Evidence map›Paper›PMID 32938925›Full record

ArticleNature communications2020

Factor analysis of ancient population genomic samples.

Olivier François, Flora Jay

Abstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
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  6. Methods for Assessing Population Relationships and History Using Genomic Data.Annual review of genomics and human genetics · 2023
    Review
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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.

Olivier François *Université Grenoble-Alpes, Centre National de la Recherche Scientifique, Grenoble INP, Laboratoire TIMC-IMAG UMR 5525, 38000, Grenoble, France. olivier.francois@univ-grenoble-alpes.fr.ORCID http://orcid.org/0000-0003-2402-2442
Flora Jay *Université Paris-Saclay, Centre National de la Recherche Scientifique, Inria, Laboratoire de Recherche en Informatique UMR 8623, Bâtiment 650 Ada Lovelace, 91405, Orsay Cedex, France. flora.jay@lri.fr.ORCID http://orcid.org/0000-0001-5884-4730

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent years have seen a growing number of studies investigating evolutionary questions using ancient DNA. To address these questions, one of the most frequently-used method is principal component analysis (PCA). When PCA is applied to temporal samples, the sample dates are, however, ignored during analysis, leading to imperfect representations of samples in PC plots. Here, we present a factor analysis (FA) method in which individual scores are corrected for the effect of allele frequency drift over time. We obtained exact solutions for the estimates of corrected factors, and we provided a fast algorithm for their computation. Using computer simulations and ancient European samples, we compared geometric representations obtained from FA with PCA and with ancestry estimation programs. In admixture analyses, FA estimates agreed with tree-based statistics, and they were more accurate than those obtained from PCA projections and from ancestry estimation programs. A great advantage of FA over existing approaches is to improve descriptive analyses of ancient DNA samples without requiring inclusion of outgroup or present-day samples.

Indexed as

Factor Analysis, StatisticalGenome, HumanAlgorithmsDNA, AncientEnglandEuropeGene FrequencyGenetic DriftGenetics, PopulationHumansMetagenomicsModels, GeneticPrincipal Component AnalysisDNA, Ancient

Identifiers

PMID32938925
PMCPMC7494920

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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.