ArticlePloS one2015
A Comparative Study of Tests for Homogeneity of Variances with Application to DNA Methylation Data.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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.
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Who cites it
8 citing papers in PubMed, 22 citations in OpenAlex.
- Data-Driven Identification of Early Cancer-Associated Genes via Penalized Trans-Dimensional Hidden Markov Models.Biomolecules · 2025Article
- Detecting genetic effects on phenotype variability to capture gene-by-environment interactions: a systematic method comparison.G3 (Bethesda, Md.) · 2024Review
- Assessing Differential Variability of High-Throughput DNA Methylation Data.Current environmental health reports · 2022Review
- A robust mean and variance test with application to high-dimensional phenotypes.European journal of epidemiology · 2022Review
- Integrative OMICS Data-Driven Procedure Using a Derivatized Meta-Analysis Approach.Frontiers in genetics · 2022Article
- Longitudinal DNA methylation differences precede type 1 diabetes.Scientific reports · 2020Article
- Robust joint score tests in the application of DNA methylation data analysis.BMC bioinformatics · 2018Article
- Detecting Differentially Variable MicroRNAs via Model-Based Clustering.International journal of genomics · 2018Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
Variable DNA methylation has been associated with cancers and complex diseases. Researchers have identified many DNA methylation markers that have different mean methylation levels between diseased subjects and normal subjects. Recently, researchers found that DNA methylation markers with different variabilities between subject groups could also have biological meaning. In this article, we aimed to help researchers choose the right test of equal variance in DNA methylation data analysis. We performed systematic simulation studies and a real data analysis to compare the performances of 7 equal-variance tests, including 2 tests recently proposed in the DNA methylation analysis literature. Our results showed that the Brown-Forsythe test and trimmed-mean-based Levene's test had good performance in testing for equality of variance in our simulation studies and real data analyses. Our results also showed that outlier profiles could be biologically very important.
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Registered trials
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.