Open main menu

Genome Analysis Wiki β

Changes

no edit summary
'''Note:''' the latest version of this practical is available at: [[SeqShop: Variant Calling and Filtering for SNPs Practical]]
* The ones here is the original one from the June workshop (updated to be run from elsewhere)
 
 
==Introduction==
See the [[Media:SeqShop - GotCloud snpcall.pdf|introductory slides]] for an intro to this tutorial.
''If you are running during the SeqShop Workshop, please skip this section.''
<div class="mw-collapsible-content">
=== Download the example data ===
 
=== Setup your run environment ===
 
Environment variables will be used throughout the tutorial.
We recommend that you setup these variables so This tutorial builds on the alignment tutorial, if you won't have to modify every command in the not already, please first run that tutorial.  <div class="mw-collapsible mw-collapsed" style="width:500px">I'm using bash (replace the paths below with the appropriate paths):<div class="mw-collapsible-content">* Point to where you installed GotCloud*:<pre>export GC=/home/username/gotcloud</pre>* Point to where you installed the seqshop files*:<pre>export SS=/home/username/seqshop/</pre>* Point to where you want the output to go*:<pre>export OUT=/home/username/seqshop_output/</pre></div></div> <div class="mw-collapsible mw-collapsed" style="width:500px">I'm using tcsh (replace the paths below with the appropriate paths):<div class="mw-collapsible-content">* Point to where you installed GotCloud*:<pre>setenv GC /home/username/gotcloud</pre>* Point to where you installed the seqshop files*:<pre>setenv SS /home/username/seqshop/</pre>* Point to where you want the output to go*[[SeqShop:<pre>setenv OUT /home/username/seqshop_output/</pre></div></div> </div></div>_Sequence_Mapping_and_Assembly_Practical, June 2014|Alignment Tutorial]]
{{SeqShopRemoteEnv}}
== Examining GotCloud SnpCall Input files ==
Per sample BAM files contain sequence reads that are mapped to positions in the genome.
For a reminder on how to look at/read BAM files, see: [[SeqShop:_Sequence_Mapping_and_Assembly_Practical, June 2014#BAM_Files|SeqShop Aligment: BAM Files]]
For this tutorial, we will use the 4 BAMs produced in the [[SeqShop: Sequence Mapping and Assembly Practical, June 2014]] as well as with 58 BAMs that were pre-aligned to that 1MB region of chromosome 22.
=== Reference Files ===
<li>View Screenshot</li>
<div class="mw-collapsible-content">
[[File:RefDir.png|500px700px]]
</div>
</div>
;Do you notice a difference between this index and yours?
<ul>
<div class="mw-collapsible mw-collapsed" style="width:500px550px">
<li>Answer:</li>
<div class="mw-collapsible-content">
<li>It doesn't have a full path to the BAM file, while your index has /home/...</li>
[[File:Bamindex1.png|300px]]
<li>That's ok, we will use the <code>--base_prefix ${SS}</code> command-line option to prefix the BAM paths</li><li>Alternatively, we could have set BAM_INDEX in <code>gotcloud.conf</code> contains to the path to those the BAMs<pre>BAM_INDEX = /home/username/seqshop/example</pre> </li>[[File<ul><li>NOTE:BamindexConfthe conf file can't interpret ${SS} environment variables or '~', so you would have to specify the full path</li><li>We just used the command-line option for this tutorial since this path will vary by user.png|300px]]</li></ul>
</div>
</div>
We need to add these BAMs to our index
* Append the bam.index from the pre-aligned BAMs to the one you generated from the alignment pipeline
** '''Be sure to do this command just once'''
cat ${SS}/bams/bam.index >> ${OUT}/bam.index
* ">>" will append to the file that follows it
* Be sure to do this command just once
** Check that your BAM index is the correct size
**:<pre>wc -l ${OUT}/bam.index</pre>
We will use the same configuration file as we used yesterday in GotCloud Align.
See [[SeqShop:_Sequence_Mapping_and_Assembly_Practical_Sequence Mapping and Assembly Practical, June 2014#GotCloud Configuration File|SeqShop: Alignment: GotCloud Configuration File]] for more details
* Note we want to limit snpcall to just chr22 so the configuration already has <code>CHRS = 22</code> (default was 1-22 & X).
Now that we have all of our input files, we need just a simple command to run:
${GC}/gotcloud snpcall --conf ${SS}/gotcloud.conf --numjobs 4 --region 22:36000000-37000000 --base_prefix ${SS} --outdir ${OUT}
* <code>${GC}/gotcloud</code> runs GotCloud
* <code>align</code> tells GotCloud you want to run the alignment pipeline.
* <code>--conf</code> tells GotCloud the name of the configuration file to use.
** The configuration for this test was downloaded with the seqshop input files.
* --numjobs tells GotCloud how many jobs to run in parallel
** Depends on your system
* --region 22:36000000-37000000
** The sample files are just a small region of chromosome 22, so to save time, we tell GotCloud to ignore the other regions
* <code>--base_prefix</code> tells GotCloud the prefix to append to relative paths.
** The Configuration file cannot read environment variables, so we need to tell GotCloud the path to the input files, ${SS}
** Alternatively, gotcloud.conf could be updated to specify the full paths
* <code>--out_dir</code> tells GotCloud where to write the output.
** This could be specified in gotcloud.conf, but to allow you to use the ${OUT} to change the output location, it is specified on the command-line
<div class="mw-collapsible mw-collapsed" style="width:500px">
* Scroll down: they all look like they <code>PASS</code>
 
