For a complete, detailed argument reference, refer to the GATK document page here.
For a complete, detailed argument reference, refer to the GATK document page here.
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
Hi,
I am trying to decide between two approaches for performing realignment around indels. I have ~600 samples that have been aligned to a very fragmented draft genome assembly.
What is best:
1. take each sample and create a list of targets, followed by realignment on each sample.
2. combine all samples into one large bam file and create a list of targets, followed by realignment on the same large bam file.
Also, would there be any advantages in terms of speed with either approach?
Cheers,
Steve
I've the following queries on running RealignerTargetCreator module in GATK1.4.
1) Is it recommended to provide the target capture BED file to RealignerTargetCreator in case of targeted/exome experiments? Without the bed file, the tool is taking long time (~6-7 hrs). What's the optimal way here?
2) Does running mark duplicates before or after 'RealignerTargetCreator' have any effect on the # of snps/indels? What is recommended?
Look forward to your comments. Raj
Hi there,
I get an error when I try to run GATK with the following command:
java -jar GenomeAnalysisTK-2.3-9-ge5ebf34/GenomeAnalysisTK.jar -T RealignerTargetCreator -R reference.fa -I merged_bam_files_indexed_markduplicate.bam -o reads.intervals
However I get this error:
SAM/BAM file SAMFileReader{/merged_bam_files_indexed_markduplicate.bam} is malformed: Read HWI-ST303_0093:5:5:13416:34802#0 is either missing the read group or its read group is not defined in the BAM header, both of which are required by the GATK. Please use http://gatkforums.broadinstitute.org/discussion/59/companion-utilities-replacereadgroups to fix this problem
It suggest that it a header issue however my bam file has a header:
samtools view -h merged_bam_files_indexed_markduplicate.bam | grep ^@RG
@RG ID:test1 PL:Illumina PU:HWI-ST303 LB:test PI:75 SM:test CN:japan
@RG ID:test2 PL:Illumina PU:HWI-ST303 LB:test PI:75 SM:test CN:japan
when I grep the read within the error:
HWI-ST303_0093:5:5:13416:34802#0 99 1 1090 29 23S60M17S = 1150 160 TGTTTGGGTTGAAGATTGATACTGGAAGAAGATTAGAATTGTAGAAAGGGGAAAACGATGTTAGAAAGTTAATACGGCTTACTCCAGATCCTTGGATCTC GGGGGGGGGGGGFGGGGGGGGGGGGGGGGGGGGGGGGGGGGEGFGGGGGGGGGDGFGFGGGGGFEDFGEGGGDGEG?FGGDDGFFDGGEDDFFFFEDG?E MD:Z:60 PG:Z:MarkDuplicates RG:Z:test1 XG:i:0 AM:i:29 NM:i:0 SM:i:29 XM:i:0 XO:i:0 XT:A:M
Following Picard solution:
java -XX:MaxDirectMemorySize=4G -jar picard-tools-1.85/AddOrReplaceReadGroups.jar I= test.bam O= test.header.bam SORT_ORDER=coordinate RGID=test RGLB=test RGPL=Illumina RGSM=test/ RGPU=HWI-ST303 RGCN=japan CREATE_INDEX=True
I get this error after 2 min.:
Exception in thread "main" net.sf.samtools.SAMFormatException: SAM validation error: ERROR: Record 12247781, Read name HWI-ST303_0093:5:26:10129:50409#0, MAPQ should be 0 for unmapped read.`
Any recommendation on how to solve this issue ?
