Reconstruction of a matrix of genotypic correlations between variants within a gene for joint analysis of imputed and sequenced data

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Abstract

When combining imputed and sequenced data in a single gene-based association analysis, the problem of reconstructing genetic correlation matrices arises. It is related to the fact that for a gene, we know the correlations between genotypes of all imputed variants and the correlations between genotypes of all sequenced variants, but we do not know the correlations between genotypes of variants, one of which is imputed and the other is sequenced. To recover these correlations, we propose an efficient method based on maximising the determinant of the matrix. This method has a number of useful properties and has an analytical solution for our task. Approbation of the proposed method was performed by comparing reconstructed and real correlation matrices constructed on individual genotypes from the UK biobank. Comparison of the results of gene-based association analysis performed by the SKAT, BT and PCA methods on reconstructed and real matrices, using modelled summary statistics and calculated summary statistics on real phenotypes, showed high quality of reconstruction and robustness of the method to different gene structures.

About the authors

G. R. Svishcheva

Federal Research Centre, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences; Vavilov Institute of General Genetics, Russian Academy of Sciences

Author for correspondence.
Email: gulsvi@mail.ru
Russian Federation, 630090, Novosibirsk; 119991, Moscow

A. V. Kirichenko

Federal Research Centre, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences

Email: gulsvi@mail.ru
Russian Federation, 630090, Novosibirsk

N. M. Belonogova

Federal Research Centre, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences

Email: gulsvi@mail.ru
Russian Federation, 630090, Novosibirsk

E. E. Elgaeva

Federal Research Centre, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University

Email: gulsvi@mail.ru
Russian Federation, 630090, Novosibirsk; 630090, Novosibirsk

A. Ya. Tsepilov

Federal Research Centre, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences

Email: gulsvi@mail.ru
Russian Federation, 630090, Novosibirsk

I. V. Zorkoltseva

Federal Research Centre, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences

Email: gulsvi@mail.ru
Russian Federation, 630090, Novosibirsk

T. I. Axenovich

Federal Research Centre, Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences

Email: gulsvi@mail.ru
Russian Federation, 630090, Novosibirsk

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