placed them in a utbox folder. Download the corresponding bam files and index files from here onto your computer.

Some useful IGV Features

SNPS
Coverage tracks- to see coverage in one sample vs another acorss a certain location.
All sorts of views for paired end data. These help us find analogous pair mappings, split mappings etc.

Launching IGV

For the remainder of the tutorial, work on your local machine. NOT THE SERVER!

There are two ways; Launching IGV in your web browser or by downloading the binaries locally and running IGV from your machine. We are just going to run it from web browser for this demo.

In a Web browser

Navigate to https://igv.org/app/ and this opens up IGV on the web browser.

Load genome track on IGV

From the main window of IGV, click on Genomes > Load Genome from server.... Choose dm3 Because our genome is already on the IGV server, we can do this.

Load mapped reads into IGV

From the main window of IGV, click on File > Load from File.... Choose your bam file and bai file.

After loading the reference genome and loading an alignment file, click on the + button in the upper right until reads appear!

Look at one of the differentially expressed genes on IGV

Some of the top upregulated genes were:

crc

KdelR

Nacalpha

CG8979

CG4389

Vha68-2

regucalcin

CG3835

CG1746

Just type the gene name into the text box to look for the gene. Notice you'll need to zoom in and out to see the whole gene. See if you can identify spliced alignments. Look to see how coverage is at exons compared to introns.

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