PLRS: a flexible tool for the joint analysis of DNA copy number and mRNA expression data

G.G.R. Leday; M. van de Wiel

doi:10.1093/bioinformatics/btt082

PLRS: a flexible tool for the joint analysis of DNA copy number and mRNA expression data

G.G.R. Leday, M. van de Wiel

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Abstract

DNA copy number and mRNA expression are commonly used data types in cancer studies. Available software for integrative analysis arbitrarily fixes the parametric form of the association between the two molecular levels and hence offers no opportunities for modelling it. We present a new tool for flexible modelling of this association. PLRS uses a wide class of interpretable models including popular ones and incorporates prior biological knowledge. It is capable to identify the gene-specific type of relationship between gene copy number and mRNA expression. Moreover, it tests the strength of the association and provides confidence intervals. We illustrate PLRS using glioblastoma data from The Cancer Genome Atlas. © 2013 The Author.

Original language	English
Pages (from-to)	1081-1082
Journal	Bioinformatics
Volume	29
Issue number	8
DOIs	https://doi.org/10.1093/bioinformatics/btt082
Publication status	Published - 2013

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10.1093/bioinformatics/btt082

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abstract = "DNA copy number and mRNA expression are commonly used data types in cancer studies. Available software for integrative analysis arbitrarily fixes the parametric form of the association between the two molecular levels and hence offers no opportunities for modelling it. We present a new tool for flexible modelling of this association. PLRS uses a wide class of interpretable models including popular ones and incorporates prior biological knowledge. It is capable to identify the gene-specific type of relationship between gene copy number and mRNA expression. Moreover, it tests the strength of the association and provides confidence intervals. We illustrate PLRS using glioblastoma data from The Cancer Genome Atlas. {\textcopyright} 2013 The Author.",

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AB - DNA copy number and mRNA expression are commonly used data types in cancer studies. Available software for integrative analysis arbitrarily fixes the parametric form of the association between the two molecular levels and hence offers no opportunities for modelling it. We present a new tool for flexible modelling of this association. PLRS uses a wide class of interpretable models including popular ones and incorporates prior biological knowledge. It is capable to identify the gene-specific type of relationship between gene copy number and mRNA expression. Moreover, it tests the strength of the association and provides confidence intervals. We illustrate PLRS using glioblastoma data from The Cancer Genome Atlas. © 2013 The Author.

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PLRS: a flexible tool for the joint analysis of DNA copy number and mRNA expression data

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