LDx: estimation of linkage disequilibrium from high-throughput pooled resequencing data

TL;DR

LDx is a computational tool that estimates linkage disequilibrium from pooled resequencing data, enabling insights into population structure and demographic history despite the loss of haplotype information.

Contribution

LDx introduces an approximate maximum likelihood method to estimate LD from pooled resequencing data, bridging the gap caused by haplotype information loss.

Findings

LDx estimates correlate highly with individual resequencing r2 values.

LDx can infer genome-wide LD decay patterns in D. melanogaster.

LDx distinguishes between different demographic models using pooled data.

Abstract

High-throughput pooled resequencing offers significant potential for whole genome population sequencing. However, its main drawback is the loss of haplotype information. In order to regain some of this information, we present LDx, a computational tool for estimating linkage disequilibrium (LD) from pooled resequencing data. LDx uses an approximate maximum likelihood approach to estimate LD (r2) between pairs of SNPs that can be observed within and among single reads. LDx also reports r2 estimates derived solely from observed genotype counts. We demonstrate that the LDx estimates are highly correlated with r2 estimated from individually resequenced strains. We discuss the performance of LDx using more stringent quality conditions and infer via simulation the degree to which performance can improve based on read depth. Finally we demonstrate two possible uses of LDx with real and simulated pooled resequencing data. First, we use LDx to infer genomewide patterns of decay of LD with physical distance in D. melanogaster population resequencing data. Second, we demonstrate that r2 estimates from LDx are capable of distinguishing alternative demographic models representing plausible demographic histories of D. melanogaster.