Evidence map›Paper›PMID 18928554›Full record

ArticleBMC genetics2008

Calculating expected DNA remnants from ancient founding events in human population genetics.

Andrew Stacey, Nathan C Sheffield, Keith A Crandall

Abstract read
In one paragraph

Article in BMC genetics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Andrew StaceyDepartment of Statistics, Brigham Young University, Provo, UT 84602, USA. Andrew.Stacey@osumc.edu
Nathan C Sheffield
Keith A Crandall

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent advancements in sequencing and computational technologies have led to rapid generation and analysis of high quality genetic data. Such genetic data have achieved wide acceptance in studies of historic human population origins and admixture. However, in studies relating to small, recent admixture events, genetic factors such as historic population sizes, genetic drift, and mutation can have pronounced effects on data reliability and utility. To address these issues we conducted genetic simulations targeting influential genetic parameters in admixed populations.

resultsWe performed a series of simulations, adjusting variable values to assess the affect of these genetic parameters on current human population studies and what these studies infer about past population structure. Final mean allele frequencies varied from 0.0005 to over 0.50, depending on the parameters.

conclusionThe results of the simulations illustrate that, while genetic data may be sensitive and powerful in large genetic studies, caution must be used when applying genetic information to small, recent admixture events. For some parameter sets, genetic data will not be adequate to detect historic admixture. In such cases, studies should consider anthropologic, archeological, and linguistic data where possible.

Indexed as

Genetics, PopulationSequence Analysis, DNAComputer SimulationGene FrequencyGenetic DriftHumansMutation

Identifiers

PMID18928554
PMCPMC2588638

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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.