<p>You can't generate LD statistics for summary data from SNPs, as the LD calculation relies on the comparison of variants at the genotype level. Plink expects data to be in a genotype matrix with either each marker for each line (probably better in your case), or each individual for each line. Plink v1.9, in particular, will accept VCF-formatted input files, when populated with 'GT' information that describes the variants for each individual.</p>

<p>If you're okay with using the 1000 genome population for calculating LD, plink v1.9-compatible datasets should be accessible from
<a href="https://www.cog-genomics.org/plink2/resources" rel="nofollow noreferrer">here</a>.</p>

<p>If not, you'll need to discuss your project with IGAP to see if you can have access to genotype-level data for LD testing. That's unlikely, because there are personal identification issues associated with non-summary data.</p>

<p>There's comprehensive documentation about the LD command(s) on the Plink 1.9 website <a href="https://www.cog-genomics.org/plink/1.9/ld" rel="nofollow noreferrer">here</a>.</p>

CC BY-SA 3.0
2017-11-22T12:48:08.480Z
Thanks for your explanation @gringer. I will now use a plink v1.9-compatible dataset from 1000 genome  and then use plink  --noweb 
 --bfile 1000genomefile --clump SNPfile --clump-field P --clump-p1 1.0001 --clump-p2 1.0001 --clump-r2 0.8 --clump-kb 1000 --out resultfile. But I'm unsure if line-by-line listing of SNPs on SNPfile will work and what the correct format should be. Any suggestions?
user27976
CC BY-SA 3.0
2017-11-22T14:14:05.907Z
EDIT:  --clump-p1 0.0001 --clump-p2 0.0001
user27976
CC BY-SA 3.0
2017-11-22T00:36:08.450Z
2017-11-22T10:13:52.723Z
2017-11-22T10:13:52.723Z
gringer
<p>I have a list of SNPs (index SNPs). As my tagging SNPs, I want to use SNP data from <a href="http://web.pasteur-lille.fr/en/recherche/u744/igap/igap_download.php" rel="nofollow noreferrer">here</a>. The data has the following column headers: Chromosome, Position, MarkerName, Effect_allele,   Non_Effect_allele, Beta, SE, Pvalue.</p>

<p>My ultimate aim is to identify SNPs in the tagging set that are in LD with each of index SNPs. I need to calculate r2 between index SNPs and tagging SNPs within 1MB window and get a table of index vs tagging SNPs (r2>0.8). </p>

<p>How can I use PLINK to carry out this work? I'm new to PLINK and LD clumping</p>

<snp><plink>
Using PLINK to find SNPs in LD (Linkage Disequilibrium) with another set of SNPs
# Using PLINK to find SNPs in LD (Linkage Disequilibrium) with another set of SNPs

(Asked by: username_0 on 2017-11-21)

I have a list of SNPs (index SNPs). As my tagging SNPs, I want to use SNP data from [here](http://web.pasteur-lille.fr/en/recherche/u744/igap/igap_download.php). The data has the following column headers: Chromosome, Position, MarkerName, Effect\_allele, Non\_Effect\_allele, Beta, SE, Pvalue.

My ultimate aim is to identify SNPs in the tagging set that are in LD with each of index SNPs. I need to calculate r2 between index SNPs and tagging SNPs within 1MB window and get a table of index vs tagging SNPs (r2>0.8).

How can I use PLINK to carry out this work? I'm new to PLINK and LD clumping

**Tags:** snp, plink

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## 1 answers

### Answer by username_1 on 2017-11-22. Score: 1 | Accepted answer

You can't generate LD statistics for summary data from SNPs, as the LD calculation relies on the comparison of variants at the genotype level. Plink expects data to be in a genotype matrix with either each marker for each line (probably better in your case), or each individual for each line. Plink v1.9, in particular, will accept VCF-formatted input files, when populated with 'GT' information that describes the variants for each individual.

If you're okay with using the 1000 genome population for calculating LD, plink v1.9-compatible datasets should be accessible from
[here](https://www.cog-genomics.org/plink2/resources).

If not, you'll need to discuss your project with IGAP to see if you can have access to genotype-level data for LD testing. That's unlikely, because there are personal identification issues associated with non-summary data.

There's comprehensive documentation about the LD command(s) on the Plink 1.9 website [here](https://www.cog-genomics.org/plink/1.9/ld).

> **Comments:**
> **username_0**: Thanks for your explanation @gringer. I will now use a plink v1.9-compatible dataset from 1000 genome  and then use plink  --noweb   --bfile 1000genomefile --clump SNPfile --clump-field P --clump-p1 1.0001 --clump-p2 1.0001 --clump-r2 0.8 --clump-kb 1000 --out resultfile. But I'm unsure if line-by-line listing of SNPs on SNPfile will work and what the correct format should be. Any suggestions?  
> **username_0**: EDIT:  --clump-p1 0.0001 --clump-p2 0.0001  

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