Analysis in case-control sequencing association studies with different sequencing depths.

ABSTRACT: With the advent of next-generation sequencing, investigators have access to higher quality sequencing data. However, to sequence all samples in a study using next generation sequencing can still be prohibitively expensive. One potential remedy could be to combine next generation sequencing data from cases with publicly available sequencing data for controls, but there could be a systematic difference in quality of sequenced data, such as sequencing depths, between sequenced study cases and publicly available controls. We propose a regression calibration (RC)-based method and a maximum-likelihood method for conducting an association study with such a combined sample by accounting for differential sequencing errors between cases and controls. The methods allow for adjusting for covariates, s

SUBMITTER: Chen S 

PROVIDER: S-EPMC7308042 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature