DepthOfCoverage and DiagnoseTargets: our plans for development and support

We have decided to continue providing and supporting DepthOfCoverage and DiagnoseTargets for the foreseeable future. Going forward, we'll try to integrate them and develop their features to address the main needs of the community. To this end we welcome your continuing feedback, so please feel free to contribute comments and ideas in this thread.

To all who took the time to tell us what you find useful about DoC and DT (and what you wish it could do), a big thank you! This is always very useful to us because it helps us identify which features are most valuable to our users.



mengyuankan


Thanks Geraldine. A newbie question: what's the difference between DepthOfCoverage and DiagnoseTargets, and which one do you recommend to use (or both)?

Tue 12 Mar 2013

Geraldine_VdAuwera


The two are somewhat convergent, but basically DepthOfCoverage allows you to evaluate the depth of coverage in your data at certain sites or over intervals generally, whereas DiagnoseTargets is more specifically designed to evaluate the quality of data covering exome target intervals. The best thing to do is to read their respective documentations pages (links below) and see which sounds like it will suit you needs best. http://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_sting_gatk_walkers_coverage_DepthOfCoverage.html http://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_sting_gatk_walkers_diagnostics_targets_DiagnoseTargets.html

Tue 12 Mar 2013

kevyin


Hi @Geraldine_VdAuwera and thanks for support on this. The DepthOfCoverage documentation mentions -nt as a parallelism option but I get an error. `##### ERROR MESSAGE: Invalid command line: Argument nt has a bad value: The analysis DepthOfCoverage aggregates results by interval. Due to a current limitation of the GATK, analyses of this type do not currently support parallel execution. Please run your analysis without the -nt option.` My command line: `java -jar GenomeAnalysisTK.jar -T DepthOfCoverage -I ExampleBAM.bam -R exampleFASTA.fasta -o ./test_coverage_out -nt 4` Is this an error in the documentation? Or am I missing something? Thanks.

Tue 12 Mar 2013

Geraldine_VdAuwera


Hi @kevyin, DOC is currently set up to aggregate statistics over intervals by default, which is incompatible with the `-nt` mode. You can disable this behavior by using the `--omitIntervalStatistics` flag, which should make `-nt` work. Let me know if you have any issues with that. We may change the default behavior in future; in any case we will add a note about this to the documentation. Thanks for reporting this!

Tue 12 Mar 2013



Search blog by tag

2013 ad agbt14 appistry baserecalibrator belgium best-practices blog bqsr broken-links brussels bug bug-fixed cancer catvariants challenge combinegvcfs combinevariants commercial community compbio competition conferences depthofcoverage diagnosetargets documentation downtime error fastaalternatereferencemaker forum gatk gatk-3-0 gatk-3-1 gatk-3-2 gatk-lite gatk2 gatk3 genotypegvcfs gsa gsa-announce gvcf haplotypecaller hardware holiday indelrealigner intel job job-offer jobs joint-analysis joint-discovery key license lite media meetings multisample multithreading mutect nt optimization pairhmm paper performance phone-home pipeline poster presentations press printreads queue randomlysplitvariants readbackedphasing reducereads reference-model release release-notes rnaseq scatter-gather selectvariants slides spam splitncigarreads support talks topstory trivia tutorials unifiedgenotyper userstories validatevariants variantannotator varianteval variantrecalibrator variantstobinaryped version-highlights video videos webinar workshop


GATK Dev Team

@gatk_dev

RT @edgenome: We are recruiting a bioinformatician to join our team in Roslin. Apply before the 5th of September http://t.co/i3CtwG7r1K
19 Aug 14
RT @DrLabRatOry: .@PatSchloss “If you want to make a pie chart… you should be shot, but you could do it with this summary file” #edamame2014
16 Aug 14
Appistry webinar on RNAseq analysis pipeline 8/21 @appistry http://t.co/vGjoZxbhqA
15 Aug 14
@evolvability @joshuas Effect may be minimal on good quality data. Helps more if data is messy.
14 Aug 14
@joshuas @evolvability It is technically not needed for HC, but still improves results of BQSR, hence still in Best Practices.
14 Aug 14