Mathematical Methods in Interdisciplinary Sciences

2Deep Learning in Population Genetics: Prediction and Explanation of Selection of a Population

Romila Ghoshand¹ and Satyakama Paul²

¹Department of Statistics, Amity University, Kolkata, India

²Institute of Intelligent Systems, University of Johannesburg, Johannesburg, South Africa

2.1 Introduction

A major aim in population genetic studies is to draw insights into the evolutionary background of a population. Until decades after its emergence in twentieth century, theories on genetics have been way ahead of the data required to prove the statements. Improvement of the data generating capacity of genomes in the end of twentieth century have enabled analysis of genomic data over related disciplines. Currently, with the advent of whole genome sequencing data, demographic inference can be carried out with more efficient models [1].

In this paper, we focus on using deep learning (DL) to infer on selection on a whole‐genome variation data of Drosophila melanogaster species. Since the availability of genome sequencing data, several studies on demography and selection have been carried on the populations of Drosophila. However, determination or joint inference of both demography and selection has been argued by several researchers to be difficult because of the high influence of selection over shaping the demography of a population [2]. In many of the previous research studies on selection, it is clearly indicated that for Drosophila genome, selection I confounded demography [3] and ...