Documentation error in RNAseq workflow

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



Search blog by tag

2013 ad agbt14 appistry ashg ashg2014 baserecalibrator belgium best-practices beta blog brussels bug bug-fixed cancer catvariants challenge combinegvcfs combinevariants commandline commandlinegatk commercial compbio competition conferences denovo depthofcoverage diagnosetargets downtime error fastaalternatereferencemaker fix forum gatk gatk-3-0 gatk-3-2 gatk3 genotype genotypegvcfs genotyperefinement gsa gvcf haploid haplotypecaller hardware holiday htsjdk ibm indelrealigner job job-offer jobs joint-analysis joint-discovery key license media meetings mendelianviolations multisample multithreading mutect nt pairhmm paper performance phone-home picard pipeline ploidy polyploid poster presentations press printreads queue randomlysplitvariants readbackedphasing reducereads reference-model release release-notes rnaseq search selectvariants service slides snow spam speed splitncigarreads status sting support syntax talks team third-party-tools topstory trivia troll unifiedgenotyper userstories validatevariants variantannotator variantrecalibrator variantstobinaryped version-highlights versions video videos vqsr webinar workshop


GATK Dev Team

@gatk_dev

New #GATK Guide category: Common Problems (suggest your pet peeves for inclusion!) https://t.co/dYZqN6E34n
26 Apr 15
New #GATK tutorial on using -bamout arg to visualize data after remapping by HaplotypeCaller: https://t.co/CDfYObEocg
26 Apr 15
@pathogenomenick @ECCMID If calling variants in repeat regions and/or care about indels, use caller that performs reassembly or equivalent
25 Apr 15
@pathogenomenick @ECCMID Thank you for mentioning that quality trimming is not important with modern tools!
25 Apr 15
@pathogenomenick @ECCMID Re: coverage QC, average is not enough, distribution matters; "can I answer questions in my intervals of interest?"
25 Apr 15