My plan is to do the following to resolve the issue:
picard/MarkDuplicates.jar I=test.bam O=test_markduplicate.bam M=test.matrix AS=true VALIDATION_STRINGENCY=LENIANT
samtools index test_markduplicate.bam
I see a lot of messages like below but the command still running:
Ignoring SAM validation error: ERROR: Record (number), Read name HWI-ST303_0093:5:5:13416:34802#0, RG ID on SAMRecord not found in header: test1
while running the command
then try the GATK RealignerTargetCreator
I already tried to do the following
java -jar GenomeAnalysisTK-2.3-9-ge5ebf34/GenomeAnalysisTK.jar -T RealignerTargetCreator -R reference.fa -I merged_bam_files_indexed_markduplicate.bam -o reads.intervals --validation_strictness LENIENT
But I still got the same error
N.B: the same command run with no issue with GATK version (1.2)
My pipeline in short: mapping the paired end reads with
bwa aln -q 20 ref.fa read > files.sai
bwa sampe ref.fa file1.sai file2.sai read1 read2 > test1.sam
samtools view -bS test1.sam | samtools sort - test
samtools index test1.bam
samtools merge -rh RG.txt test test1.bam test2.bam
RG.txt
@RG ID:test1 PL:Illumina PU:HWI-ST303 LB:test PI:75 SM:test CN:japan
@RG ID:test2 PL:Illumina PU:HWI-ST303 LB:test PI:75 SM:test CN:japan
samtools index test.bam
picard/MarkDuplicates.jar I=test.bam O=test_markduplicate.bam M=test.matrix AS=true VALIDATION_STRINGENCY=SILENT
samtools index test_markduplicate.bam
HI
I am using the following set of commands on GATK2.1.13 to generate a VCF file
echo `java -Xmx20g -jar /usr/bin/GenomeAnalysisTK.jar -I B2_with_ReadGroup.ddup.sorted.bam -R human_g1k_v37.fasta -T RealignerTargetCreator -o my.intervals -et NO_ET -K /root/sandbox/saket.kumar_iitb.ac.in.key`
echo "Realignment Done at `date`"
echo "Starting IndelRealigner at `date`"
echo `java -Xmx20g -jar /usr/bin/GenomeAnalysisTK.jar -I B2_with_ReadGroup.ddup.sorted.bam -R human_g1k_v37.fasta -T IndelRealigner -targetIntervals my.intervals -o myrealignedBam.bam -et NO_ET -K /root/sandbox/saket.kumar_iitb.ac.in.key`
echo "Realignment done at `date`"
echo "Starting UnifiedGenotyper at `date`"
echo `java -Xmx20g -jar /usr/bin/GenomeAnalysisTK.jar -l INFO -R human_g1k_v37.fasta -T UnifiedGenotyper -I myrealignedBam.bam -o mygatk_vcf.vcf --output_mode EMIT_ALL_SITES -et NO_ET -K /root/sandbox/saket.kumar_iitb.ac.in.key`
echo "Gentoypxing complete at `date`"
When i do a 'mpileup' for B2_with_ReadGroup.ddup.sorted.bam , I get a devcent 10 MB VCF file. But on the last ste of the above pipeline, my " mygatk_vcf.vcf " is goinging into 81GBs !!
Do you know what is wrong ?
Hello,
I am having trouble calling variants using Haplotype Caller on simulated exome reads. I have been able to call reasonable-looking variants on the exome (simulated with dwgsim) with HaplotypeCaller before running it through the Best Practices Pre-Processing pipeline. The pre-processed data worked fine with UnifiedGenotyper but with HaplotypeCaller, though it runs without errors and seems to walk across the genome, only outputs a VCF header. I have tried calling variants with and without using -L to provide the exome regions (as recommended in this forum post: http://gatkforums.broadinstitute.org/discussion/1681/expected-file-size-haplotype-caller) but this hasn't made a difference - when we run the command with the pre-processed BAMs, we only get a VCF header. Everything has been tested with both 2.4-7 and 2.4-9.
Any help or guidance would be greatly appreciated!
