Limitation of permutation-based differential correlation analysis.
Genet Epidemiol
; 47(8): 637-641, 2023 Dec.
Article
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| MEDLINE
| ID: mdl-37947279
ABSTRACT
The comparison of biological systems, through the analysis of molecular changes under different conditions, has played a crucial role in the progress of modern biological science. Specifically, differential correlation analysis (DCA) has been employed to determine whether relationships between genomic features differ across conditions or outcomes. Because ascertaining the null distribution of test statistics to capture variations in correlation is challenging, several DCA methods utilize permutation which can loosen parametric (e.g., normality) assumptions. However, permutation is often problematic for DCA due to violating the assumption that samples are exchangeable under the null. Here, we examine the limitations of permutation-based DCA and investigate instances where the permutation-based DCA exhibits poor performance. Experimental results show that the permutation-based DCA often fails to control the type I error under the null hypothesis of equal correlation structures.
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Base de datos:
MEDLINE
Asunto principal:
Genómica
Idioma:
En
Revista:
Genet Epidemiol
Asunto de la revista:
EPIDEMIOLOGIA
/
GENETICA MEDICA
Año:
2023
Tipo del documento:
Article