Date: Fri, 29 Mar 2024 04:35:42 -0500 (CDT)
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Overview
The Integrative Genomics Viewer (IGV) from the Broad Cen=
ter allows you to view several types of data files involved in any NGS anal=
ysis that employs a reference genome, including how reads from a dataset ar=
e mapped, gene annotations, and predicted genetic variants.
Learning Objectives
In this tutorial, we're going to learn how=
to do the following in IGV:
- Create a custom genome database (usually used for microbial genomes) or=
load a pre-existing genome assembly (usually used for the genomes of model=
organisms and higher Eukaryotes).
- Load output from mapping reads to a reference genome.
- Load output from calling genetic variants.
- Navigate the view of the genome and interpret the display of this data.=
Theory
Because NGS datasets are very large, it is=
often impossible or inefficient to read them entirely into a computer's me=
mory when searching for a specific piece of data. In order to more quickly =
retrieve the data we are interested in analyzing or viewing, most programs =
have a way of treating these data files as databases. Database indexes enable one=
to rapidly pull specific subsets of the data from them.
The Integrative Genomics Viewer is a progr=
am for reading several types of indexed database information, including map=
ped reads and variant calls, and displaying them on a reference genome. It =
is invaluable as a tool for viewing and interpreting the "raw data" of many=
NGS data analysis pipelines.
Table of Contents
Workflow 1: Viewing E=
. coli data in IGV
Data files
You can start this tutorial two ways:
- If you have a
mapping directory with output from the Mapping tutorial or =
the SNV calling t=
utorial, then you should use those files for part 1 of this tutorial. Y=
ou can proceed with either one alone or with both.
If you do not have any results=
, you can use some "canned" ones that we provide. Copy the entire =
contents of this directory back to your local machine:
$BI/gva=
_course/mapping/IGV
If you on o=
n a machine with a command line...
scp -r =
username@lonestar.tacc.utexas.edu:/corral-repl/utexas/BioITeam/gva_course/m=
apping/IGV .
Then skip down to #Launching IGV=
a>.
Prepare a GFF fea=
ture file for the reference sequence
IGV likes its reference genome files in GF=
F (Gene Feature Format). Unfortunately, our old friend bp_seqcon=
vert.pl
doesn't do GFF. So, we're going to show you another too=
l for sequence format conversion called Readseq.
Readseq is written in java. To use it you =
need to first download the file readseq.jar linked from here.
To get this onto TACC easily, use:
wget ht=
tp://iubio.bio.indiana.edu/soft/molbio/readseq/java/readseq.jar
The general command to run the software is=
one of these:
java -j=
ar readseq.jar
java -cp readseq.jar run
This should return the help for Readseq.=
p>
(Why the funny invocation? You are actuall=
y using the command java
and telling it where to fin=
d a "jar" file of java code to run. The -jar
and&nbs=
p;-cp
options run it in different ways. It's pretty confu=
sing.)
To do the conversion that we want, use thi=
s command:
java -c=
p readseq.jar run NC_012967.1.gbk -f GFF -o NC_012967.1.gbk.gff
It's a bit hard to figure out because, unl=
ike most conventions, it takes the unnamed arguments before the optional fl=
ag arguments, there is no example command, and you have to switch -jar to -cp
. Search online for usage exampl=
es when you can't figure something out from the help.
Take a look at the contents of the origina=
l Genbank file and the new GFF file and try to get a handle on what is goin=
g on in this conversion.
Side-note o=
n displaying BLAST results as GFF files in IGV or other browsers
Another useful trick with either IGV or UC=
SC: displaying your own BLAST results: BioPerl allows for super-easy conver=
sion from blast output to a gff file; IGV and the UCSC browser both underst=
and GFF files. The short script bl2gff.pl
does the conversion.=
Let's use the blast result we had from the=
earlier test for the JAG1 gene to show you how. You'll need to provide the=
input file - it's the ".oNNNNNN" output file from your blast job.
grep '^=
gi' blast_jag1.o586038 > jag1_blast.out
module load perl
module load bioperl
bl2gff.pl jag1_blast.out > jag1_blast.out.gff
The resulting jag1_blast.out.gff can be mo=
ved to your local machine and opened in IGV. Load the human reference first=
though!
If you have only done the mapping tutorial and NOT the variant calling =
tutorial
You will need to index your reference FAST=
A and convert your SAM output files into sorted and indexed BAM files. The =
"why?" behind these steps is described more fully in the Variant calling tutorial. If =
you are in your mapping
directory, these commands wi=
ll perform the necessary steps.
