Evidence map›Paper›PMID 30131346›Full record

ArticleGenetics2018

Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data.

Jonas Meisner, Anders Albrechtsen

Abstract read
In one paragraph

Article in Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 348 papers.

0numbers the graph read from it
0cells of the map it votes in
348citing 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

348 citing papers in PubMed.

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288 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

2 authors.

Jonas MeisnerThe Bioinformatics Centre, Department of Biology, University of Copenhagen, DK-2200, Denmark jonas.meisner@bio.ku.dk.ORCID 0000-0002-9540-6673
Anders AlbrechtsenThe Bioinformatics Centre, Department of Biology, University of Copenhagen, DK-2200, Denmark.ORCID 0000-0001-7306-031X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We here present two methods for inferring population structure and admixture proportions in low-depth next-generation sequencing (NGS) data. Inference of population structure is essential in both population genetics and association studies, and is often performed using principal component analysis (PCA) or clustering-based approaches. NGS methods provide large amounts of genetic data but are associated with statistical uncertainty, especially for low-depth sequencing data. Models can account for this uncertainty by working directly on genotype likelihoods of the unobserved genotypes. We propose a method for inferring population structure through PCA in an iterative heuristic approach of estimating individual allele frequencies, where we demonstrate improved accuracy in samples with low and variable sequencing depth for both simulated and real datasets. We also use the estimated individual allele frequencies in a fast non-negative matrix factorization method to estimate admixture proportions. Both methods have been implemented in the PCAngsd framework available at http://www.popgen.dk/software/.

Indexed as

Gene FrequencyAnimalsGenetics, PopulationGenotypePrincipal Component AnalysisSequence Analysis, DNAadmixtureancestrygenotype likelihoodslow depthnext-generation sequencingPCAPopulation structure

Identifiers

PMID30131346
PMCPMC6216594

What OpenQuestion holds

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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.