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Efficient phasing and imputation of low-coverage sequencing data using large reference panels.

Abstract：

:Low-coverage whole-genome sequencing followed by imputation has been proposed as a cost-effective genotyping approach for disease and population genetics studies. However, its competitiveness against SNP arrays is undermined because current imputation methods are computationally expensive and unable to leverage large reference panels. Here, we describe a method, GLIMPSE, for phasing and imputation of low-coverage sequencing datasets from modern reference panels. We demonstrate its remarkable performance across different coverages and human populations. GLIMPSE achieves imputation of a genome for less than US$1 in computational cost, considerably outperforming other methods and improving imputation accuracy over the full allele frequency range. As a proof of concept, we show that 1× coverage enables effective gene expression association studies and outperforms dense SNP arrays in rare variant burden tests. Overall, this study illustrates the promising potential of low-coverage imputation and suggests a paradigm shift in the design of future genomic studies.

journal_name

Nat Genet

journal_title

Nature genetics

authors

Rubinacci S,Ribeiro DM,Hofmeister RJ,Delaneau O

doi

10.1038/s41588-020-00756-0

subject

Has Abstract

pub_date

2021-01-01 00:00:00

pages

120-126

issue

1

eissn

1061-4036

issn

1546-1718

pii

10.1038/s41588-020-00756-0

journal_volume

53

pub_type

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