We discovered today that we made an error in the documentation article that describes the RNAseq Best Practices workflow. The error is not critical but is likely to cause an increased rate of False Positive calls in your dataset.

The error was made in the description of the "Split & Trim" pre-processing step. We originally wrote that you need to reassign mapping qualities to 60 using the ReassignMappingQuality read filter. However, this causes all MAPQs in the file to be reassigned to 60, whereas what you want to do is reassign MAPQs only for good alignments which STAR identifies with MAPQ 255. This is done with a different read filter, called ReassignOneMappingQuality. The correct command is therefore:

java -jar GenomeAnalysisTK.jar -T SplitNCigarReads -R ref.fasta -I dedupped.bam -o split.bam -rf ReassignOneMappingQuality -RMQF 255 -RMQT 60 -U ALLOW_N_CIGAR_READS

In our hands we see a bump in the rate of FP calls from 4% to 8% when the wrong filter is used. We don't see any significant amount of false negatives (lost true positives) with the bad command, although we do see a few more true positives show up in the results of the bad command. So basically the effect is to excessively increase sensitivity, at the expense of specificity, because poorly mapped reads are taken into account with a "good" mapping quality, where they would normally be discarded.

This effect will be stronger in datasets with lower overall quality, so your results may vary. Let us know if you observe any really dramatic effects, but we don't expect that to happen.

To be clear, we do recommend re-processing your data if you can, but if that is not an option, keep in mind how this affects the rate of false positive discovery in your data.

We apologize for this error (which has now been corrected in the documentation) and for the inconvenience it may cause you.


sirian


Thanks for the correction! I was actually wondering a little bit why you changed every score.

Wed 11 Jun 2014

sboyle


Thanks for the correction Geraldine!

Wed 11 Jun 2014

kam


Here's a working link for [ReassignOneMappingQuality](https://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_gatk_engine_filters_ReassignOneMappingQualityFilter.php). Have you considered using the mapping quality formula proposed by the authors of subread? This mapping quality score works for any read mapper. See page 20 in the [Subread User's Guide](http://bioinf.wehi.edu.au/subread-package/SubreadUsersGuide.pdf).

Wed 11 Jun 2014

Geraldine_VdAuwera


@kam This may be a good recommendation to make to the authors of the mappers.

Wed 11 Jun 2014

justinjj


Dear Geraldine, Could you please clarify me is there any difference or issue if I use the mapq as 50 instead of 60 as suggested to run GATK? The bwa aligner higher quality is 60 but the tophat2 (uses bowtie2) provide higher quality/unique mapq as 50 and GATK runs without any error in both cases also by star aligner "--outSAMmapqUnique 50" The RNAseq mappers is already giving meaningful quality score? https://software.broadinstitute.org/gatk/guide/article?id=3891 (So we use the GATK’s ReassignOneMappingQuality read filter to reassign all good alignments to the default value of 60. This is not ideal, and we hope that in the future RNAseq mappers will emit meaningful quality scores, but in the meantime this is the best we can do.) Thanks.

Wed 11 Jun 2014

Geraldine_VdAuwera


Yes, that's fine. If newer versions of the mappers produce MAPQ scores in that range, there is no need to reassign a different value.

Wed 11 Jun 2014

justinjj


Thanks Geraldine.

Wed 11 Jun 2014




At a glance



Follow us on Twitter

GATK Dev Team

@gatk_dev

RT @NJL_NGS: I just opened an new position. Join our group at Broad and help us support both clinical and research projects. https://t.co
1 Dec 16
RT @LalDennis: Friday in the Online Journal Club "Hail: Scalable genetic analyses allowing to tackle ultra large data". All infos https://t…
1 Dec 16
Looking forward to another year of #GATK workshops around the world, taking invitations for 2017 https://t.co/0sCdvGStaH
24 Nov 16
Thinking about pipelining #GATK with WDL? Take a tour of WDL resources by @WDL_dev: https://t.co/5zbWyn038s
21 Nov 16
RT @broadinstitute: You can watch @dgmacarthur's #MPGPrimer on #ExAC, #gnomAD on YouTube: https://t.co/O5y5tBT6Eo
19 Nov 16

Our favorite tweets from others

Currently in a time-out for saying that duck fat had a certain "je ne sais quack" at the thanksgiving dinner table.
25 Nov 16
@dgmacarthur @BioMickWatson @StevenNHart @splon There's even a shop near Broad that apparently fixes Hail code erro… https://t.co/IZ4BcgRZYE
19 Nov 16
I'm very happy to be at GATK Workshop hands on with @gatk_dev ! There's always something to learn. Tip: there is free coffee. Lol
8 Nov 16
Have recently begun to think of slide editing as ‘downsampling my slides’. I suspect this indicates something is wrong with me.
1 Nov 16
See more of our favorite tweets...
Search blog by tag

appistry ashg ashg16 benchmarks best-practices bug bug-fixed cancer cloud cluster cnv collaboration commandline commandlinegatk community compute conferences cram cromwell denovo depthofcoverage diagnosetargets error fix forum gatk3 gatk4 genotype genotype-refinement genotypegvcfs google grch38 gvcf haploid haplotypecaller hg38 holiday hts htsjdk ibm intel java8 job job-offer jobs license meetings mendelianviolations mutect mutect2 ngs outreach pairhmm parallelism patch performance phone-home picard pipeline plans ploidy polyploid poster presentations printreads profile promote release release-notes rnaseq runtime saas script search sequencing service slides snow speed status sting support syntax talks team terminology third-party-tools topstory troll tutorial unifiedgenotyper vcf-gz version-highlights versions vqsr wdl webinar workflow workshop