HMMploidy: inference of ploidy levels from short-read sequencing data

TY - JOUR

T1 - HMMploidy

T2 - inference of ploidy levels from short-read sequencing data

AU - Soraggi, Samuele

AU - Rhodes, Johanna

AU - Altinkaya, Isin

AU - Tarrant, Oliver

AU - Balloux, Francois

AU - Fisher, Matthew C

AU - Fumagalli, Matteo

PY - 2022/10

Y1 - 2022/10

N2 - The inference of ploidy levels from genomic data is important to understand molecular mechanisms underpinning genome evolution. However, current methods based on allele frequency and sequencing depth variation do not have power to infer ploidy levels at low-and mid-depth sequencing data, as they do not account for data uncertainty. Here we introduce HMMploidy, a novel tool that leverages the information from multiple samples and combines the information from sequencing depth and genotype likelihoods. We demonstrate that HMMploidy outperforms existing methods in most tested scenarios, especially at low-depth with large sample size. We apply HMMploidy to sequencing data from the pathogenic fungus Cryptococcus neoformans and retrieve pervasive patterns of aneuploidy, even when artificially downsampling the sequencing data. We envisage that HMMploidy will have wide applicability to low-depth sequencing data from polyploid and aneuploid species.

AB - The inference of ploidy levels from genomic data is important to understand molecular mechanisms underpinning genome evolution. However, current methods based on allele frequency and sequencing depth variation do not have power to infer ploidy levels at low-and mid-depth sequencing data, as they do not account for data uncertainty. Here we introduce HMMploidy, a novel tool that leverages the information from multiple samples and combines the information from sequencing depth and genotype likelihoods. We demonstrate that HMMploidy outperforms existing methods in most tested scenarios, especially at low-depth with large sample size. We apply HMMploidy to sequencing data from the pathogenic fungus Cryptococcus neoformans and retrieve pervasive patterns of aneuploidy, even when artificially downsampling the sequencing data. We envisage that HMMploidy will have wide applicability to low-depth sequencing data from polyploid and aneuploid species.

KW - NGS sequencing

KW - ploidy

KW - Genotype likelihoods

UR - http://www.scopus.com/inward/record.url?scp=85152912774&partnerID=8YFLogxK

U2 - 10.24072/pcjournal.178

DO - 10.24072/pcjournal.178

M3 - Journal article

SN - 2804-3871

VL - 2

JO - Peer Community Journal

JF - Peer Community Journal

M1 - e60

ER -