Evidence map›Paper›PMID 35100400›Full record

ArticleGenetics2022

Haplotype-based inference of the distribution of fitness effects.

Diego Ortega-Del Vecchyo, Kirk E Lohmueller, John Novembre

Abstract read
In one paragraph

Article in Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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  3. Review
  4. Article
  5. 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

3 authors.

Diego Ortega-Del VecchyoLaboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro 76230, México.ORCID 0000-0003-4054-3766
Kirk E LohmuellerInterdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA.
John NovembreDepartment of Human Genetics, University of Chicago, Chicago, IL 60637, USA.ORCID 0000-0001-5345-0214

Funding

Population genomics of the selective effects of new mutationsR35GM119856 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LOHMUELLER, KIRK · 2016 to 2025
$3.4M
Haplotype-based analysis methods for population genomicsR01HG007089 · NHGRI · UNIVERSITY OF CHICAGO · PI NOVEMBRE, JOHN · 2013 to 2017
$1.5M
NHGRI NIH HHS R01 HG007089NIGMS NIH HHS R35 GM119856
6 · The paper itself

Abstract

Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some nonequilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.

Indexed as

Models, GeneticSelection, GeneticChromosome MappingHaplotypesHumansLikelihood FunctionsSample SizeDFEhaplotypeinferenceselection

Identifiers

PMID35100400
PMCPMC8982047

What OpenQuestion holds

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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.