Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. Understanding the Function of a Locus Using the Knowledge Available at Single-Nucleotide Polymorphisms. Cardiogenetics2021, 11, 255-262.
Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. Understanding the Function of a Locus Using the Knowledge Available at Single-Nucleotide Polymorphisms. Cardiogenetics 2021, 11, 255-262.
Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. Understanding the Function of a Locus Using the Knowledge Available at Single-Nucleotide Polymorphisms. Cardiogenetics2021, 11, 255-262.
Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. Understanding the Function of a Locus Using the Knowledge Available at Single-Nucleotide Polymorphisms. Cardiogenetics 2021, 11, 255-262.
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.
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
