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# rules for max_alternate_alleles in HaplotypeCaller

Warsaw, PolandMember Posts: 8
edited December 2013

Hi,

I can't come to any clear conclusion how this parameter works. Help me, please. I worked on the same files with exact command but the max_alternate_alleles. In first command I put 1 for its arguments
(--max_alternate_alleles 1) and 2 in second. Output was different by number of 600 SNVs,

a) There are sites on which haplotype caller for second command changed SNV on the one with better scores than in first command.
eg.
CSB10A_v1_contig_682 232 ref.: G first: GT(90.75) second: GTT ( 135.73). Scores in brackets.

b) There are sites where unlike first command, second command didn't give any SNVs, because there was no mapped reads

c) This is not sure, because I can't track back what I think I saw: the opposite to a) - scores from second command were worse than those from first.

Could you explain me why?

Paul

Tagged:

• Warsaw, PolandMember Posts: 8

a) went messy after approval: ref.: G first: GT(90.75) second: GTT ( 135.73). Scores in brackets off course.

Hi Paul,

This argument sets a limit on the number of alternate alleles that the HaplotypeCaller will consider when evaluating haplotypes. If it sees more possibilities in the data than are allowed by this argument, it will proceed with the most likely and discard the rest. The effects on number of variant calls are not easy to predict since it changes the decisions that the caller has to make depending on the data.

Geraldine Van der Auwera, PhD

• Warsaw, PolandMember Posts: 8
edited December 2013

Geraldine,

Thank you for your answer. Do you think it's worth to change that argument to 1 in order to align reads of haploid genomes and call variants? Can it be beneficial in any way? When I add the argument with value 1 I get more possible variants from the caller than without one. I guess due to the constraints I putted caller doesn't treat some variant regions as one module, splits them and realign separately. That's how I get more variants from it. Like in this case:

with changed argument to 1:

CSB10A_v1_contig_10002  3405    .       C       CT      529.73  .       AC=2;AF=1.00;AN=2;DP=19;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=35.25;MQ0=0;QD=27.88     GT:AD:DP:GQ:PL  1/1:0,17:17:51:567,51,0
CSB10A_v1_contig_10002  3411    .       G       GTT     80.94   .       AC=2;AF=1.00;AN=2;DP=20;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=33.02;MQ0=0;QD=2.02      GT:AD:DP:GQ:PL  1/1:3,10:13:13:118,13,0
CSB10A_v1_contig_10002  3427    .       GT      G       481.73  .       AC=2;AF=1.00;AN=2;DP=17;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=34.27;MQ0=0;QD=28.34     GT:AD:DP:GQ:PL  1/1:0,15:15:45:519,45,0

without change:

CSB10A_v1_contig_10002  3405    .       C       CT      529.73  .       AC=2;AF=1.00;AN=2;DP=19;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=35.25;MQ0=0;QD=27.88     GT:AD:DP:GQ:PL  1/1:0,17:17:51:567,51,0
CSB10A_v1_contig_10002  3427    .       GT      G       481.73  .       AC=2;AF=1.00;AN=2;DP=17;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=34.27;MQ0=0;QD=28.34     GT:AD:DP:GQ:PL  1/1:0,15:15:45:519,45,0

Regards,
Paul

• Member Posts: 59

What would be a good argument for --max_alternate_alleles argument. I suppose it will vary in different organisms. What should be a good value to be set in the max alleles argument the current default is six in my case. I am running the analysis on soybean.

@smk_84‌

Hi,

You are free to experiment with this! You can run it with the default settings, and then try rerunning with the maximum alternate alleles you find from the default (the output will tell you when there are more than the default alleles).

This parameter is related to the size of the cohort (how many different samples are being analyzed together) and to how diverse you expect the population to be. It really depends on how diverse you expect your population to be. If they are all from the same family, you expect them to be closely related, but if they are all strangers, they may not be so closely related.

Good luck!

-Sheila

• Member Posts: 12

Hi,
Could you tell me if the default 6 is based on human and cohorts of maybe 1000? I deal with many different experiments, all non-human with different cohort sizes and relatedness, so will need to play with this quite a bit I think.

@jam

Hi,

The number 6 is indeed based on human cohorts, probably from the 1000 Genomes project. It is meant as a reasonable compromise between computing requirements and what is likely to occur in populations.

For larger cohort sizes, it should probably be increased. I am not sure about non-human though. You will need to adapt it to what you see in your data. The best thing to do is to play around with it, as you correctly assume.