Copy files to your desktop
IGV is an interactive graphical viewer pro=
gram. You can't run it on TACC, so we need to get the relevant files back t=
o your desktop machine.
They include:
- Indexed reference FASTA files
- GFF reference sequence feature files
- Sorted and indexed mapped read BAM files
- VCF result files
- ... and possibly many other types of files.
The easiest way to to this is probably to =
copy everything you want to transfer into a new directory called IGV
. Since many of the tutorial output files had the same names (bu=
t resided in different directories) be careful to give them unique destinat=
ion names when you copy them into the new directory together.
For starters, you could change into your&n=
bsp;mapping
directory and run commands like these if you =
just came from the mapping tutorial:
mkdir I=
GV
cp NC_012967.1.fasta IGV
cp NC_012967.1.fasta.fai IGV
cp NC_012967.1.gbk.gff IGV
cp bowtie/SRR030257.sorted.bam IGV/bowtie.sorted.bam
cp bowtie/SRR030257.sorted.bam.bai IGV/bowtie.sorted.bam.bai
...
Now, copy this entire IGV directory back t=
o your local Desktop machine.
Remember ho=
w? Try it on your own first, before peeking...
In the terminal connected to Lonestar, fig=
ure out the complete path to the IGV directory.
Open a new terminal window on your Desktop=
. Fill in the parts in brackets <> in this command:
scp -r =
<username>@lonestar.tacc.utexas.edu:</full/path/to/IGV/> .
Launching IGV
There are two ways; Launching IGV in your =
web browser or by downloading the binaries locally and running IGV from you=
r machine.
Locally on the class=
room machines booted in Linux
This downloads the IGV executable and tell=
s the command line to launch it (via the java command).
wget ht=
tp://www.broadinstitute.org/igv/projects/downloads/IGV_2.3.32.zip
unzip IGV_2.3.32.zip
cd IGV_2.3.32
java -Xmx2g -jar igv.jar
In a Web browser
Navigate a web browser to this page:http://www.broadin=
stitute.org/software/igv/download. You will need to register your email=
address to use this option!
Go ahead and click on the "Launch with 2 G=
B" option. This will download a "Java Web Start" file that you can launch b=
y locating it on your Desktop and double-clicking.
Locally on a Mac or Windows comp=
uter
Use this link to download IGV:
http://www.broadinstitute.org/igv/projects/downloads/IGV_2.3.32.zip=
After unzipping, you should be able to cli=
ck on igv.bat
for Windows or igv.command<=
/code> on MacOSX to lauch IGV. If this is not working, you might need =
to try the web start.
Load genome into IGV
From the main window of IGV, click on =
;Genomes > Create .genome File... and you should be presented with the following window.
Enter the ID and Name of the Genome you ar=
e working with (these can be anything that makes sense to you) and select t=
he path to your *.fasta file (the index, *.fai file needs to be in the same=
directory), then select the path to your *.gff file for the Gene File. Cli=
ck OK and then save this *.genome file inside the same fol=
der as your data.
Load mapped reads into IGV
From the main window of IGV, click on =
;File > Load from File.... C=
hoose bowtie.sorted.bam
After importing your reference genome and =
loading an alignment file, click on the + button in the upper right until r=
eads appear! Then, your screen should look similar to the following:=
p>
And you are now free to investigate different areas and their alignments in=
the genome.
Navigating in IGV
There are a lot of things you can do in IG=
V. Here are a few:
- Zoom in using the slider in the upper right. Do t=
his until you see mapped reads and finally individual bases appear.
- Navigate by clicking and dragging in the window. =
This is how you move left and right along the genome.
- Navigate more quickly. Use
page-up page-down
, home
, end.
- Jump to the next point of interest. Click on a tr=
ack name on the left side of the window (Ex: bowtie.vcf), to select it. You=
can then use
control-f
and control-b to jump forward and backward within that list of features. Try thi=
s on the variant calls track.
- Jump right to a gene. (If you have gene features =
loaded.) Type its name into the search box. Try "topA".
- Load multiple BAM alignments or VCF files at once.&nbs=
p;Try this to compare a few different regions between the bowtie and BWA re=
sults.
- Change the appearance of genes. Right click on th=
e gene track and try "expanded". Experiment with the other options.
- Change the appearance of reads. Right click on a =
BAM track and choose "show all bases" and "expanded". Experiment with the o=
ther options.
See the IGV Manual for more tips and h=
ow to load other kinds of data.
