Differences

This shows you the differences between two versions of the page.

--- mkatari-bioinformatics-august-2013-gatknotes [2014/07/09 07:18] – mkatari
+++ mkatari-bioinformatics-august-2013-gatknotes [2015/06/08 07:45] – mkatari
@@ Line 153: / Line 153: @@
      -GF GT -GF GQ \
      -o PTC_human.gatk.vcf.table
+</code>
+In order to filter your vcf file based on quality measures, depth, and also statistical significance, you can use variant filter option in the gatk toolkit. Below is an example of suggested filters for data that has low coverage.
+<code>
+java -Xmx2g -jar /export/apps/gatk/3.1.1/GenomeAnalysisTK.jar \
+    -R /home/emasumba/cassavaV5_0.chromsomesRomanNumerals.fa \
+    -T VariantFiltration \
+    -o namikonga_albert_filter.vcf \
+    --variant /home/emasumba/Namikonga_Albert.gatk.vcf \
+    --filterExpression "QD < 2.0 || MQ < 40.0 || FS > 60.0 || HaplotypeScore >13.0" \
+    --filterName "mannyfilter"
+</code>
+Good descriptions of the different information on vcf files [[https://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_gatk_tools_walkers_annotator_HaplotypeScore.php|GATK Docs]]
+Finally to save the SNPs that passed your filter, you simply use the selectvariant tool.
+<code>
+java -Xmx2g -jar /export/apps/gatk/3.1.1/GenomeAnalysisTK.jar \
+    -T SelectVariants \
+    --variant namikonga_albert_filter.vcf \
+    -o namikonga_albert_filter_only.vcf \
+    -ef \
+    -R /home/emasumba/cassavaV5_0.chromsomesRomanNumerals.fa
 </code>