Evidence map›Paper›PMID 40017563›Full record

ArticleJournal of the American Statistical Association2022

A Minimax Optimal Ridge-Type Set Test for Global Hypothesis with Applications in Whole Genome Sequencing Association Studies.

Yaowu Liu, Zilin Li, Xihong Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Statistical Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Ensemble methods for testing a global null.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2024
    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

3 authors.

Yaowu LiuSchool of Statistics at the Southwestern University of Finance and Economics.
Zilin LiDepartment of Biostatistics at Harvard T.H. Chan School of Public Health.
Xihong LinBiostatistics at Harvard T.H. Chan School of Public Health and Professor of Statistics at Harvard University.

Funding

The Human Genome Sequencing CenterU54HG003273 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A · 2004 to 2015
$341.3M
Genomic Architecture of Common Disease in Diverse Populations: WGS of Ongoing Hemorrhagic Stroke Study SupplementUM1HG008898 · NHGRI · BAYLOR COLLEGE OF MEDICINE · PI GIBBS, RICHARD A · 2016 to 2020
$77.0M
Building on GWAS for NHLBI-disease: the CHARGE consortiumRC2HL102419 · NHLBI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A. · 2009 to 2010
$27.6M
Translating Molecular and Clinical Data to Population Lung Cancer Risk AssessmentU19CA203654 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Christopher I. Amos, Rayjean J. Hung · 2017 to 2026
$23.7M
Statistical Methods for Analysis of Massive Genetic and Genomic Data in Cancer ResearchR35CA197449 · NCI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2015 to 2026
$10.9M
Superfund Metal Mixtures, Biomarkers and NeurodevelopmentP42ES016454 · NIEHS · HARVARD SCHOOL OF PUBLIC HEALTH · PI BELLINGER, DAVID C · 2010 to 2015
$10.1M
Statistical Methods for the Spatio-Temporal Assessment of Social Disparities in CancerP01CA134294 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANEUSE, SEBASTIEN, HERNAN, MIGUEL · 2008 to 2017
$6.8M
Powering whole genome sequence-based genetic discovery for common human diseases- Extended 2021-2022.U01HG009088 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI LIN, XIHONG, NEALE, BENJAMIN MICHAEL · 2016 to 2021
$5.1M
Leveraging Family Data to Identify Genetic Variants for Sleep ApneaR01HL113338 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LIN, XIHONG, REDLINE, SUSAN S. · 2012 to 2016
$4.4M
Predictive Modeling of the Functional and Phenotypic Impacts of Genetic VariantsU01HG012064 · NHGRI · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI Manuel Garber, XIHONG LIN · 2021 to 2026
$4.0M
Statistical Methods for Integrative Analysis of Large-Scale Whole Genome Sequencing Studies and Biobanks of Common DiseasesR01HL163560 · NHLBI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI XIHONG LIN · 2022 to 2026
$2.6M
NCI NIH HHS P01 CA134294NCI NIH HHS R35 CA197449NCI NIH HHS U19 CA203654NHGRI NIH HHS U01 HG009088NHGRI NIH HHS U01 HG012064NHGRI NIH HHS U54 HG003273NHGRI NIH HHS UM1 HG008898NHLBI NIH HHS HHSN268201700001CNHLBI NIH HHS HHSN268201700001INHLBI NIH HHS HHSN268201700002CNHLBI NIH HHS HHSN268201700002INHLBI NIH HHS HHSN268201700003CNHLBI NIH HHS HHSN268201700003INHLBI NIH HHS HHSN268201700004CNHLBI NIH HHS HHSN268201700004INHLBI NIH HHS HHSN268201700005CNHLBI NIH HHS HHSN268201700005INHLBI NIH HHS R01 HL113338NHLBI NIH HHS R01 HL163560NHLBI NIH HHS RC2 HL102419NIEHS NIH HHS P42 ES016454
6 · The paper itself

Abstract

Testing a global hypothesis for a set of variables is a fundamental problem in statistics with a wide range of applications. A few well-known classical tests include the Hotelling's

Indexed as

F-testGlobal hypothesis testingRobust powerScore testSignal strengthVariant set testWhole genome sequencing studies

Identifiers

PMID40017563
PMCPMC11865954

What OpenQuestion 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 OpenQuestion graph.