Evidence map›Paper›PMID 24875187›Full record

ArticleGenetics2014

Genome-wide estimation of linkage disequilibrium from population-level high-throughput sequencing data.

Takahiro Maruki, Michael Lynch

Abstract read
In one paragraph

Article in Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Genetic control of male production inProceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Population Genomics ofGenetics · 2017
    Article
  13. Article
  14. Article
  15. 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

2 authors.

Takahiro MarukiDepartment of Biology, Indiana University, Bloomington, Indiana 47405 tmaruki@indiana.edu.
Michael LynchDepartment of Biology, Indiana University, Bloomington, Indiana 47405.

Funding

The Rate and Molecular Spectrum of Spontaneous MutationsR01GM036827 · NIGMS · UNIVERSITY OF OREGON · PI LYNCH, MICHAEL R · 1988 to 2016
$5.7M
Population Genomics of Daphnia pulexR01GM101672 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI LYNCH, MICHAEL R · 2013 to 2016
$2.3M
NIGMS NIH HHS 1R01GM101672-01A1NIGMS NIH HHS R01 GM036827NIGMS NIH HHS R01 GM101672
6 · The paper itself

Abstract

Rapidly improving sequencing technologies provide unprecedented opportunities for analyzing genome-wide patterns of polymorphisms. In particular, they have great potential for linkage-disequilibrium analyses on both global and local genetic scales, which will substantially improve our ability to derive evolutionary inferences. However, there are some difficulties with analyzing high-throughput sequencing data, including high error rates associated with base reads and complications from the random sampling of sequenced chromosomes in diploid organisms. To overcome these difficulties, we developed a maximum-likelihood estimator of linkage disequilibrium for use with error-prone sampling data. Computer simulations indicate that the estimator is nearly unbiased with a sampling variance at high coverage asymptotically approaching the value expected when all relevant information is accurately estimated. The estimator does not require phasing of haplotypes and enables the estimation of linkage disequilibrium even when all individual reads cover just single polymorphic sites.

Indexed as

Linkage DisequilibriumComputer SimulationGene FrequencyGenetic Association StudiesGenetic LociHigh-Throughput Nucleotide SequencingModels, Molecularlinkage disequilibriumpopulation genomics

Identifiers

PMID24875187
PMCPMC4125401

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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.