Exercises
- Why are some reads different colors? Hint: Try changing the display opt=
ions to show read pairs and editing some of the distance constraints.
What is a typical mapping quality (MQ)=
for a read? Convert this to the probability that it is mismapped.
Remember th=
e formula for a Phred quality score?
The estimated probability that a read is m=
apped incorrectly is 10^(-MQ/10).
Can you find a variant where the seque=
nced sample differs from the reference? This is going to be like looking fo=
r a needle in a haystack. Fortunately, we are going to learn how to use var=
iant callers tomorrow and then we'll be able to zoom right to areas where t=
here are discrepancies between reads and the reference genome that might in=
dicate there were mutations in the sequenced E. coli.
Some intere=
sting locations to look at for the time being...
- Coordinate 161,041. What gene is this in and what is the effect on the =
protein sequence?
- Coordinate 3,248,957. What gene is this in and what is the effect on th=
e protein sequence?
- Coordinate 4,015,892. What is different about the reads mapped to this =
location?
- Coordinate 3,894,997. What type of mutation is this?
- Coordinate 1,733,647. What's going on here?
- See if you can find more interesting locations. There are ~40 mutations=
total in this sample.
Load variant calls into IGV
We're really interested in places in the g=
enome where we think there are mutations. If you have completed the Variant calling tutori=
al, then you can load your VCF files to check out those spots, but firs=
t you need to (guess what?) index it.
You can do this from within IGV:
- Choose Tools > Run igvtools.=
...
- Choose "index" from the commands drop-down menu.
- Select your *.vcf file (Ex:
bowtie.vcf
) for "Input Fi=
le"
- Click the "run" button.
It will look like nothing has happened, bu=
t you can now close the "Run" window and choose File&=
nbsp;> Load File. If you navigate to your IGV dire=
ctory, you will now see a brand new bowtie.vcf.idx
f=
ile. You can now load the file bowtie.vcf
, and it will sh=
ow up as a new track near the top of your window.
Tip: You can also in=
dex BAM and FASTA files the same way inside of IGV if you haven't already c=
reated indexes for them. But, it's usually easier and quicker to do this on=
the command line at TACC. Indexing BAM files can be a computationally heft=
y task.
Exercises
Check out the rbsA =
gene region? What's going on here?
Answer
There was a large deletion. Can you figure=
out the exact coordinates of the endpoints?
Navigate to coordinate 3,289,962. Comp=
are the results for different alignment programs and settings. Can you=
explain what's going on here?
Answer
There is a 16 base deletion in the glt=
B gene reading frame.
What is going on in the pykF<=
/em> gene region? You might see red read pairs. What does that mean? C=
an you guess what type of mutation occurred here?
Answer
The read pairs are discordantly mapped. Th=
ere was an insertion of a new copy of a mobile genetic element (an IS15=
0 element) that exists at other locations in the reference sequence.=
p>
Workflow 2: Viewing Human=
Genome Data in IGV
If you've made it through the other exerci=
ses on your own data, take a look at some human genome re-sequencing data w=
here the files can be loaded directly from public databases.
Advanced exerc=
ise: human data scavenger hunt
See this page for the human data scaven=
ger hunt
Data from the CEU trio from the 1000 Genom=
es Project can be found directly from the Broad's server for IGV. There are=
now MANY genomes available this way - one of the original family trios are=
represented in samples NA12892, NA12891, and NA12878 (mom, dad, child resp=
ectively).
Find one or more dbSNP accession numbers f=
or SNPs apparent in one of the two 1000 genomes project trios in the GABBR1=
gene.
Steps:
- Download and install the Integrative Genome Viewer from the Broad Insti=
tute.
- Select "Human hg18" or "Human hg19" as the reference genome
- Get some data: File > Load from Server=E2=80=A6 > 1000 ge=
nomes > Alignments > CEU Trio WGS > select those 3 samples
- Navigate to the rightmost exons of the GABBR1 gene
- Zoom in until you find some SNPs - they might be in exons or introns; t=
here is also at least one example of a short insertion variant between exon=
s 2 and 3
- Load and look at the SNP track: File > Load from server >=
Annotations > Variants and Repeats > dbSNP
This is whole genome coverage data; later =
we'll look at exome data.
Answer
rs29220, rs29222, rs28359988, rs76688565, =
there might be more in the locus; I got tired of looking.
Is there an alternate allele in the child =
which correlates with one or both of the parents? (i.e. - do genetics work?=
)
From here...
You can use IGV to visualize mapped reads =
and predicted variants from any later tutorial!
You may also want to check out alternative=
genome browsers:
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