Evidence map›Paper›PMID 24760431›Full record

ArticleJournal of mathematical biology2015

An analytical framework in the general coalescent tree setting for analyzing polymorphisms created by two mutations.

Ori Sargsyan

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Article in Journal of mathematical biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Statistical Inference for the Evolutionary History of Cancer Genomes.Statistical science : a review journal of the Institute of Mathematical Statistics · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Ori Sargsyan, Los Alamos, NM, 87544, USA, orisargsyan@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents an analytical framework for analyzing polymorphisms created by two mutation events in samples of DNA sequences modeled in the general coalescent tree setting. I developed the framework by deriving analytical formulas for the numbers of the topologies of the genealogies with two mutation events. This approach gives an advantage to analyze polymorphisms in large samples of DNA sequences at a non-recombining locus under vicarious evolutionary scenarios. Particularly the framework allows to estimate the probability of polymorphism data created by two mutation events as well as the ages of the events. Based on these results I extended the definition of the site frequency spectrum by classifying pairs of polymorphic sites into groups and presented analytical expressions for computing the expected sizes of these groups. Within the framework I also designed a Bayesian approach for inferring the haplotype of the most recent common ancestor at two polymorphic sites. Lastly, the framework was applied to polymorphism data from human APOE gene region under various demographic scenarios for ancestral human population and explored the signature of linkage disequilibrium for inferring the ancestral haplotype at two polymorphic sites. Interestingly enough, the results show that the most frequent haplotype at two completely linked polymorphic sites is not always the most likely candidate for the haplotype of the most recent common ancestor.

Indexed as

Models, GeneticMutationPolymorphism, GeneticAlgorithmsApolipoproteins EBayes TheoremDNAEvolution, MolecularHaplotypesHumansMathematical ConceptsMonte Carlo MethodProbabilityApolipoproteins EDNA

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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.