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




- Upcoming events

See Events calendar for full list and dates


- Recent events

See Events calendar for full list and dates


- Recent posts



- Follow us on Twitter

GATK Dev Team

@gatk_dev

Upcoming #GATK events in July : UK workshops and BOSC 17 https://t.co/rhcvvCzBHL
24 Jun 17
@VinceBattista Which package /URL are you trying that is not working?
20 Jun 17
@RemiMarenco Java 1.8 is supported already in GATK 3.7 -- but yes GATK4 will support it, as well as OpenJDK.
1 Jun 17
RT @dgmacarthur: Get in on the ground floor with an amazing team building software that's already transforming genomic analysis. https://t.…
26 May 17
I added a video to a @YouTube playlist https://t.co/fpNmKf6jlP GATK4: speed optimizations, new tools, and open source licensing
26 May 17

- Our favorite tweets from others

Getting started with #GoogleCloud and learnt that #Cromwell + #WDL by @broadinstitute is just awesome. Go #GATK
13 Jun 17
Thanks you @gatk_dev team for making GATK v4 open source! https://t.co/qXwhHCSD6s #Bioinformatics #Genomics
5 Jun 17
Huge thanks to the @gatk_dev team: they return to BSD license (https://t.co/xW80GJctrT)! Watch out for the #GATK package in #Bioconda!
26 May 17
This is great GATK @gatk_dev 4 open source (again), BSD3! 💯 https://t.co/jmsStAVE6S
25 May 17
Wooow, really exiting and cheerful news! Will load it up on our server for sure! Congrats @gatk_dev https://t.co/9ppcH4I4Mh
25 May 17
See more of our favorite tweets...