Beware of risk for increased false positive rates in genome-wide association studies for phenotypic variability

Beware of risk for increased false positive rates in genome-wide association studies for phenotypic variability

Bibliographic Details
Main Authors:	Xia eShen, Örjan eCarlborg
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2013-05-01
Series:	Frontiers in Genetics
Subjects:	genome-wide association studies phenotypic variability genetic variance heterogeneity type I error rate false positive rate
Online Access:	http://journal.frontiersin.org/Journal/10.3389/fgene.2013.00093/full

Similar Items

An evaluation of the genome-wide false positive rates of common methods for identifying differentially methylated regions using illumina methylation arrays
by: Yuanchao Zheng, et al.
Published: (2022-12-01)

Commentary: Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates
by: Karsten Mueller, et al.
Published: (2017-06-01)

Comprehensive Comparative Analysis of Local False Discovery Rate Control Methods
by: Shin June Kim, et al.
Published: (2021-01-01)

False Discovery Rate Control in Cancer Biomarker Selection Using Knockoffs
by: Arlina Shen, et al.
Published: (2019-05-01)

Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma
by: Lin eLi, et al.
Published: (2013-05-01)

Aggregating Knockoffs for False Discovery Rate Control with an Application to Gut Microbiome Data
by: Fang Xie, et al.
Published: (2021-02-01)

Weighted multiple testing procedures in genome-wide association studies
by: Ludivine Obry, et al.
Published: (2023-06-01)

Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data
by: Yang Wu, et al.
Published: (2017-05-01)

Appraisal of cytohistomorphology of papillary carcinoma thyroid and its variants with evaluation of discrepant cases
by: Supreetha Megalamane, et al.
Published: (2022-01-01)

Big little lies: a compendium and simulation of p-hacking strategies
by: Angelika M. Stefan, et al.
Published: (2023-02-01)

PASE: a novel method for functional prediction of amino acid substitutions based on physicochemical properties
by: Xidan eLi, et al.
Published: (2013-03-01)

Understanding one-way ANOVA using conceptual figures
by: Tae Kyun Kim
Published: (2017-02-01)

Accounting for heterogeneity in false‐positive detection rate in southeastern beach mouse habitat occupancy models
by: Eric D. Stolen, et al.
Published: (2019-10-01)

The Influence of False Cardiac Feedback on Autonomic Markers of Arousal
by: Marie Kuřátková, et al.
Published: (2019-09-01)

Quantile-Adaptive Sufficient Variable Screening by Controlling False Discovery
by: Zihao Yuan, et al.
Published: (2023-03-01)

Cardiac Troponin and the True False Positive∗
by: James L. Januzzi, Jr., MD, et al.
Published: (2020-03-01)

An investigation of the false discovery rate and the misinterpretation of p-values
by: David Colquhoun
Published: (2014-01-01)

Technical variability of 2D gel electrophoresis – Application to soybean allergens
by: Catherine Pallen, et al.
Published: (2014-01-01)

A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets
by: Hanaa Naouma, et al.
Published: (2019-12-01)

Weighted multiple testing procedures for genomic studies
by: Gui Jiang, et al.
Published: (2012-06-01)

Are false positives in suicide classification models a risk group? Evidence for “true alarms” in a population-representative longitudinal study of Norwegian adolescents
by: E. F. Haghish, et al.
Published: (2023-09-01)

False Alarm Analysis of the CATM-CFAR in Presence of Clutter Edge
by: D. Ivković, et al.
Published: (2014-04-01)

Closed‐form expressions and statistical analysis of constant false alarm rate detection in multiple false target jamming condition
by: Xiaozhou Chen, et al.
Published: (2022-12-01)

A direct approach to estimating false discovery rates conditional on covariates
by: Simina M. Boca, et al.
Published: (2018-12-01)

Reduction of False Positives for Runtime Errors in C/C++ Software: A Comparative Study
by: Jihyun Park, et al.
Published: (2023-08-01)

All tests are imperfect: Accounting for false positives and false negatives using Bayesian statistics
by: Song S. Qian, et al.
Published: (2020-03-01)

Lessons from a genome-wide CRISPR-Cas9 screening: what researchers should know before start
by: Mohammad Masoudi
Published: (2021-12-01)

How to use analysis of variance correctly——the multiple comparisons among the multiple means
by: Hu Chunyan, et al.
Published: (2022-02-01)

Inconsistency in prevalence of hypertension based on self-reports and use of standard tests: Implications for large scale surveys
by: Shri Kant Singh, et al.
Published: (2022-09-01)

An improved algorithm based on Bloom filter and its application in bar code recognition and processing
by: Mai Jiang, et al.
Published: (2018-12-01)

Common causes of false positive F18 FDG PET/CT scans in oncology
by: Kevin R. Carter, et al.
Published: (2007-09-01)

The method of vicinity minutiae decomposition with higher level graphs for fingerprint verification
by: Sergiy Rassomakhin, et al.
Published: (2021-11-01)

A Potential Pitfall in POCUS of the Gallbladder: Beware of the Duodenum
by: Fan Yang, et al.
Published: (2022-11-01)

Effectiveness of <i>R1-nj</i> Anthocyanin Marker in the Identification of In Vivo Induced Maize Haploid Embryos
by: Luis Antonio Lopez, et al.
Published: (2023-06-01)

The vagaries of IgM: a case report of EBV infection with concomitantly false-positive IgM for CMV, VZV, and HSV
by: Raai Mahmood, et al.
Published: (2020-09-01)

Genome-wide genetic links between amyotrophic lateral sclerosis and autoimmune diseases
by: Chun Yu Li, et al.
Published: (2021-02-01)

Estimating the Proportion of True Null Hypotheses for Multiple Comparisons
by: R.W. Doerge, et al.
Published: (2008-01-01)

Asymptotic Properties of MSE Estimate for the False Discovery Rate Controlling Procedures in Multiple Hypothesis Testing
by: Sofia Palionnaya, et al.
Published: (2020-11-01)

Using controls to limit false discovery in the era of big data
by: Matthew M. Parks, et al.
Published: (2018-09-01)

False negatives of screening in large-scale population
by: XU Ning, et al.
Published: (2022-05-01)