Command Used for HaplotypeCaller:
java -Xmx4g -jar GenomeAnalysisTK.jar -T HaplotypeCaller -R ucsc.hg19.fasta -I exome.realigned.dedup.recal.bam -o exome.raw.vcf -D dbsnp_137.hg19.vcf -stand_emit_conf 10 -rf BadCigar -L Illumin_TruSeq.bed --logging_level DEBUG
Commands Used for pre-processing (run in sequence using a Perl script):
java -Xmx16g -jar GenomeAnalysisTK.jar -T RealignerTargetCreator -nt 8 -R ucsc.hg19.fasta -I exome.bam -o exome.intervals -known dbsnp_137.hg19.vcf
java -Xmx4g -jar GenomeAnalysisTK.jar -T IndelRealigner -R ucsc.hg19.fasta -I exome.bam -o exome.realigned.bam -targetIntervals intervals.bam -known dbsnp_137.hg19.vcf
java -Xmx16g -jar MarkDuplicates.jar I=exome.realigned.bam METRICS_FILE=exome.dups O=exome.realigned.dedup.bam
samtools index exome.realigned.dedup
java -Xmx4g -jar GenomeAnalysisTK.jar -T BaseRecalibrator -nct 8 -R ucsc.hg19.fasta -I exome.realigned.dedup.bam -o exome.recal_data.grp -knownSites dbsnp_137.hg19.vcf -cov ReadGroupCovariate -cov ContextCovariate -cov CycleCovariate -cov QualityScoreCovariate
java -Xmx4g -jar GenomeAnalysisTK.jar -T PrintReads -nct 8 -R ucsc.hg19.fasta -I exome.realigned.dedup.bam -BQSR exome.recal_data.grp -baq CALCULATE_AS_NECESSARY -o exome.realigned.dedup.recal.bam
Hi all - I'm using GATK realigner which can take several hours on my samples. I'm trying to optimize my pipeline by dividing this up by chromosome for each node in my cluster. I can call RealignerTargetCreator using the -L parameter for each chromosome which results in a bunch of interval files. Now, I either want to call IndelRealigner using the -L parameter for each chromsome then merge the resulting BAM files, or merge the interval files into one then call IndelRealigner.
1) I don't see a way to merge interval files using GATK. Is this possible?
or
2) Can I call IndelRealigner and process each chromosome separately then merge the resulting BAM files together?
I can't seem to run the IndelRealigner on reads that contain colons, ":" in the reference scaffold names. The RealignerTargetCreator step works correctly and generates the interval table, but the second, IndelRealigner, step fails. When I look at the generated interval table, I see the interval delimiter is a colon, which I imagine is the problem.
Unfortunately, I have a set of human references that have a colon in every scaffold name, so changing this would be a massive undertaking.
I believe this problem could be solved if you searched for the colon delimiter from the end of the interval string instead of from the beginning, so I'm hoping this a real simple fix.
Thanks!
Hi,
I have downloaded newest version of GATK (version 2.4-3) this week and tried to perform local realignment for my targeted sequencing data. Reference genome, SNP and indel data files were downloaded from resource bundle. However, I encountered two issues when I was doing the realignment.
First, in the step of RealignerTargetCreator. With the same command line, if I run it under version 2.4-3, I got an error message "MESSAGE: -49" (no other detail information provided); if I run it under an older version 2.3-9, it ran very well with no errors.
Second, in the step of IndelRealigner. I got error message "MESSAGE: Bad input: We encountered a non-standard non-IUPAC base in the provided reference: '13'". However, reference genome was downloaded from the bundle. I am not sure how to fix this issue.
I hope someone can help me with these issues. Let me know if more info is needed.
Thanks!
Hi, I got errors when ran GATK RealignerTargetCreator and IndelRealigner in v2.4.9. I've checked many related discussions and comments. First, I got an error like "we encountered an extremely high quality score of 69" with option -S LENIENT and the GATK program stalled. So I added "--fix_misencoded_quality_scores", and then I got different error message "ERROR MESSAGE: Bad input: We encountered a non-standard non-IUPAC base in the provided reference: '0'" now. I tried older versions of GATK and both java 1.6 and 1.7. I'm hoping that you can help this. Please let me know if I'm missing something. Thanks!
--Giltae
Hello,
I am using Realigner target creator of GATK toolbox but it keeps on giving me this error:
How could I solve this problem.
Thanks a lot in advance.
