Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Understanding the Function of a Locus Using the Knowledge Available at Single-Nucleotide Polymorphisms

Version 1 : Received: 1 August 2021 / Approved: 3 August 2021 / Online: 3 August 2021 (14:26:17 CEST)

How to cite: Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. Understanding the Function of a Locus Using the Knowledge Available at Single-Nucleotide Polymorphisms. Preprints 2021, 2021080084 (doi: 10.20944/preprints202108.0084.v1). Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. Understanding the Function of a Locus Using the Knowledge Available at Single-Nucleotide Polymorphisms. Preprints 2021, 2021080084 (doi: 10.20944/preprints202108.0084.v1).

Abstract

Understanding the function of a locus is a challenge in molecular biology. Although numerous molecular data have been generated in the last decades, it remains difficult to grasp, how these data are related at a locus? In this study, we describe an analytical workflow that can solve this problem using the knowledge available at single-nucleotide polymorphisms (SNPs) level. The underlying algorithm uses SNPs as connectors to link omics data and identify correlation between them through a joint bioinformatical/statistical approach. We describe its application in finding the mechanism whereby a mutation causes a phenotype and in revealing the path whereby a gene is being regulated and impacts the phenotypes. We translated our workflow into freely available shell scripts that carry out the analyses. Our approach provides a basic framework to solve the information overload problem in biology.

Keywords

Annotation; SNPs; Rare variants; Mendelian randomization; Algorithm

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