STATISTICAL CHALLENGES IN NEXT GENERATION POPULATION GENOMICS STUDY

Abstract

A majority of lower frequencies variants are identified with the advent of next generation sequencing, encouraging the array-based follow-up studies emphasizing on low frequency and rare variants. Besides, next generation sequencing facilitates population genetics research by providing fine-scale haplotype sequence of individual genome.

The first study investigates the microarray genotype calling issue for low frequency and rare variants. Existing genotype calling algorithms are developed mainly for common SNPs and present many problems for rare variants. We design and introduce a new method, iCall, for a robust genotyping of common, low-frequency and rare SNPs, and we show that iCall outperforms existing genotype calling algorithms.

The second study continues the theme of investigating the impact that sequencing technologies bring to genetics research. Specifically we evaluate existing methods for estimating the divergence time of closely related populations, followed by estimating the population divergence time between Southeast Asian Malays and South Asian Indians.