Hello,
I try to run the realigner target creator with the data divided on chromosomes. It seems to run smooth but the runtime for chromosome 1 seems to never end. I have checked my bam files and as expected the one with chr 1 is a little bit bigger than chr 2 but nothing proportional to the differences in predicted runtime. The version i use is GATK 2.3.0 and this is how i run it:
java -Xmx12g -jar programs/GenomeAnalysisTK-2.3-0/GenomeAnalysisTK.jar -l INFO -T VariantRecalibrator -R Homo_sapiens.GRCh37.57_dna_concat.fa -recalFile allchr_varrecal_BOTH_comb_ref.intervals -rscriptFile 15_allchr_varrecal_BOTH_comb_ref.intervals.plots.R -tranchesFile allchr_varrecal_BOTH_comb_ref.intervals.tranches -resource:hapmap,VCF,known=false,training=true,truth=true,prior=15.0 hapmap_3.3.b37.sites.vcf -resource:omni,VCF,known=false,training=true,truth=false,prior=12.0 1000G_omni2.5.b37.sites.vcf -resource:dbsnp,VCF,known=true,training=false,truth=false,prior=8.0 dbsnp_135.b37.vcf -resource:mills,VCF,known=true,training=true,truth=true,prior=12.0 Mills_and_1000G_gold_standard.indels.hg19.sites.vcf -an QD -an HaplotypeScore -an MQRankSum -an ReadPosRankSum -an FS -an MQ --mode BOTH -nt 8 -input allchr_real_recal_resrt_raw_BOTH_comb_ref.vcf -L Agilent_SureSelect.V4.GRCh37.70_targets_nochr.bed.pad100.interval_list --pedigreeValidationType SILENT --pedigree my_fam.fam
predicted runtime looks like:
INFO 15:11:33,778 ProgressMeter - 1:33587200 3.36e+07 2.3 h 4.1 m 1.1% 8.8 d 8.7 d INFO 15:11:33,778 ProgressMeter - 11:73495886 1.82e+09 2.3 h 4.5 s 61.0% 3.7 h 87.4 m INFO 15:11:33,778 ProgressMeter - 10:6623707 1.68e+09 2.3 h 4.9 s 54.5% 4.2 h 114.3 m INFO 15:11:33,778 ProgressMeter - 11:572298 1.82e+09 2.3 h 4.5 s 58.7% 3.9 h 96.4 m INFO 15:11:33,779 ProgressMeter - 11:122078003 1.82e+09 2.3 h 4.5 s 62.6% 3.6 h 81.7 m INFO 15:11:53,780 ProgressMeter - 11:10589211 1.82e+09 2.3 h 4.5 s 59.0% 3.9 h 95.3 m INFO 15:11:53,780 ProgressMeter - 11:105031869 1.82e+09 2.3 h 4.5 s 62.1% 3.7 h 83.9 m INFO 15:11:53,781 ProgressMeter - 11:46994477 1.82e+09 2.3 h 4.5 s 60.2% 3.8 h 90.8 m INFO 15:12:03,779 ProgressMeter - 11:8677862 1.82e+09 2.3 h 4.5 s 58.9% 3.9 h 95.7 m INFO 15:12:03,779 ProgressMeter - 11:130690257 1.82e+09 2.3 h 4.5 s 62.9% 3.6 h 81.1 m INFO 15:12:13,779 ProgressMeter - 11:84816026 1.82e+09 2.3 h 4.5 s 61.4% 3.7 h 86.4 m INFO 15:12:13,779 ProgressMeter - 10:17039143 1.68e+09 2.3 h 4.9 s 54.8% 4.2 h 113.3 m INFO 15:12:23,780 ProgressMeter - 11:18556991 1.82e+09 2.3 h 4.5 s 59.3% 3.9 h 94.6 m INFO 15:12:23,780 ProgressMeter - 11:113365440 1.82e+09 2.3 h 4.5 s 62.3% 3.7 h 83.2 m INFO 15:12:23,782 ProgressMeter - 11:55284794 1.82e+09 2.3 h 4.5 s 60.4% 3.8 h 90.1 m INFO 15:12:33,780 ProgressMeter - 1:33783808 3.38e+07 2.3 h 4.1 m 1.1% 8.8 d 8.7 d INFO 15:12:33,780 ProgressMeter - 12:3311608 1.95e+09 2.3 h 4.2 s 63.1% 3.6 h 80.5 m INFO 15:12:43,779 ProgressMeter - 11:93292307 1.82e+09 2.3 h 4.6 s 61.7% 3.7 h 85.8 m INFO 15:12:43,780 ProgressMeter - 10:24841443 1.68e+09 2.3 h 4.9 s 55.1% 4.2 h 112.5 m INFO 15:12:43,780 ProgressMeter - 11:19408689 1.82e+09 2.3 h 4.6 s 59.3% 3.9 h 94.8 m INFO 15:12:53,965 ProgressMeter - 11:26512308 1.82e+09 2.3 h 4.6 s 59.5% 3.9 h 94.0 m INFO 15:12:53,965 ProgressMeter - 11:121738354 1.82e+09 2.3 h 4.6 s 62.6% 3.7 h 82.6 m INFO 15:12:53,965 ProgressMeter - 11:63468191 1.82e+09 2.3 h 4.6 s 60.7% 3.8 h 89.4 m INFO 15:13:03,781 ProgressMeter - 12:11960820 1.95e+09 2.3 h 