Evidence map›Paper›PMID 33841491›Full record

ArticleFrontiers in genetics2021

Inference of Ancestries and Heterozygosity Proportion and Genotype Imputation in West African Cattle Populations.

Netsanet Z Gebrehiwot, Hassan Aliloo, Eva M Strucken, Karen Marshall, Mohammad Al Kalaldeh, Ayao Missohou, John P Gibson

Abstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

7 authors.

Netsanet Z GebrehiwotCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.
Hassan AlilooCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.
Eva M StruckenCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.
Karen MarshallInternational Livestock Research Institute and Centre for Tropical Livestock Genetics and Health, Nairobi, Kenya.
Mohammad Al KalaldehCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.
Ayao MissohouL'École Inter-États des Sciences et Médecine Vétérinaires de Dakar (EISMV), Dakar, Senegal.
John P GibsonCentre for Genetic Analysis and Applications, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several studies have evaluated computational methods that infer the haplotypes from population genotype data in European cattle populations. However, little is known about how well they perform in African indigenous and crossbred populations. This study investigates: (1) global and local ancestry inference; (2) heterozygosity proportion estimation; and (3) genotype imputation in West African indigenous and crossbred cattle populations. Principal component analysis (PCA), ADMIXTURE, and LAMP-LD were used to analyse a medium-density single nucleotide polymorphism (SNP) dataset from Senegalese crossbred cattle. Reference SNP data of East and West African indigenous and crossbred cattle populations were used to investigate the accuracy of imputation from low to medium-density and from medium to high-density SNP datasets using Minimac v3. The first two principal components differentiated

Indexed as

ADMIXTUREAfrican cattleglobal ancestryLAMP-LDlocal ancestryMinimacPCASNPs

Identifiers

PMID33841491
PMCPMC8025404

What OpenQuestion holds

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LicenceCC BY
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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.