Non-parametric MANOVA methods for detecting differentially expressed genes in real-time RT-PCR experiments

Niccoló Bassani, Federico Ambrogi, Roberta Bosotti, Matteo Bertolotti, Antonella Isacchi, Elia Biganzoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

RT-PCR is a quantitative technique of molecular biology used to amplify DNA sequences starting from a sample of mRNA, typically used to explore gene expression variation across groups of treatment. Because of the non-normal distribution of data, non-parametric methods based on the MANOVA approach and the use of permutations to obtain global F-ratio tests have been proposed to deal with this problem. The issue of analyzing univariate contrasts is addressed via Steel-type tests. Results of a study involving 30 mice assigned to 5 differents treatment regimens are presented. MANOVA methods detect an effect of treatment on gene expression, with good agreement between methods. These results are potentially useful to draw out new biological hypothesis to be verified in following designed studies. Future research will focus on comparison of such methods with classical strategies for analysing RT-PCR data; moreover, work will also concentrate on extending such methods to doubly multivariate design.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages56-69
Number of pages14
Volume6160 LNBI
DOIs
Publication statusPublished - 2010
Event6th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2009 - Genoa, Italy
Duration: Oct 15 2009Oct 17 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6160 LNBI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2009
CountryItaly
CityGenoa
Period10/15/0910/17/09

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Keywords

  • gene expression
  • MANOVA
  • non-parametric
  • permutations
  • RT-PCR

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Bassani, N., Ambrogi, F., Bosotti, R., Bertolotti, M., Isacchi, A., & Biganzoli, E. (2010). Non-parametric MANOVA methods for detecting differentially expressed genes in real-time RT-PCR experiments. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6160 LNBI, pp. 56-69). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6160 LNBI). https://doi.org/10.1007/978-3-642-14571-1_5