4.3 s 63.4% 3.6 h 79.8 m INFO 15:13:13,780 ProgressMeter - 11:101551879 1.82e+09 2.3 h 4.6 s 61.9% 3.7 h 85.1 m INFO 15:13:13,780 ProgressMeter - 10:32238974 1.68e+09 2.3 h 4.9 s 55.3% 4.2 h 111.8 m INFO 15:13:13,780 ProgressMeter - 11:27204534 1.82e+09 2.3 h 4.6 s 59.5% 3.9 h 94.1 m INFO 15:13:23,966 ProgressMeter - 11:71529440 1.82e+09 2.3 h 4.6 s 61.0% 3.8 h 88.8 m INFO 15:13:23,968 ProgressMeter - 11:34170083 1.82e+09 2.3 h 4.6 s 59.8% 3.9 h 93.4 m INFO 15:13:23,977 ProgressMeter - 11:129889715 1.82e+09 2.3 h 4.6 s 62.9% 3.7 h 81.9 m INFO 15:13:33,781 ProgressMeter - 1:33980416 3.40e+07 2.3 h 4.1 m 1.1% 8.8 d 8.7 d
Any suggestions?
Regards,
Måns
Hi all,
We're doing some analysis on quite big data and time is an issue, so I did a bit of scaling testing on a subset of the data before beginning. The results were unexpected.
When I run GATK RealignerTargetCreator with -nt 8 and give it 8 cores to work with, it actually takes about 2.5 times LONGER than if I just run it single-threaded. I don't mean that the user or CPU time goes up - the real, walltime goes up. In the -nt 8 case, the 8 cores would have been on a single node of our cluster with shared memory.
I tried testing on two different kinds of subsets of the data and both performed worse when multithreaded. I first tried restricting the input data by genomic region, ie just analysing chr22. When multithreading didn't seem to be working as expected in this test, I thought that maybe GATK was trying to parallelise over genomic regions, so I instead tried testing on a single lane of input data (a 9.6G bam file spread over the whole genome). This also ran more slowly when multithreaded.
So my question is: should I use -nt 8 in my real analysis even though it was a bad option in testing? Is it possible that multithreading will be bad for small amounts of data, but good in the large-data case? Or, does this indicate that I'm doing something wrong when trying to run RealignerTargetCreator multithreaded?
I really would like to use the fastest option for the real data as it will be very big. Any help much appreciated.
Thanks, Clare
java -jar GenomeAnalysisTK.jar -R exampleFASTA.fasta -I exampleBAM.bam -T RealignerTargetCreator -o exampleTarget.intervals
I used the example files, and I got no error report, but in the output, there is no data, that is to say. The exampleTarget.intervals is empty.
Why is this happening?
And when I add --known dbsnp_135.hg19.vcf( that is in the bundle), it will get an error
Hi,
I want to run RealignerTargetCreator with this command line :
qsub -b Y -N RTC -q bigmem.q "/usr/local/java/latest/bin/java -Xmx36g -jar /home/sabotf/sources/GenomeAnalysisTK/GenomeAnalysisTK.jar -T RealignerTargetCreator -R /data/projects/assembling-glab/PacBio_test/XL/filtered_subreads_XL.fasta -o /data/projects/assembling-glab/mappingResults/Tog5681Clean_vs_CG14_XL/output.intervals -I /data/projects/assembling-glab/mappingResults/Tog5681Clean_vs_CG14_XL/rmdup.bam"
but this return this error :
`##### ERROR ------------------------------------------------------------------------------------------
I tried with -Xmx4g, then,-Xmx12g, then -Xmx48g, and always the same error. I don't know what to do ... any idea ? thanks
Hi,
I am currently working with a project where we have sequenced a library of approximately 70 bps insert sizes using 2x100 paired-end seq. While this can seem unnecessary, it can improve base qualities a lot.