Remember, use 'q' to exit out of less
q
Let's check if they are all PASS.
=== Genotype Refinement Input ===
The GotCloud genotype refinement pipeline takes as input ${OUT}/split/chr22/chr22.filtered.PASS.vcf.gz (the VCF file of PASS'ing SNPs from snpcall).
The bam index and the configuration file we used for GotCloud snpcall will tell GotCloud genotype refinement everything it needs to know, so no new input files need to be prepared.
=== Running GotCloud Genotype Refinement ===
Since everything is setup, just run the following command (very similar to snpcall).
${GC}/gotcloud ldrefine --conf ${INSS}/gotcloud.conf --numjobs 2 --region 22:36000000-37000000--base_prefix ${SS} --outdir ${OUT}
* Beagle will take about 2-3 minutes to complete
* Thunder will automatically run and will take another 3-4 minutes
 
<div class="mw-collapsible mw-collapsed" style="width:350px">
When completed, it should look like this:
<div class="mw-collapsible-content">
[[File:GcldrefineOut.png]]
</div>
</div>
=== Genotype Refinement Output ===
; What's new in the output directory?
 
<ul>
<div class="mw-collapsible mw-collapsed" style="width:500px">
<li>Answer</li>
<div class="mw-collapsible-content">
:<pre>ls ${OUT}</pre>
<ul>
<li><code>beagle</code> directory : Beagle output</li>
<li><code>thunder</code> directory : Thunder output</li>
<li><code>umake.beagle.conf*</code> : Configuration values Contain the configuration & steps used for GotCloud beagle</li><li><code>umake.beagle.Makefile</code> : GNU makefile for commands run as part of GotCloud beagle</li><li><code>umake.beagle.Makefile.log</code> : Log of the in GotCloud beagle run</li>
<li><code>umake.thunder.*</code> files : Contain the configuration & steps used in GotCloud thunder</li>
</ul>
</ul>
Let's take a look at that interesting location we found in the [[SeqShop:_Sequence_Mapping_and_Assembly_Practical, June 2014#Accessing_BAMs_by_Position|alignment tutorial]] : chromosome 22, positions 36907000-36907100
Use tabix to extract that from the VCFs:
The region we selected contains ''APOL1'' gene, which is known to play an important role in kidney diseases such as nephrotic syndrome. One of the non-synonymous risk allele, <code>rs73885139</code> located at position <code>22:36661906</code> increases the risk of nephrotic syndrome by >2-folds. Let's see if we found the interesting variant by looking at the VCF file by position.
${GC}/bin/tabix ${OUT}/vcfs/chr22/chr22.filtered.vcf.gz 22:36661906 | head -1
Did you see a variant at the position?
${GC}/bin/tabix ${OUT}/vcfs/chr22/chr22.filtered.vcf.gz 22:36661906 | head -1
22 36661906 . A G 18 PASS DP=409;MQ=59;NS=62;AN=124;AC=2;AF=0.013827;AB=0.4065;AZ=-0.5287;
FIC=-0.0092;SLRT=-0.0075;HWEAF=0.0138;HWDAF=0.0276,0.0000;LBS=36,36,0,0,1,1,0,0;
Let's check the sequence data to confirm that the variant really exists
${GC}/bin/samtools tview $IN{SS}/bams/HG01242.recal.bam $REF{SS}/ref22/human.g1k.v37.chr22.fa
* Type 'g' to go to a specific position
Let's get some information on the BEAGLE VCF:
perl ${SS}/ext/bed-diff.pl --vcf1 ${SS}/ref22/1kg.omni.chr22.36Mb.vcf.gz --vcf2 ${OUT}/beagle/chr22/chr22.filtered.PASS.beagled.ALL.vcf.gz --gcRoot ${GC} --out ${OUT}/bedDiff.beagle
perl ${EXT}/bed-diff.pl --vcf1 ${REF}/1kg.omni.chr22.36Mb.vcf.gz --vcf2 ${OUT}/beagle/chr22/chr22.filtered.PASS.beagled.ALL.vcf.gz --gcRoot ${GC} --out ${OUT}/bedDiff.beagle
Look at the results:
Now, let's see if it improved after running Thunder VCF:
perl ${EXTSS}/ext/bed-diff.pl --vcf1 ${REFSS}/ref22/1kg.omni.chr22.36Mb.vcf.gz --vcf2 ${OUT}/thunder/chr22/ALL/thunder/chr22.filtered.PASS.beagled.ALL.thunder.vcf.gz --gcRoot ${GC} --out ${OUT}/bedDiff.thunder
Look at the results: