Evidence map›Paper›PMID 32773169›Full record

ReviewTrends in genetics : TIG2020

Alternative Applications of Genotyping Array Data Using Multivariant Methods.

David C Samuels, Jennifer E Below, Scott Ness, Hui Yu, Shuguang Leng, Yan Guo

Open access · greenAbstract readReview
In one paragraph

Review in Trends in genetics : TIG, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 19% 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

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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Genetic Dissection and Functional Validation ofInternational journal of molecular sciences · 2026
    Article
  3. Article
  4. Article
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 4 institutions in 1 country.

David C SamuelsDepartment of Molecular Physiology and Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN 37232, USA.
Jennifer E BelowDevision of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA.
Scott NessDepartment of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA.
Hui YuDepartment of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA.
Shuguang LengDepartment of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA.
Yan GuoDepartment of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87109, USA. Electronic address: yanguo1978@gmail.com.
University of New Mexico · USNew Mexico Cancer Center · USVanderbilt University · USVanderbilt University Medical Center · US

Funding

WOMEN'S CANCERS RESEARCH PROGRAMP30CA118100 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Yolanda Sanchez · 2005 to 2026
$57.1M
NCI NIH HHS P30 CA118100
6 · The paper itself

Abstract

One of the forerunners that pioneered the revolution of high-throughput genomic technologies is the genotyping microarray technology, which can genotype millions of single-nucleotide variants simultaneously. Owing to apparent benefits, such as high speed, low cost, and high throughput, the genotyping array has gained lasting applications in genome-wide association studies (GWAS) and thus accumulated an enormous amount of data. Empowered by continuous manufactural upgrades and analytical innovation, unconventional applications of genotyping array data have emerged to address more diverse genetic problems, holding promise of boosting genetic research into human diseases through the re-mining of the rich accumulated data. Here, we review several unconventional genotyping array analysis techniques that have been built on the idea of large-scale multivariant analysis and provide empirical application examples. These unconventional outcomes of genotyping arrays include polygenic score, runs of homozygosity (ROH)/heterozygosity ratio, distant pedigree computation, and mitochondrial DNA (mtDNA) copy number inference.

Indexed as

GenomeGenome-Wide Association StudyPolymorphism, Single NucleotideAnimalsComputational BiologyGenomicsGenotypeGenotyping TechniquesHumansOligonucleotide Array Sequence Analysis

Identifiers

PMID32773169
PMCPMC7572808
OpenAlexW3047167141

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.