PoolHap

PoolHap infers haplotype frequencies from pooled next-generation sequencing (NGS) samples when haplotypes are known, enabling quantitative analysis of polymorphic mixtures such as multiple pathogen strains in blood, diverse tumor cell types, various mRNA isoforms in single cells, and pooled individuals for bulked segregant analysis.

Key Features:

• Haplotype frequency inference: Estimates frequencies of known haplotypes from pooled sequencing data.
• Uses NGS data: Operates on next-generation sequencing reads to extract allele information.
• Genome-wide SNP leverage: Exploits large numbers of single nucleotide polymorphisms (SNPs) across genome-wide coverage to compensate for uneven coverage.
• Validation on simulated and real datasets: Demonstrated performance on both simulated data and empirical datasets.
• High accuracy: Reported haplotype frequency estimation error margin below 2%.
• Empirical demonstration: Successfully estimated frequencies in 34-strain mixtures at 2X total coverage using Arabidopsis thaliana whole-genome polymorphism data.

Scientific Applications:

• Pathogen mixture analysis: Quantifies relative abundances of multiple pathogen strains in blood or other clinical samples.
• Tumor heterogeneity: Profiles proportions of diverse cell types within cancerous tissue.
• mRNA isoform quantification: Estimates relative abundances of various mRNA isoforms in single cells.
• Bulked segregant analysis and genetic mapping: Infers haplotype proportions from artificially pooled individuals for cost-efficient mapping studies.

Methodology:

PoolHap analyzes simulated and real NGS datasets, leverages genome-wide SNP counts to infer frequencies of known haplotypes, and reports frequency estimates with demonstrated accuracy (error <2%) including a test on 34-strain mixtures at 2X total coverage using Arabidopsis thaliana whole-genome polymorphism data.