We have been asked what our DISCOVAR input data looks like, and the best way to answer this question is with some examples. We don’t claim that these data are necessarily representative, but they do illustrate what we are able to generate here at the Broad Institute.
DISCOVAR now generates variant lists using the Variant Calling Format (VCF). This is the standard used by the community and is supported by many tools. Whilst the VCF file contains all events found by DISCOVAR, the complementary
.variant file may contain additional information not easily represented in the VCF format. We encourage our users to look at both. The VCF should be filtered prior to use, and we have provided a tool and instructions on how to do this.
To facilitate calling variants using DISCOVAR on large genomes, we have created a tool to merge VCF files generated for overlapping regions. Simply run DISCOVAR on each region in turn (or in parallel to speed things up), then merge the VCF files that are produced. We currently recommend using a 50 kb region size, with a 10 kb overlap.
For more information on the VCF output, filtering and merging, please refer to our manual.
We’ve added a key purification step “A second 0.7x SPRI clean up was performed following adapter ligation to remove adapter dimers and library fragments below ~150 bp in size.” This improves performance.
DISCOVAR is designed to use 250 base reads. In response to numerous queries we have now posted instructions for generating such data on the HiSeq 2500, as this is the most cost effective approach.
We are now posting detailed instructions for generating libraries appropriate for use with DISCOVAR. Instructions for generating 250 base reads on the HiSeq 2500 will be posted as soon as we have a version that we’re sure is portable.
Are you getting the most out of your hardware when running DISCOVAR?
Take a look at our Computational Performance tips – they could help you get more bang for your computational buck!
DISCOVAR is a heavily multithreaded and memory intensive tool that will push your machines hard. Configuring your hardware to get the best performance isn’t straightforward, but with the right settings you may see significant improvements. After much experimentation and investigation, and with help from fellow DISCOVAR users, we have prepared a set of tips. We’ll continue to add and update them as we learn more, and we would like to hear about your experiences via our forum.
Revision 46631 contains a number of algorithmic improvements. In particular there are now less ‘false’ bubbles in assemblies. These arise particularly in assemblies at high (> 60x) coverage, as one might have e.g. for a bacterium. These bubbles have substantial support on both branches but examination of the quality score distributions of the read bases associated with both allows DISCOVAR to kill off one branch.
You can now download DISCOVAR compatible, high coverage, 250 base PCR-free reads for the trio of NA12878 (daughter), NA12891 (father) and NA12892 (mother) from the 1000 Genomes Data Coordination Center. With these data you will be able to run DISCOVAR to call variants on any region of the genome for the trio. Please be sure to read the release and publication policies governing these data.
Many people have asked if they can use their existing Illumina datasets with DISCOVAR – datasets that don’t meet the recommendations of ~60x coverage by 250 base paired reads from a ~700 bp PCR-free fragment library. We investigated and made some minor changes to the algorithm, embodied in release 46382 onwards, and it is now possible to use shorter reads from PCR libraries – with some caveats. We have successfully tested DISCOVAR on 100 base reads from a ~180 bp PCR fragment library, obtaining reasonable results but inferior to those generated from the recommended data. For more information on please see our FAQ.
Would you like to help us benchmark servers?
We are contemplating server purchases and would like to get the most bang for our buck. We imagine that some of you are in the same situation. Therefore, to share intelligence, we are creating a table that shows DISCOVAR performance stats, along with server configuration information. Please take a look at the current benchmark table, which we will continue to update as we get more results. Better yet – why not participate by benchmarking your systems and sharing the results with us.