Imputation of Missing Genotypes within LD-Blocks Relying on the Basic Coalescent and Beyond [Source Code]

DOI

Background

Genotypes not directly measured in genetic studies are often imputed to improve statistical power and to increase mapping resolution. The accuracy of standard imputation techniques strongly depends on the similarity of linkage disequilibrium (LD) patterns in the study and reference populations. Here we develop a novel approach for genotype imputation in low-recombination regions that relies on the coalescent and permits to explicitly account for population demographic factors.

To test the new method, study and reference haplotypes were simulated and gene trees were inferred under the basic coalescent and also considering population growth and structure. The reference haplotypes that first coalesced with study haplotypes were used as templates for genotype imputation. Computer simulations were complemented with the analysis of real data. Genotype concordance rates were used to compare the accuracies of coalescent-based and standard (IMPUTE2) imputation.

Results

Simulations revealed that, in LD-blocks, imputation accuracy relying on the basic coalescent was higher and less variable than with IMPUTE2. Explicit consideration of population growth and structure, even if present, did not practically improve accuracy. The advantage of coalescent-based over standard imputation increased with the minor allele frequency and it decreased with population stratification. Results based on real data indicated that, even in low-recombination regions, further research is needed to incorporate recombination in coalescence inference, in particular for studies with genetically diverse and admixed individuals.

Conclusions

To exploit the full potential of coalescent-based methods for the imputation of missing genotypes in genetic studies, further methodological research is needed to reduce computer time, to take into account recombination, and to implement these methods in user-friendly computer programs. Here we provide reproducible code which takes advantage of publicly available software to facilitate further developments in the field.

Identifier
DOI https://doi.org/10.11588/data/X9UEHB
Related Identifier https://doi.org/10.1186/s12864-017-4208-2
Metadata Access https://heidata.uni-heidelberg.de/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.11588/data/X9UEHB
Provenance
Creator Kabisch, Maria; Hamann, Ute; Lorenzo Bermejo, Justo ORCID logo
Publisher heiDATA
Contributor Lorenzo Bermejo, Justo
Publication Year 2018
Rights info:eu-repo/semantics/openAccess
OpenAccess true
Contact Lorenzo Bermejo, Justo (Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany)
Representation
Resource Type Dataset
Format application/x-sas-syntax; application/pdf
Size 11567; 2641; 18304; 2109; 5292; 244085
Version 1.0
Discipline Life Sciences; Medicine