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Variant Discovery in High-Throughput Sequencing Data

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Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size. Learn more

How to apply VQSR to mouse samples, to find the best thresholds for hard-filtering

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    Gökalp Çelik

    Hi Paulo Ricardo

    Your best bet would always be the MGI database and Ensembl

    https://www.jax.org/research-and-faculty/resources/mgi-snp-database 

    https://www.ensembl.org/Mus_musculus/Info/Index 

    You may also want to check the mouse genome project website for any additional resources

    https://www.sanger.ac.uk/data/mouse-genomes-project/ 

    I hope these would help.

    Regards.

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    Paulo Ricardo

    Thank you for your response, I believe I will use resources from all the references you provided. However, how would I create the code?  For example, instead of hapmap what would I put, would I change Known, or training, or truth, or prior parameters?

    hapmap,known=false,training=true,truth=true,prior=15.0:hapmap_3.3.hg38.sites.vcf.gz 
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    Gökalp Çelik

    Definition for this parameter indicates that prior values are not used by the algorithm therefore it may not be too crucial. 

    --resource <FeatureInput>     A list of sites for which to apply a prior probability of being correct but which aren't
                                  used by the algorithm (training and truth sets are required to run)  This argument must be
                                  specified at least once. Required.

    I will ask our team to get more insights into this matter. 

    Regards. 

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    Paulo Ricardo

    Thank you very much for your availability.

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