A two-sample tree-based test for hierarchically organized genomic signals

Abstract This article addresses a common type of data encountered in genomic studies, where a signal along a linear chromosome exhibits a hierarchical organization. We propose a novel framework to assess the significance of dissimilarities between two sets of genomic matrices obtained from distinct...

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Published inJournal of the Royal Statistical Society Series C: Applied Statistics Vol. 73; no. 3; pp. 774 - 795
Main Authors Neuvial, Pierre, Randriamihamison, Nathanaël, Chavent, Marie, Foissac, Sylvain, Vialaneix, Nathalie
Format Journal Article
LanguageEnglish
Published UK Oxford University Press 01.06.2024
Wiley
Subjects
Biotechnology
Chromosomes
Computer Science
Genomics
Life Sciences
Mathematics
Matrices
Modeling and Simulation
Statistics
Trees
moderated
tree distances
value aggregation
cophenetic distances
statistics
moderated t statistics
p-value aggregation
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ISSN0035-9254
1467-9876
DOI10.1093/jrsssc/qlae011

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Summary:Abstract This article addresses a common type of data encountered in genomic studies, where a signal along a linear chromosome exhibits a hierarchical organization. We propose a novel framework to assess the significance of dissimilarities between two sets of genomic matrices obtained from distinct biological conditions. Our approach relies on a data representation based on trees. It utilizes tree distances and an aggregation procedure for tests performed at the level of leaf pairs. Numerical experiments demonstrate its statistical validity and its superior accuracy and power compared to alternatives. The method’s effectiveness is illustrated using real-world data from GWAS and Hi-C data.
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ISSN:0035-9254
1467-9876
DOI:10.1093/jrsssc/qlae011