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How to understand the genotype imputation in GWAS, for this problem, this article introduces the corresponding analysis and solution in detail, hoping to help more small partners who want to solve this problem find a simpler and easier way.

GWAS is used to find SNP loci associated with diseases or specific traits. In order to mine information more effectively, GWAS needs large sample size and high density SNP typing results. Of course, the best typing scheme is whole genome sequencing. However, the cost of whole genome sequencing of hundreds or thousands of samples is still huge. At present, the more economical and effective scheme is GWAS chip, which uses the idea of tag SNP to design probes for specific populations, covering SNP loci in the order of tens of M.

Compared with whole genome sequencing, GWAS chip is indeed more economical, but its shortcomings are also obvious. It can only analyze and mine known SNP loci, and the amount of locus data is relatively small. It is necessary to know that the SNP loci obtained by a whole genome sequencing analysis are about several hundred M. To solve this problem, scientists proposed the idea of genotype filling.

Genotype imputation, called genotype filling, is based on the idea of using haplotypes to infer the typing results of SNP loci not covered by the chip. It is applicable to both family data and independent sample analysis. The process of genotype filling in a family sample is illustrated as follows

Some samples have relatively complete SNP typing results, haplotypes shared among family samples are constructed according to the typing results of these samples, and complete typing results corresponding to box markers in the figure are used. For samples with genotype deletion, possible haplotypes of this sample are inferred according to genetic relationship, and for loci with genotype deletion, the typing results in corresponding haplotypes are directly used for filling.

The genotype filling process for independent samples is illustrated as follows

First, there needs to be a reference haplotype. According to the existing typing results of the sample, compare it with the reference haplotype to determine the haplotype it may belong to, and then fill in.

The above schematic diagram is from the following documents

Genotype Imputation

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2925172/

As can be seen from the above schematic diagram, there are two necessary conditions for genotype filling. The first condition is the reference haplotype. For independent samples, haplotypes of hapmap or 1000G can be used as references. The second condition is the proportion and distribution of known typing result loci. For samples to be filled, to ensure a certain density of typing results, it is necessary to infer the possible haplotypes of the samples according to the existing typing results. The more loci the typing results are known, The higher the accuracy of haplotype inference, the higher the accuracy of population. According to this condition, GWAS chip is most suitable for genotype population because the number and distribution of SNP sites covered by it are more helpful to infer the haplotype of samples.

There are already a lot of software available for genotyping, some of which are listed below

Beagle

IMPUTE2

MACH

About how to understand the GWAS in the genotype imputation of the answer to the question shared here, I hope the above content can be of some help to everyone, if you still have a lot of doubts not solved, you can pay attention to the industry information channel to learn more related knowledge.

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