A question about genetic map #90
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Hello,
Well you have a few options. You could interpolate genetic map distances
for sites in between the locations that you have information at. You could
use the —pmap flag, which will use physical distances in bp instead of a
genetic map. You could also use the nSL statistic, which is very similar to
iHS but does not need a genetic map.
Hope this helps,
Zachary
Le lun. 9 janv. 2023 à 6:55 AM, Pam ***@***.***> a écrit :
… Hi szpiech，
Thank you for your tool. I have a question about it.
The map file is needed in the calculation of iHS. The genetic position of
the rsID is required in the map file, but the SHAPEIT has only a small
fraction of the loci of the genetic map for 1000 Genome. However, selscan
needs the genetic distance of all region rsIDs when calculating iHS, i.e.,
one genetic position per rsID. Can I use physical position/1e6 instead of
genetic position? Will this cause a large estimation error?
I look forward to hearing from you!
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Hello, |
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Hello,
Yes you can use predictGMAP for linear interpolation. Pay attention to the
max gap parameter in that program (you may just want to set it very large).
I would expect that using physical distances would lead to larger scores in
regions of low recombination, to some extent this still happens when a
genetic map is included, but it may exacerbate.
…-Zachary
Le lun. 9 janv. 2023 à 8:22 AM, Pam ***@***.***> a écrit :
Hello,
Thank you for your reply. Linear interpolation by distance? Or use
predictGMAP? Perhaps using --PMAP is the most straightforward. Do these
methods have a great impact on the results?
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Hi, |
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Well, if you have the genetic map, I'd probably go with doing the
interpolation. Selscan can take tped files and vcf files too, just no
missing data, if that helps your planning.
…-Zachary
On Mon, Jan 9, 2023 at 9:21 AM Pam ***@***.***> wrote:
Hi,
Thank you for your reply.
1）Which of these do you recommend?
2）I probably figured out how to run it. selscan should have to use
genotype data, I currently have plink data of 2000 individuals, then I need
to convert the plink file to .hap format using ShapIT, then make the map
file (depending on whether genetic position or physical position is used),
and finally I can run selscan. Great！
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Hi， |
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Hello,
I don't fully understand your questions. For 1, it sounds like you are
doing GWAS in one set of data, and then you would like to calculate iHS
using different data (TGP) to look at scores in significant GWAS regions?
Yes you can do this, but for what purpose? For 2, I don't understand what
you are asking.
Best,
Zachary
…On Tue, Jan 10, 2023 at 1:30 AM Pam ***@***.***> wrote:
Hi，
Thank you for your advice. There is an interesting question
1）After the significant loci obtained by GWAS, can I use 1000 Genome as
input file for --hap and --map to calculate iHS without using my own
genotype?
2) Similarly, when comparing XP-EHH between two groups again, my data VS
1000G (EUR) or 1000G (EAS) vs 1000G (EUR) is still confusing. This may not
be related to the phenotype, but rather the need to use the genotype of the
reference population to be able to calculate iHS, XP-EHH.
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Hi,
Have a nice day. |
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Hello,
Okay, for your GWAS question, I think you may be best served by finding the
matching TGP population (if it exists) for your study and looking at scores
in the regions that are hits in your GWAS data. I say this because your
GWAS data are likely NOT a random sample of the population, and therefore
your haplotype patterns may be biased in unexpected ways.
Regarding your other questions, yes you may want to increase max gap in
predictGMAP (sometimes I just set it to 3000000000) so that you get
interpolated distances at each site. Regarding 2, --hap is for passing
genetic data in a very simple .hap format, this format is described in the
manual. Alternatively you can use --tped or --vcf to let selscan use those
data formats instead. If you are using a two-population statistic like
XP-EHH, you will need to pass one population file with the flag --hap (or
--tped or --vcf) and the second population file with --hap-ref (or
--tped-ref or --vcf-ref). I may be wrong but I think there is a version of
shapeit that now outputs vcf files.
…-Zachary
On Tue, Jan 10, 2023 at 11:36 AM Pam ***@***.***> wrote:
Hi,
Thank you for your time. Sorry maybe I didn't say myself clearly. Let me
summarize my questions.
I have a genotype data of more than 2000+ individuals and through GWAS I
get some significant locus. My aims are to test if these regions are
subject to positive selection using selscan or to perform a genome-wide
scan to find some positive selection locus.
Following your suggestion, I downloaded the 1000 Genome genetic map file
to be used as a reference map file for predictGMAP to get my map file.
1. max gap parameter will lose some loci, do we need to increase the
gap?
2. I am confused about the --hap parameter of selscan, do I need to
extract the haplotype from my data using shapeit or just use the hap data
provided by 1000 Genome? Similarly, when comparing the difference between
populations (EAS vs EUR) using XP-EHH.
Have a nice day.
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Hi， |
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Hi， |
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Hello,
This information can be found in the vcf files at
http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/ in the INFO
field with the AA tag.
…-Zachary
On Tue, Feb 14, 2023 at 6:49 AM Pam ***@***.***> wrote:
Hi，
Thank you for your tool. I am going to calculate the background
distribution of iHS for 1000G, but how can I determine whether the allele
is an ancestral allele or a derived allele. I didn't find a better way.
I look forward to hearing from you!
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Hi, |
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Hello,
In the end the choice is up to you. Polarizing the ones you do have
information for is certainly a good idea, whether you choose to filter the
others is a more subtle choice. I would be surprised if it made a huge
difference either way, but I might be mistaken.
…-Zachary
Le mar. 21 févr. 2023 à 8:45 AM, Pam ***@***.***> a écrit :
Hi,
Thank you for your reply.This solved my problem.
I have found the AA (ancestral allele) in this files, and considering that
the iHS calculation does not support INDEL, I removed INDEL, there are SNPs
with AA of . or null, or unknown, should these SNPs be removed, because
they will bring unreliability in the calculation, so they are not involved
in the calculation of iHS? But I also found that many SNP's REF allele
could be AA, and I'm torn again whether I should delete it here.
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Hi,
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Hello,
Yes when you normalize with norm, just give all the chromosome files at
once for joint normalization.
…-Zachary
On Wed, Feb 22, 2023 at 10:05 PM Pam ***@***.***> wrote:
Hi,
Thank you for your reply. You are right. I checked these SNPs for which AA
was not provided, and most of them were low frequency . Therefore, this may
not be an issue for most GWAS requiring a threshold of MAF 0.01.
1.
Regarding AA, the information of 1000 GP may be too old, and some
researchers started to reacquire AA starting from the comparison of
near-origin species, for example, the sequence comparison of more than 10
kinds of chimpanzees. But this will take a lot of time for sequence
alignment. If I have time, I would like to try to compare more species to
get AA.
2.
The new version of selscan, which can use unphased haplotype solves a
big problem. Overall, phased haplotype is a bit more accurate.
3.
I found the norm program that doesn't require me to standardize iHS
myself. Great! Across genome-wide iHS normalization (frequency bins), this
should be considered for all chromosomes, do I need --files followed by all
chromosome iHS results for joint normalization?
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Hi szpiech，
Thank you for your tool. I have a question about it.
The map file is needed in the calculation of iHS. The genetic position of the rsID is required in the map file, but the SHAPEIT has only a small fraction of the loci of the genetic map for 1000 Genome. However, selscan needs the genetic distance of all region rsIDs when calculating iHS, i.e., one genetic position per rsID. Can I use physical position/1e6 instead of genetic position? Will this cause a large estimation error?
I look forward to hearing from you!
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