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How to perform Linkage Disequilibrium analysis for significantly associated K-mers?

Hello, I am performing a K-mer based GWAS on my dataset. I have obtained some k-mers that are significantly associated with the trait of interest. Now, I want to perform a linkage disequilibrium (LD) analysis among those significant K-mers and create a heatmap as it is done with SNPs. But the problem is that the positioning of the k-mers is not know as it is a reference-free method. I have a table with presence/absence pattern of the associated k-mers in my samples.

Does someone have any idea how can I measure the LD among the significant k-mers?

I have the Plink binary files (*.bim, *.bed and *.fam files) containing the K-mer data that I used for GWAS.

Please let me know if you have any ideas.

Thank you.

next-gen genome snp assembly

2 answers

what tool did you use for your gwas and how was the presence/absence kmer pattern generated?

I used the K-mer GWAS tool to do the GWAS [https://www.nature.com/articles/s41588-020-0612-7]

If one gets any significant association between a K-mer and the phenotype, then a presence/absence pattern of that K-mer among the samples can be obtained. The presence/absence pattern is in binary form. I saw in the paper that they used a formula for getting the LD value under the section "Calculation of Linkage Disequilibrium". I asked the author about the input files. They said they only used that presence/absence pattern table and applied that formula in R to obtain the LD value. But I am not sure how to use that formula for estimating LD in R. Do you have any idea?

Hi Anik,

Did you manage to calculate LD between significant kmers? if yes, which tool did you eventually use and what were the input files for the same.

Thanks

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