Evidence map›Paper›PMID 20622977›Full record

ArticleAnnual review of anthropology2008

Detecting the Genetic Signature of Natural Selection in Human Populations: Models, Methods, and Data.

Angela M Hancock, Anna Di Rienzo

Open access · greenAbstract read
In one paragraph

Article in Annual review of anthropology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% of its field
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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.

  1. Pooled it
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  20. Evolutionary lessons from California plant phylogeography.Proceedings of the National Academy of Sciences of the United States of America · 2016
    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 at 1 institution in 1 country.

Angela M HancockDepartment of Human Genetics, University of Chicago, Chicago, Illinois 60637.
Anna Di Rienzo
University of Chicago · US

Funding

PREDOCTORAL TRAINING IN GENETICS AND REGULATIONT32GM007197 · NIGMS · UNIVERSITY OF CHICAGO · PI ROTHMAN-DENES, LUCIA B. B · 1985 to 2020
$17.0M
POPULATION AND EVOLUTIONARY GENETICS OF NIDDMIR01DK056670 · NIDDK · UNIVERSITY OF CHICAGO · PI DI RIENZO, ANNA · 2001 to 2010
$3.2M
Local Adaptations in HumansR01GM079558 · NIGMS · UNIVERSITY OF CHICAGO · PI DI RIENZO, ANNA · 2007 to 2010
$1.2M
NIDDK NIH HHS R01 DK056670NIGMS NIH HHS R01 GM079558NIGMS NIH HHS T32 GM007197
6 · The paper itself

Abstract

Patterns of DNA sequence variation in the genome contain a record of past selective events. The ability to collect increasingly large data sets of polymorphisms has allowed investigators to perform hypothesis-driven studies of candidate genes as well as genome-wide scans for signatures of adaptations. This genetic approach to the study of natural selection has identified many signals consistent with predictions from anthropological studies. Selective pressures related to variation in climate, diet, and pathogen exposure have left strong marks on patterns of human variation. Additional signals of adaptations are observed in genes involved in chemosensory perception and reproduction. Several ongoing projects aim to sequence the complete genome of 1000 individuals from different human populations. These large-scale projects will provide data for more complete genome scans of selection, but more focused studies aimed at testing specific hypotheses will continue to hold an important place in elucidating the history of adaptations in humans.

Identifiers

PMID20622977
PMCPMC2901121
OpenAlexW2148105239

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.