Evidence map›Paper›PMID 23829669›Full record

ArticleAlgorithms for molecular biology : AMB2013

Estimating population size via line graph reconstruction.

Bjarni V Halldórsson, Dima Blokh, Roded Sharan

Abstract read
In one paragraph

Article in Algorithms for molecular biology : AMB, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Bjarni V HalldórssonSchool of Science and Engineering, Reykjavík University, Menntavegur 1, Reykjavik 101, Iceland. bjarnivh@ru.is.
Dima Blokh
Roded Sharan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe propose a novel graph theoretic method to estimate haplotype population size from genotype data. The method considers only the potential sharing of haplotypes between individuals and is based on transforming the graph of potential haplotype sharing into a line graph using a minimum number of edge and vertex deletions.

resultsWe show that the resulting line graph deletion problems are NP complete and provide exact integer programming solutions for them. We test our approach using extensive simulations of multiple population evolution and genotypes sampling scenarios. Our results also indicate that the method may be useful in comparing populations and it may be used as a first step in a method for haplotype phasing.

conclusionsOur computational experiments show that when most of the sharings are true sharings the problem can be solved very fast and the estimated size is very close to the true size; when many of the potential sharings do not stem from true haplotype sharing, our method gives reasonable lower bounds on the underlying number of haplotypes. In comparison, a naive approach of phasing the input genotypes provides trivial upper bounds of twice the number of genotypes.

Identifiers

PMID23829669
PMCPMC3716786

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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.