The current GATK version is 3.7-0
Examples: Monday, today, last week, Mar 26, 3/26/04

#### Howdy, Stranger!

It looks like you're new here. If you want to get involved, click one of these buttons!

GATK 3.7 is here! Be sure to read the Version Highlights and optionally the full Release Notes.
Register now for the upcoming GATK Best Practices workshop, Feb 20-22 in Leuven, Belgium. Open to all comers! More info and signup at http://bit.ly/2i4mGxz

# Local Realignment around Indels

Dev Posts: 71
edited June 2016

## Realigner Target Creator

For a complete, detailed argument reference, refer to the GATK document page here.

## Indel Realigner

For a complete, detailed argument reference, refer to the GATK document page here.

# Running the Indel Realigner only at known sites

While we advocate for using the Indel Realigner over an aggregated bam using the full Smith-Waterman alignment algorithm, it will work for just a single lane of sequencing data when run in -knownsOnly mode. Novel sites obviously won't be cleaned up, but the majority of a single individual's short indels will already have been seen in dbSNP and/or 1000 Genomes. One would employ the known-only/lane-level realignment strategy in a large-scale project (e.g. 1000 Genomes) where computation time is severely constrained and limited. We modify the example arguments from above to reflect the command-lines necessary for known-only/lane-level cleaning.

The RealignerTargetCreator step would need to be done just once for a single set of indels; so as long as the set of known indels doesn't change, the output.intervals file from below would never need to be recalculated.

 java -Xmx1g -jar /path/to/GenomeAnalysisTK.jar \
-T RealignerTargetCreator \
-R /path/to/reference.fasta \
-o /path/to/output.intervals \
-known /path/to/indel_calls.vcf


The IndelRealigner step needs to be run on every bam file.

java -Xmx4g -Djava.io.tmpdir=/path/to/tmpdir \
-jar /path/to/GenomeAnalysisTK.jar \
-I <lane-level.bam> \
-R <ref.fasta> \
-T IndelRealigner \
-targetIntervals <intervalListFromStep1Above.intervals> \
-o <realignedBam.bam> \
-known /path/to/indel_calls.vcf
--consensusDeterminationModel KNOWNS_ONLY \
-LOD 0.4

Post edited by shlee on
Tagged:

• PolandMember Posts: 15
edited May 2016

IT gives me this error : ##### ERROR MESSAGE: SAM/BAM/CRAM file htsjdk.samtools.SamReader\$PrimitiveSamReaderToSamReaderAdapter@301da01d appears to be using the wrong encoding for quality scores: we encountered an extremely high quality score of 65. Please see https://www.broadinstitute.org/gatk/guide?id=6470 for more details and options related to this error. Any IDea?? "this link does not take me to any place"

the command is :
java -Djava.io.tmpdir=./temp/ -jar GenomeAnalysisTK.jar -T RealignerTargetCreator scores -R genome.fa -known maize_snps_v3.vcf -I input_merged_lane_sorted_dedup.bam -o input_merged_lane_sorted_dedup_intervals

Using GATK v3.5

Post edited by medhat on

#### Issue · Github May 2016 by Sheila

Issue Number
931
State
closed
Last Updated
Assignee
Array
Milestone
Array
Closed By
chandrans

@medhat
Hi,

-Sheila

• PolandMember Posts: 15

thanks a lot it was fixed by adding flag --fix_misencoded_quality_score

@medhat
Great. I just made a note to fix the error message so it points to the correct article

• Member Posts: 2

The link to Step-by-step tutorial(s), (howto) Perform local realignment around indels, is broken: https://www.broadinstitute.org/gatk/guide/article?id=2800 . Some other howto links also not working. Could you please fix it? Thanks.

• Member Posts: 2

The link is in Best Practice -> Pre-processing -> Realign Indels.

@daxue
Hi,

I suspect those are being fixed as we talk on the thread!

As for the how to, here it is. This new article replaces the old article (2800).

-Sheila

Yes this is actually fixed in web dev, and we'll be pushing the updates later this week following the 3.6 release (which is happening today).

Geraldine Van der Auwera, PhD

• CardiffMember Posts: 3

Dear GATK team

I was hoping you could advise how to resolve the 54bp deletion in the attached screen shot. This data is from a tumour-only amplicon experiment. It actually does get called with HaplotypeCaller but I understand it's not really suitable to use the local reassembly tool with low complexity data, is that correct? So I've been trying to force IR to resolve it by manipulating the LOD, greedy and max consensuses values but the gap wont open. I have checked the region is included in the interval file.

Any thoughts or suggestions much appreciated.

Thanks
Matt

@CardiffBioinf
Hi Matt,

For tumor data, you should be using MuTect2.

-Sheila

• UKMember Posts: 8

Hello,

I have run indel realignment on whole genome data. After indel realignment I got an high frequency of deletions at the end of the reads (up to 0.16). These high deletion frequencies at the end of the reads did not appear before running indel realignment. Is this normal? I have included plots of indel frequencies (after indel realignment and before indel realignment).
Thanks,

Marie

@mariel
Hi Marie,

Indeed, we expect a higher number of indels at the ends of reads. Have a look at the tool documentation and the Indel Realignment presentation here.

-Sheila

@mariel
Hi again Marie,

To clarify, Indel Realignment enables you to identify indels that you would normally miss, especially at the ends of reads. This is because mappers tend to make mistakes at the ends of reads. So we do expect to see more indels at ends of reads after running Indel Realignment. However, we don't expect to see overall more indels covered only by ends of reads. If that is what you are seeing, this may actually be a sign of artifacts.

Can you tell us more about the sequencing technology you used? Is it exome data? How much coverage do you have? In low coverage exome data, you could have more sites that are only covered by ends of reads, which skews the expectations. Have you done the variant calling and gotten the TiTv ratio?

Thanks,
Sheila

• UKMember Posts: 8

@Sheila

Hi Sheila,

I am using PE150bp sequencing on an Illumina HiSeq XTen. It is whole genome re-sequencing. I am mapping against the reference genome of another (related) species. I have a mean coverage of 10x.

I haven't done the variant calling, I'm using ANGSD for SNP calling and genotype likelihoods estimation as I have relatively low coverage data.

Thanks,

Marie

#### Issue · Github November 2016 by Sheila

Issue Number
1406
State
closed
Last Updated
Assignee
Array
Milestone
Array
Closed By
vdauwera

That sounds like it could be an artifact, perhaps caused (or aggravated) by mapping against a different species. It's hard to say without a deeper analysis but I would definitely consider this a red flag. You'll need to evaluate your variant calling results carefully. Unfortunately since it is a use case that we have no experience with we can't help you beyond this.

Geraldine Van der Auwera, PhD

• UKMember Posts: 8

@Geraldine_VdAuwera