Title:
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Proportionality: a valid alternative to correlation for relative data
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Author:
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Lovell, David; Pawlowsky-Glahn, Vera; Egozcue Rubí, Juan José; Marguerat, Samuel; Baehler, Juerg
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Other authors:
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Universitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis |
Abstract:
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In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative-or compositional-data, differential expression needs careful interpretation, and correlation-a statistical workhorse for analyzing pairwise relationships-is an inappropriate measure of association. Using yeast gene expression data we show how correlation can be misleading and present proportionality as a valid alternative for relative data. We show how the strength of proportionality between two variables can be meaningfully and interpretably described by a new statistic. which can be used instead of correlation as the basis of familiar analyses and visualisation methods, including co-expression networks and clustered heatmaps. While the main aim of this study is to present proportionality as a means to analyse relative data, it also raises intriguing questions about the molecular mechanisms underlying the proportional regulation of a range of yeast genes. |
Abstract:
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Peer Reviewed |
Subject(s):
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-Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi matemàtica -Correlation (Statistics) -Molecular biology -Gene-expression -Fission yeast -Responses -Correlació (Estadística) -Biologia molecular |
Rights:
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http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type:
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Article - Published version Article |
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