Evidence map›Paper›PMID 29959179›Full record

ArticleGenetics2018

Significance Testing for Allelic Heterogeneity.

Yangqing Deng, Wei Pan

Abstract read
PubMed Full text at PMC Publisher
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 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.

  1. Article
  2. Review
  3. Article
  4. Article
  5. A powerful and versatile colocalization test.PLoS computational biology · 2020
    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

2 authors.

Yangqing DengDivision of Biostatistics, University of Minnesota, Minneapolis, Minnesota 55455.
Wei PanDivision of Biostatistics, University of Minnesota, Minneapolis, Minnesota 55455 weip@biostat.umn.edu.

Funding

Association analysis of rare variants with sequencing dataR01HL116720 · NHLBI · UNIVERSITY OF MINNESOTA · PI PAN, WEI, WEI, PENG · 2013 to 2020
$3.3M
Powerful Inference and Prediction for Genetic AssociationR01HL105397 · NHLBI · UNIVERSITY OF MINNESOTA · PI PAN, WEI, SHEN, XIAOTONG TOM · 2011 to 2018
$2.9M
Estimation and Inference of Gene Regulatory NetworksR01GM126002 · NIGMS · UNIVERSITY OF MINNESOTA · PI PAN, WEI, SHEN, XIAOTONG TOM · 2017 to 2020
$1.4M
Statistical Methods for Genomic DataR01GM113250 · NIGMS · UNIVERSITY OF MINNESOTA · PI PAN, WEI · 2014 to 2017
$702k
Integrating genomic and imaging endophenotypes in GWASR21AG057038 · NIA · UNIVERSITY OF MINNESOTA · PI PAN, WEI · 2017 to 2018
$405k
NHLBI NIH HHS R01 HL105397NHLBI NIH HHS R01 HL116720NIA NIH HHS R21 AG057038NIGMS NIH HHS R01 GM113250NIGMS NIH HHS R01 GM126002
6 · The paper itself

Abstract

It is useful to detect allelic heterogeneity (AH),

Indexed as

AllelesBayes TheoremData Interpretation, StatisticalGene FrequencyGenetic HeterogeneityGenome-Wide Association StudyGenotypeHumansLinkage DisequilibriumModels, GeneticPhenotypePolymorphism, Single NucleotideQuantitative Trait LociSequence Analysis, DNACAVIARconditional/joint modelingGWASintersection-union teststatistical power

Identifiers

PMID29959179
PMCPMC6116971

What OpenQuestion holds

Textmetadata
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.