Microarrays are a widespread technology mostly used to explore expression profiles for thousand of genes simultaneously. On the other hand, considerable efforts to understand inter-relationships between groups of genes were made. To this end, multivariate visualization techniques (e.g. biplots) and Partial Least Squares regression have gained relevance in the field of genomic research. Biplots provide a graphical aid to understand mutual relationships between genes and samples and among gene themselves but no dependency is implied; use of passive projection of variables, however, is helpful for understanding conditional relationships between different sets of genes. Additionally, PLS regression provides a framework for quantitatively evaluating these dependencies and for assessing which are the relevant interactions that should be deeper investigated in further studies. These techniques have been applied on a subset of a microarray study on 49 samples of malignant pleural mesothelioma. 70 genes were selected, 62 involved in cell-cell junctions disruption and 8 involved in Epithelial-Mesenchymal Transition (EMT). Since these latter are supposed to play a role in subsequent loss of apicobasal cell polarity, analysis were performed considering EMT genes as the conditioning (i.e. independent) variables and the polarity genes as conditioned (i.e. dependent) variables. PLS regression provided results consistent with those obtained from graphical visualization of EMT genes principal components and passive projections of polarity genes, and helped in detecting relevant associations between different sets of genes. These associations should be investigated in further studies for validation. Future work will address the differential pattern of expression according to histotype of subjects in the PLS framework. Moreover, PLS path modeling will be considered after the specification of a detailed dependency network.

Use of biplots and Partial Least Squares regression in microarray data analysis for assessing association between genes involved in different biological pathways / N.P. Bassani, F. Ambrogi, D. Coradini, E. Biganzoli. ((Intervento presentato al 7. convegno International Meeting on Computational Intelligence for Bioinformatics and Biostatistics tenutosi a Palermo nel 2010.

Use of biplots and Partial Least Squares regression in microarray data analysis for assessing association between genes involved in different biological pathways

N.P. Bassani
Primo
;
F. Ambrogi
Secondo
;
E. Biganzoli
Ultimo
2010-09-17

Abstract

Microarrays are a widespread technology mostly used to explore expression profiles for thousand of genes simultaneously. On the other hand, considerable efforts to understand inter-relationships between groups of genes were made. To this end, multivariate visualization techniques (e.g. biplots) and Partial Least Squares regression have gained relevance in the field of genomic research. Biplots provide a graphical aid to understand mutual relationships between genes and samples and among gene themselves but no dependency is implied; use of passive projection of variables, however, is helpful for understanding conditional relationships between different sets of genes. Additionally, PLS regression provides a framework for quantitatively evaluating these dependencies and for assessing which are the relevant interactions that should be deeper investigated in further studies. These techniques have been applied on a subset of a microarray study on 49 samples of malignant pleural mesothelioma. 70 genes were selected, 62 involved in cell-cell junctions disruption and 8 involved in Epithelial-Mesenchymal Transition (EMT). Since these latter are supposed to play a role in subsequent loss of apicobasal cell polarity, analysis were performed considering EMT genes as the conditioning (i.e. independent) variables and the polarity genes as conditioned (i.e. dependent) variables. PLS regression provided results consistent with those obtained from graphical visualization of EMT genes principal components and passive projections of polarity genes, and helped in detecting relevant associations between different sets of genes. These associations should be investigated in further studies for validation. Future work will address the differential pattern of expression according to histotype of subjects in the PLS framework. Moreover, PLS path modeling will be considered after the specification of a detailed dependency network.
Settore MED/01 - Statistica Medica
Use of biplots and Partial Least Squares regression in microarray data analysis for assessing association between genes involved in different biological pathways / N.P. Bassani, F. Ambrogi, D. Coradini, E. Biganzoli. ((Intervento presentato al 7. convegno International Meeting on Computational Intelligence for Bioinformatics and Biostatistics tenutosi a Palermo nel 2010.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/165241
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