Evidence map›Paper›PMID 28249985›Full record

ArticleGenetics2017

Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples.

Bernard Y Kim, Christian D Huber, Kirk E Lohmueller

Abstract read
In one paragraph

Article in Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 163 papers.

0numbers the graph read from it
0cells of the map it votes in
163citing 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

163 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. AScience advances · 2026
    Article
  6. Article
  7. Article
  8. Pervasive cryptic selection in the human noncoding genome.bioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Evolutionary dynamics under phenotypic uncertainty.bioRxiv : the preprint server for biology · 2026
    Article
  14. Neural posterior estimation for population genetics.bioRxiv : the preprint server for biology · 2026
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

103 more citing papers are in PubMed but not listed here.

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.

Bernard Y KimDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095.
Christian D HuberDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095.
Kirk E LohmuellerDepartment of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095 klohmueller@ucla.edu.

Funding

Population genomics of the selective effects of new mutationsR35GM119856 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LOHMUELLER, KIRK · 2016 to 2025
$3.4M
NIGMS NIH HHS R35 GM119856
6 · The paper itself

Abstract

The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38-0.84 fold) strongly deleterious mutations with selection coefficient |

Indexed as

Evolution, MolecularGenetic FitnessGenetics, PopulationSequence Analysis, DNAExomeHigh-Throughput Nucleotide SequencingHumansModels, GeneticMutationSample SizeSelection, GeneticWhite Peopledeleterious mutationsdiffusion theorypopulation geneticssite frequency spectrum

Identifiers

PMID28249985
PMCPMC5419480

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.