Evidence map›Paper›PMID 23421795›Full record

ArticleJournal of computational biology : a journal of computational molecular cell biology2013

Ancestry inference in complex admixtures via variable-length Markov chain linkage models.

Jesse M Rodriguez, Sivan Bercovici, Megan Elmore, Serafim Batzoglou

Abstract read
In one paragraph

Article in Journal of computational biology : a journal of computational molecular cell biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
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  6. Review
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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

4 authors.

Jesse M RodriguezDepartment of Computer Science, Stanford University, Stanford, California 94305, USA. jesserod@cs.stanford.edu
Sivan Bercovici
Megan Elmore
Serafim Batzoglou

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
A Strategy for High Quality Clinical Resequencing of the Human GenomeRC2HG005570 · NHGRI · STANFORD UNIVERSITY · PI DAVIS, RONALD WAYNE · 2009 to 2010
$2.8M
NHGRI NIH HHS 5RC2HG005570-02NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

Inferring the ancestral origin of chromosomal segments in admixed individuals is key for genetic applications, ranging from analyzing population demographics and history, to mapping disease genes. Previous methods addressed ancestry inference by using either weak models of linkage disequilibrium, or large models that make explicit use of ancestral haplotypes. In this paper we introduce ALLOY, an efficient method that incorporates generalized, but highly expressive, linkage disequilibrium models. ALLOY applies a factorial hidden Markov model to capture the parallel process producing the maternal and paternal admixed haplotypes, and models the background linkage disequilibrium in the ancestral populations via an inhomogeneous variable-length Markov chain. We test ALLOY in a broad range of scenarios ranging from recent to ancient admixtures with up to four ancestral populations. We show that ALLOY outperforms the previous state of the art, and is robust to uncertainties in model parameters.

Indexed as

Genealogy and HeraldryGene PoolGenetic LinkageMarkov ChainsModels, GeneticAlgorithmsComputational BiologyComputer SimulationHaplotypesHumansLinkage Disequilibrium

Identifiers

PMID23421795
PMCPMC3590892

What OpenQuestion holds

Textmetadata
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Registered trials

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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.