A novel tree-based procedure for deciphering the genomic spectrum of clinical disease entitiesReport as inadecuate

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Journal of Clinical Bioinformatics

, 4:6

First Online: 16 April 2014Received: 23 December 2013Accepted: 08 April 2014DOI: 10.1186-2043-9113-4-6

Cite this article as: Mbogning, C., Perdry, H., Toussile, W. et al. J Clin Bioinform 2014 4: 6. doi:10.1186-2043-9113-4-6


BackgroundDissecting the genomic spectrum of clinical disease entities is a challenging task. Recursive partitioning or classification trees methods provide powerful tools for exploring complex interplay among genomic factors, with respect to a main factor, that can reveal hidden genomic patterns. To take confounding variables into account, the partially linear tree-based regression PLTR model has been recently published. It combines regression models and tree-based methodology. It is however computationally burdensome and not well suited for situations for which a large number of exploratory variables is expected.

MethodsWe developed a novel procedure that represents an alternative to the original PLTR procedure, and considered different selection criteria. A simulation study with different scenarios has been performed to compare the performances of the proposed procedure to the original PLTR strategy.

ResultsThe proposed procedure with a Bayesian Information Criterion BIC achieved good performances to detect the hidden structure as compared to the original procedure. The novel procedure was used for analyzing patterns of copy-number alterations in lung adenocarcinomas, with respect to Kirsten Rat Sarcoma Viral Oncogene Homolog gene KRAS mutation status, while controlling for a cohort effect. Results highlight two subgroups of pure or nearly pure wild-type KRAS tumors with particular copy-number alteration patterns.

ConclusionsThe proposed procedure with a BIC criterion represents a powerful and practical alternative to the original procedure. Our procedure performs well in a general framework and is simple to implement.

KeywordsRecursive partitioning Tree-based regression Lung cancer Disease taxonomy Genomic Electronic supplementary materialThe online version of this article doi:10.1186-2043-9113-4-6 contains supplementary material, which is available to authorized users.

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Author: Cyprien Mbogning - Hervé Perdry - Wilson Toussile - Philippe Broët

Source: https://link.springer.com/

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