TY - GEN
T1 - Use of biplots and partial least squares regression in microarray data analysis for assessing association between genes involved in different biological pathways
AU - Bassani, Niccoló
AU - Ambrogi, Federico
AU - Coradini, Danila
AU - Biganzoli, Elia
PY - 2011
Y1 - 2011
N2 - Microarrays are widely used to study expression profiles for thousand of transcripts simultaneously and to explore inter-relationships between sets of genes. Visualization techniques and Partial Least Squares (PLS) regression have thus gained relevance in genomic. Biplots provide an aid to understand relationships between genes and samples and among genes, whereas passive projections of variables are helpful for understanding conditional relationships between sets of genes to be quantitatively evaluated via PLS regression. 62 genes involved in loss of cell polarity and 8 involved in Epithelial-Mesenchymal Transition (EMT), were selected from a study on 49 mesothelioma samples, and analysis considered EMT genes as conditioning and polarity genes as conditioned variables. PLS regression results are consistent with the PCA-based biplot of EMT genes and with passive projections of polarity genes. Future work will address sparsity in PCA and PLS regression. PLS path modeling will be considered after specification of a detailed dependency network.
AB - Microarrays are widely used to study expression profiles for thousand of transcripts simultaneously and to explore inter-relationships between sets of genes. Visualization techniques and Partial Least Squares (PLS) regression have thus gained relevance in genomic. Biplots provide an aid to understand relationships between genes and samples and among genes, whereas passive projections of variables are helpful for understanding conditional relationships between sets of genes to be quantitatively evaluated via PLS regression. 62 genes involved in loss of cell polarity and 8 involved in Epithelial-Mesenchymal Transition (EMT), were selected from a study on 49 mesothelioma samples, and analysis considered EMT genes as conditioning and polarity genes as conditioned variables. PLS regression results are consistent with the PCA-based biplot of EMT genes and with passive projections of polarity genes. Future work will address sparsity in PCA and PLS regression. PLS path modeling will be considered after specification of a detailed dependency network.
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U2 - 10.1007/978-3-642-21946-7_10
DO - 10.1007/978-3-642-21946-7_10
M3 - Conference contribution
AN - SCOPUS:80051697932
SN - 9783642219450
VL - 6685 LNBI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 123
EP - 134
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 7th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2010
Y2 - 16 September 2010 through 18 September 2010
ER -