Evidence map›Paper›PMID 26883445›Full record

ArticleGenetics2016

The Site Frequency Spectrum for General Coalescents.

Jeffrey P Spence, John A Kamm, Yun S Song

Abstract read
In one paragraph

Article in Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Scaling the Discrete-time Wright Fisher model to biobank-scale datasets.bioRxiv : the preprint server for biology · 2023
    Article
  8. Article
  9. Article
  10. Nonparametric coalescent inference of mutation spectrum history and demography.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  11. Article
  12. Article
  13. The multifurcating skyline plot.Virus evolution · 2019
    Article
  14. Article
  15. Article
  16. Article
  17. Explosive genetic evidence for explosive human population growth.Current opinion in genetics & development · 2016
    Review
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.

Jeffrey P SpenceComputational Biology Graduate Group, University of California, Berkeley, California 94720.
John A KammDepartment of Statistics, University of California, Berkeley, California 94720.
Yun S SongDepartment of Statistics, University of California, Berkeley, California 94720 Computer Science Division, University of California, Berkeley, California 94720 Department of Integrative Biology, University of California, Berkeley, California 94720 Department of Mathematics, University of Pennsylvania, Philadelphia, Pennsylvania 19104 Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 yss@berkeley.edu.

Funding

GENOMICST32HG000047 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI RASMUS NIELSEN, Daniel Soleyman Rokhsar · 2000 to 2026
$13.5M
Population Genetic Consequences of Recent Explosive Population Growth in HumansR01GM108805 · NIGMS · CORNELL UNIVERSITY · PI CLARK, ANDREW G, KEINAN, ALON · 2014 to 2017
$2.2M
NHGRI NIH HHS T32 HG000047NHGRI NIH HHS T32-HG000047NIGMS NIH HHS R01 GM108805NIGMS NIH HHS R01-GM108805
6 · The paper itself

Abstract

General genealogical processes such as Λ- and Ξ-coalescents, which respectively model multiple and simultaneous mergers, have important applications in studying marine species, strong positive selection, recurrent selective sweeps, strong bottlenecks, large sample sizes, and so on. Recently, there has been significant progress in developing useful inference tools for such general models. In particular, inference methods based on the site frequency spectrum (SFS) have received noticeable attention. Here, we derive a new formula for the expected SFS for general Λ- and Ξ-coalescents, which leads to an efficient algorithm. For time-homogeneous coalescents, the runtime of our algorithm for computing the expected SFS is O(n2) where n is the sample size. This is a factor of[Formula: see text]faster than the state-of-the-art method. Furthermore, in contrast to existing methods, our method generalizes to time-inhomogeneous Λ- and Ξ-coalescents with measures that factorize as[Formula: see text] and [Formula: see text]respectively, where ζ denotes a strictly positive function of time. The runtime of our algorithm in this setting is[Formula: see text]We also obtain general theoretical results for the identifiability of the Λ measure when ζ is a constant function, as well as for the identifiability of the function ζ under a fixed Ξ measure.

Indexed as

AlgorithmsModels, TheoreticalModels, Geneticfrequency spectrumidentifiabilitymultiple mergersimultaneous merger

Identifiers

PMID26883445
PMCPMC4827730

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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.