2023
DOI: 10.1002/pmic.202200406
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Controlling for false discoveries subsequently to large scale one‐way ANOVA testing in proteomics: Practical considerations

Abstract: In discovery proteomics, as well as many other “omic” approaches, the possibility to test for the differential abundance of hundreds (or of thousands) of features simultaneously is appealing, despite requiring specific statistical safeguards, among which controlling for the false discovery rate (FDR) has become standard. Moreover, when more than two biological conditions or group treatments are considered, it has become customary to rely on the one‐way analysis of variance (ANOVA) framework, where a first glob… Show more

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Cited by 3 publications
(2 citation statements)
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“…Exploratory factor analysis, Bartlett's tests, and the Kaiser-Meyer-Olkin (KMO) index were used to evaluate the construct validity (34). Correlations between variables were examined using Pearson correlation analysis, group comparisons were conducted using t-tests, and comparisons across multiple groups were assessed using ANOVA (35).…”
Section: Methodsmentioning
confidence: 99%
“…Exploratory factor analysis, Bartlett's tests, and the Kaiser-Meyer-Olkin (KMO) index were used to evaluate the construct validity (34). Correlations between variables were examined using Pearson correlation analysis, group comparisons were conducted using t-tests, and comparisons across multiple groups were assessed using ANOVA (35).…”
Section: Methodsmentioning
confidence: 99%
“…When comparing the differences between groups with different screw insertion depths, a one-way ANOVA was used for these continuous variables. A p -value less than 0.05 indicated a significant difference ( Burger, 2023 ; Chatzi and Doody, 2023 ).…”
Section: Toggle Tests Under Different Loading Protocolsmentioning
confidence: 99%