ArticlePloS one2011
PoolHap: inferring haplotype frequencies from pooled samples by next generation sequencing.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
22 citing papers in PubMed.
- PolyAdapt: Characterizing Polygenic Adaptive Architectures in the Presence of Strong Linkage Disequilibrium.Genome biology and evolution · 2026Article
- The illusion of polygenicity in pool-seq genetic mapping studies: insufficient power can mask simple genetic architectures.Genetics · 2026Article
- Leveraging low-cost short-read sequencing: revolutionizing complex trait genetics.Molecular biology and evolution · 2026Article
- Varaps: a python package for estimating SARS-CoV-2 lineages proportions from pooled sequencing data (ANRS0160).BMC bioinformatics · 2025Article
- "Select and Resequence" Methods Enable a Genome-Wide Association Study of the Dimorphic Human Fungal Pathogen Coccidioides posadasii.Genome biology and evolution · 2025Article
- Article
- Haplotype based testing for a better understanding of the selective architecture.BMC bioinformatics · 2023Article
- Adaptation in Outbred Sexual Yeast is Repeatable, Polygenic and Favors Rare Haplotypes.Molecular biology and evolution · 2022Article
- High-throughput estimation of allele frequencies using combined pooled-population sequencing and haplotype-based data processing.Plant methods · 2022Article
- Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing.Genetics · 2022Article
- Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding.Molecular biology and evolution · 2021Article
- Detecting selected haplotype blocks in evolve and resequence experiments.Molecular ecology resources · 2021Article
- Two Synthetic 18-Way Outcrossed Populations of Diploid Budding Yeast with Utility for Complex Trait Dissection.Genetics · 2020Article
- Accurate Allele Frequencies from Ultra-low Coverage Pool-Seq Samples in Evolve-and-Resequence Experiments.G3 (Bethesda, Md.) · 2019Article
- Genetic redundancy fuels polygenic adaptation in Drosophila.PLoS biology · 2019Article
- Perilla Oil Supplementation Ameliorates High-Fat/High-Cholesterol Diet Induced Nonalcoholic Fatty Liver Disease in Rats via Enhanced Fecal Cholesterol and Bile Acid Excretion.BioMed research international · 2016Article
- Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits.Genetics · 2015Article
- Patterns of linkage disequilibrium and long range hitchhiking in evolving experimental Drosophila melanogaster populations.Molecular biology and evolution · 2015Article
- Sequencing pools of individuals - mining genome-wide polymorphism data without big funding.Nature reviews. Genetics · 2014Review
- Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
With the advance of next-generation sequencing (NGS) technologies, increasingly ambitious applications are becoming feasible. A particularly powerful one is the sequencing of polymorphic, pooled samples. The pool can be naturally occurring, as in the case of multiple pathogen strains in a blood sample, multiple types of cells in a cancerous tissue sample, or multiple isoforms of mRNA in a cell. In these cases, it's difficult or impossible to partition the subtypes experimentally before sequencing, and those subtype frequencies must hence be inferred. In addition, investigators may occasionally want to artificially pool the sample of a large number of individuals for reasons of cost-efficiency, e.g., when carrying out genetic mapping using bulked segregant analysis. Here we describe PoolHap, a computational tool for inferring haplotype frequencies from pooled samples when haplotypes are known. The key insight into why PoolHap works is that the large number of SNPs that come with genome-wide coverage can compensate for the uneven coverage across the genome. The performance of PoolHap is illustrated and discussed using simulated and real data. We show that PoolHap is able to accurately estimate the proportions of haplotypes with less than 2% error for 34-strain mixtures with 2X total coverage Arabidopsis thaliana whole genome polymorphism data. This method should facilitate greater biological insight into heterogeneous samples that are difficult or impossible to isolate experimentally. Software and users manual are freely available at http://arabidopsis.gmi.oeaw.ac.at/quan/poolhap/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.