SNP & Variation Suite Software

Genotype Imputation


Imputation LD Plot in SVS

SVS allows you to natively impute missing or incomplete genotypes in your GWAS workflows



Genotype Imputation is commonly used in research workflows to accomplish the following goals:

  • Increased density of genotype calls for fine mapping or to identify candidate causal variants at a susceptibility locus
  • Harmonize disparate SNP sets between microarray platforms so that they can be analyzed together in meta-analysis or mega-analysis
  • Merge public data or NGS variant data in with micro-array data for combined analysis 

The SVS imputation algorithm is an adaptation of the mature BEAGLE 4.1 algorithm that is designed to scale to tens of thousands of samples and whole genome sequencing variation density.

For Human and Animal Genomics

If you are studying human populations, we provide publicly available subsets of pre-phased 1000 Genomes phased genotypes subsetted down to useful frequencies to be used for imputation:

  • 5% allele frequency or greater (8.5 million variants)
  • 1% allele frequency or greater (14.2 million variants)
  • Allele count greater than 20 (~0.4% with 19.5 million variants)

Another common use case in both human and agrigenomics involves imputing from one genotype array up to a reference panel with a higher marker density. Among other things, this allows you to leverage data from multiple GWAS conducted on different micro-array platforms. In this case, you are able to use our Create Imputation Reference Panel tool to create your own phased reference panel dataset you can use for imputation of your own data.

Golden Helix SVS provides full support for non-human genomes and imputation also works for any species under study.

System Requirements

The imputation capability is provided as part of an SVS Server license.The recommended minimum machine requirement to run SVS on a server with imputation is an 8 core machine with 16GB of RAM. The imputation program is multi-threaded and automatically detects the number of available CPU cores. Runtime is directly correlated to the number of CPU cores and so large impute jobs will benefit from having as many CPU cores as possible on a single server.


Whole Genome Density

We provide pre-phased subsets of the 1000 Genomes Phase3 2500 human samples to be used when imputing genotypes up to whole genome density.




Related Resources

Case Study - Matthew McClure, Irish Cattle Breeding Federation
Matthew McClure

"SVS has improved our workflow substantially. We are able to view sequence data, zoom in on variants, and examine alignments to see if they agree."

Read the case study »

BEAGLE Imputation in SVS for Human & Animal

Watch the Imputation in SVS Webcast on YouTube

Learn more »

GWAS eBook
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GWAS

by Dr. Andreas Scherer

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SVS Software is intended for Research Use Only. Not for use in diagnostic procedures.