Evidence map›Paper›PMID 26731477›Full record

ArticlePharmacogenetics and genomics2016

A comparison of DMET Plus microarray and genome-wide technologies by assessing population substructure.

Jami N Jackson, Kevin M Long, Yijing He, Alison A Motsinger-Reif, Howard L McLeod, John Jack

Abstract read
In one paragraph

Article in Pharmacogenetics and genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.4field-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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

6 authors at 3 institutions in 2 countries.

Jami N JacksonaDepartment of Statistics bBioinformatics Research Center, North Carolina State University cOrtelion LLC dPharmacogenetics for Every Nation Initiative, Raleigh, North Carolina eDeBartolo Family Personalized Medicine Institute, Moffitt Cancer Center, Tampa, Florida, USA fXiangya Hospital, Central South University, Changsha, China.
Kevin M Long
Yijing He
Alison A Motsinger-Reif
Howard L McLeod
John Jack
Central South University · CNMoffitt Cancer Center · USNorth Carolina State University · US

Funding

Biostatistics Training in the Omics EraT32GM081057 · NIGMS · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI MUSE, SPENCER V. · 2007 to 2019
$2.5M
NIGMS NIH HHS T32 GM081057
6 · The paper itself

Abstract

objectiveThe capacity of the Affymetrix drug metabolism enzymes and transporters (DMET) Plus pharmacogenomics genotyping chip to estimate population substructure and cryptic relatedness was evaluated. The results were compared with estimates using genome-wide HapMap data for the same individuals.

methodsFor 301 unrelated individuals, spanning three continental populations and one admixed population, genotypic data were collected using the Affymetrix DMET Plus microarray. Genome-wide data on these individuals were obtained from HapMap release 3. Population substructure was assessed using Eigenstrat and ADMIXTURE software for both platforms. Cryptic relatedness was explored by inbreeding coefficient estimation. Nonparametric tests were used to determine correlations of the analytical results of the two genotyping platforms.

resultsPrincipal components analysis identified population substructure for both datasets, with 15.8 and 16.6% of the total variance explained in the first two principal components for DMET Plus and HapMap data, respectively. ADMIXTURE results correctly identified four subpopulations within each dataset. Nonparametric rank correlations indicated significant associations between analyses with an average ρ=0.7272 (P<10) across the three continental populations and ρ=0.4888 for the admixed population. Concordance correlation coefficients (average ρc=0.9693 across all four subpopulations) strongly indicate concordance between ADMIXTURE results. Inbreeding coefficients were slightly inflated (16 individuals>0.15) using DMET Plus data and no cryptic relatedness was indicated using HapMap data. The inflated inbreeding estimation could be because of the limited number of markers provided by DMET as a random sample of 1832 markers from HapMap also yielded inflated estimates of cryptic relatedness (39 individuals>0.15). Furthermore, use of single nucleotide polymorphisms located in genes involved in metabolism and transport may have different allele frequencies in subpopulations than single nucleotide polymorphisms sampled from the whole genome.

conclusionThe DMET Plus pharmacogenomics genotyping chip is effective in quantifying population substructure across the three continental populations and inferring the presence of an admixed population. On the basis of our results, these microarrays offer sufficient depth for covariate adjustment of population substructure in genomic association studies.

Identifiers

PMID26731477
PMCPMC5746476
OpenAlexW2322396224

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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.