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 di erents treatment regimens are presented. MANOVA methods detect an e ect of treatment on gene expression, with good agreement between methods. These results are potentially useful to draw out new biological hypothesis to be veri ed 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.

Non-parametric MANOVA methods for detecting differentially expressed genes in real-time RT-PCR experiments / N.P. Bassani, F. Ambrogi, R. Bosotti, M. Bertolotti, A. Isacchi, E. Biganzoli - In: Computational intelligence methods for bioinformatics and biostatistics II : 6th international meeting, CIBB 2009, Genoa, Italy, October 15-17, 2009, revised selected papers / [a cura di] F. Masulli, L.E. Peterson, R. Tagliaferri. - New York : Springer, 2010. - ISBN 9783642145704. - pp. 56-69 (( Intervento presentato al 6. convegno International meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics tenutosi a Genova nel 2009 [10.1007/978-3-642-14571-1_5].

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

N.P. Bassani
Primo
;
F. Ambrogi
Secondo
;
E. Biganzoli
Ultimo
2010

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 di erents treatment regimens are presented. MANOVA methods detect an e ect of treatment on gene expression, with good agreement between methods. These results are potentially useful to draw out new biological hypothesis to be veri ed 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.
gene expression; MANOVA; non-parametric; permutations; RT-PCR
Settore MED/01 - Statistica Medica
http://hdl.handle.net/2434/146659
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/146761
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