I have used SeqPrep (https://github.com/jstjohn/SeqPrep) which strips adaptors and merges reads that overlap, in our case the entire read most of the times. This also boosts the base qualities, if a base was sequenced twice, the quality improves quite a bit. This way, base qualities can stretch up to 70 and over (probability of error 0.0001 x 0.0001 if both reads had Q40 at that base, it merged qual = 80). No funny business there. :)
However, this does not seem to play nicely with GATK. The realignment crashes (see below) saying the the base quals must be erroneous. In my case, but they are correct. Can I force GATK to work with these BQs? (--validation_strictness LENIENT didn't help as you can see below :)
cheers Daniel Klevebring
INFO 13:04:07,408 HelpFormatter - --------------------------------------------------------------------------------
INFO 13:04:07,411 HelpFormatter - The Genome Analysis Toolkit (GATK) v2.4-7-g5e89f01, Compiled 2013/03/06 01:01:28
INFO 13:04:07,411 HelpFormatter - Copyright (c) 2010 The Broad Institute
INFO 13:04:07,411 HelpFormatter - For support and documentation go to http://www.broadinstitute.org/gatk
INFO 13:04:07,416 HelpFormatter - Program Args: -T RealignerTargetCreator -I /scratch/3041404/P394_102.prmdup.bam -R /bubo/proj/b2010040/private/GoldenPath/hg19/GATK_resource_bundle/human_g1k_v37_clean.fasta -o /scratch/3041404/P394_102.realn.intervals --intervals /bubo/proj/b2010040/private/GoldenPath/NG_design/1000G_REF_picard_custom_design_target_regions_HG19.bed.interval_list --validation_strictness LENIENT
INFO 13:04:07,416 HelpFormatter - Date/Time: 2013/03/13 13:04:07
INFO 13:04:07,416 HelpFormatter - --------------------------------------------------------------------------------
INFO 13:04:07,416 HelpFormatter - --------------------------------------------------------------------------------
INFO 13:04:08,461 GenomeAnalysisEngine - Strictness is LENIENT
INFO 13:04:08,632 GenomeAnalysisEngine - Downsampling Settings: Method: BY_SAMPLE, Target Coverage: 1000
INFO 13:04:08,640 SAMDataSource$SAMReaders - Initializing SAMRecords in serial
INFO 13:04:08,655 SAMDataSource$SAMReaders - Done initializing BAM readers: total time 0.01
INFO 13:04:09,782 IntervalUtils - Processing 39772003 bp from intervals
INFO 13:04:10,001 GenomeAnalysisEngine - Creating shard strategy for 1 BAM files
INFO 13:04:10,262 GenomeAnalysisEngine - Done creating shard strategy
INFO 13:04:10,262 ProgressMeter - [INITIALIZATION COMPLETE; STARTING PROCESSING]
INFO 13:04:10,263 ProgressMeter - Location processed.sites runtime per.1M.sites completed total.runtime remaining
INFO 13:04:18,482 GATKRunReport - Uploaded run statistics report to AWS S3
##### ERROR ------------------------------------------------------------------------------------------
##### ERROR A USER ERROR has occurred (version 2.4-7-g5e89f01):
##### ERROR The invalid arguments or inputs must be corrected before the GATK can proceed
##### ERROR Please do not post this error to the GATK forum
##### ERROR
##### ERROR See the documentation (rerun with -h) for this tool to view allowable command-line arguments.
##### ERROR Visit our website and forum for extensive documentation and answers to
##### ERROR commonly asked questions http://www.broadinstitute.org/gatk
##### ERROR
##### ERROR MESSAGE: SAM/BAM file SAMFileReader{/scratch/3041404/P394_102.prmdup.bam} appears to be using the wrong encoding for quality scores: we encountered an extremely high quality score of 70; please see the GATK --help documentation for options related to this error
##### ERROR ------------------------------------------------------------------------------------------
Hello,
before I only used BWA and as you described in the best pratice I performed the realign step. Now I want to integrate in my pipeline Stampy associated with BWA.
Do you think, I should make the realign step ?
Thanks !