-Sheila

• Member Posts: 13
edited September 2014

Hi,

I'm considering this parameter for some non-human data with ~1000 samples. I'm running the pipeline with HaplotypeCaller on each single individual to produce .gvcf files and then GenotypeGVCFs on all the samples together. What I'd like to know is if I'm running HaplotypeCaller on one diploid individual, whether it is reasonable to set the max_alternate_alleles to 1? This makes sense biologically because there are only two alleles total but I'm not sure how the algorithm works exactly.

Thanks!

@Greg_Owens‌

Hi,

When running Haplotype Caller, the samples are compared to the reference. For diploid samples, there is a possibility that the sample may be heterozygous for two different alleles than the reference. For example, if the reference is A, and the sample is T/C, setting max_alternate_alleles to 1 will only return either T or C as an alternate allele (whichever allele is more likely). So, you will miss an important second alternate allele.

When working with 1000 samples, setting max_alternate_alleles to a higher number also allows you to include variants that are not seen in large quantities in one individual sample. But, if the variant is seen in smaller quantities in many samples, the variant is more likely to be a true variant.

I hope this helps.

-Sheila

• Member Posts: 13

Thanks Sheila. I went with max alternate alleles = 2 for the Haplotype Caller (which is being run on individual samples) for the reasons you talked about. For the GenotypeGVCFs, I'm going to use max_alternate_alleles = 3 because I'm not going to use the indels and SNPs can only be four states.

• Member Posts: 79
edited August 24

Hi,
For 50 human whole exome samples what value do you suggest for max_alternate_alleles parameter in GenotypeGVCFs? For your information while using haplotypecaller to generate GVCF for individual samples I did not change this parameter and it ran with the default value 6. Here my purpose is to generate a generic in-house database with allele frequency for use in variant annotation.

Post edited by aneek on

@aneek
Hi,

We don't really have any recommendations for how many alternate alleles you should accept. The default is 6 in HaplotypeCaller, but it is up to you to decide what you are interested in. As you have seen, there is a warning that tells you when there are more alternate alleles at a site than the default 6. If you wish to include those extra alternate alleles, you should change the default settings.

-Sheila

• Member Posts: 79

@ Sheila

Hi,

Thank you very much for the explanation. As you said, I repeatedly tried with different values of --max_alternate_alleles parameter until I receive no warning message while performing the GenotypeGVCFs step and I have discovered maximum number of alternate allele 38 in one specific location. Therefore at last I ran the program with --max_alternate_alleles value 40 and it completed the task without any warning, means max number achieved hopefully.

Although I did not see any computational problems and the program ran smoothly, however, I am fearing, using such high --max_alternate_alleles value is ok for only 50 whole exome samples. Please advice.

Another query is, since in HaplotypeCaller step for generating individual g.vcfs I did not change this parameter from default, is it wise to change this parameter in GenotypeGVCFs step, so also in such high value (40)?

In one sentence I just want to be sure that I not doing anything wrong which may finally end up in a database file with wrong alternate allele frequencies.

Thanks.

#### Issue · Github August 25 by Sheila

Issue Number
1205
State
closed
Last Updated
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Array
Milestone
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vdauwera
• Member Posts: 79

@aneek, we do not provide guidance for this because it is entirely up to you as an analyst to decide what is appropriate for your study. In some case it may be meaningful to capture all possible alternate alleles observed at a particular locus, especially if you have reason to believe that the polymorphism observed there holds some biological significance. However, in other cases the presence of very many alternate alleles just indicates technical difficulties in the sequencing process and is not useful (seeing 38 alleles in 50 samples seems like it might fall under that category). The development team has been working on methods to applying allele-specific filtering, which may prove useful for distinguishing such cases, but this is not yet ready for wide use. In the meantime you need to decide what you are willing to include in your analysis.

Geraldine Van der Auwera, PhD

• Member Posts: 79

@Geraldine_VdAuwera

Hi, thanks a lot. I understood. In my case it might be the technical error since I am getting 38 alleles in a particular locus. However even for that if I set the --max_alternate_alleles value to 40 and proceed for the analysis, do you think it can affect the final output of the file (alternate allele frequencies etc.).

Also is there any way (commandline etc.) to detect how many loci are having such high number of alternate alleles in the samples.

Thanks..

@aneek
Hi,

No, there is no argument. You will need to to look at the WARN statements that are output.

-Sheila