Motivation: The systematic integration of expression profiles and other types of gene information, such as chromosomal localization, ontological annotations and sequence characteristics, still represents a challenge in the gene expression arena. In particular, the analysis of transcriptional data in context of the physical location of genes in a genome appears promising in detecting chromosomal regions with transcriptional imbalances often characterizing cancer.Results: A computational tool named locally adaptive statistical procedure (LAP), which incorporates transcriptional data and structural information for the identification of differentially expressed chromosomal regions, is described. LAP accounts for variations in the distance between genes and in gene density by smoothing standard statistics on gene position before testing the significance of their differential levels of gene expression. The procedure smoothes parameters and computes p-values locally to account for the complex structure of the genome and to more precisely estimate the differential expression of chromosomal regions. The application of LAP to three independent sets of raw expression data allowed identifying differentially expressed regions that are directly involved in known chromosomal aberrations characteristic of tumors.

A locally adaptive statistical procedure (LAP) to identify differentially expressed chromosomal regions / Callegaro, A; Basso, D; Bicciato, Silvio. - In: BIOINFORMATICS. - ISSN 1367-4803. - STAMPA. - 22:21(2006), pp. 2658-2666. [10.1093/bioinformatics/btl455]

A locally adaptive statistical procedure (LAP) to identify differentially expressed chromosomal regions

BICCIATO, Silvio
2006

Abstract

Motivation: The systematic integration of expression profiles and other types of gene information, such as chromosomal localization, ontological annotations and sequence characteristics, still represents a challenge in the gene expression arena. In particular, the analysis of transcriptional data in context of the physical location of genes in a genome appears promising in detecting chromosomal regions with transcriptional imbalances often characterizing cancer.Results: A computational tool named locally adaptive statistical procedure (LAP), which incorporates transcriptional data and structural information for the identification of differentially expressed chromosomal regions, is described. LAP accounts for variations in the distance between genes and in gene density by smoothing standard statistics on gene position before testing the significance of their differential levels of gene expression. The procedure smoothes parameters and computes p-values locally to account for the complex structure of the genome and to more precisely estimate the differential expression of chromosomal regions. The application of LAP to three independent sets of raw expression data allowed identifying differentially expressed regions that are directly involved in known chromosomal aberrations characteristic of tumors.
2006
22
21
2658
2666
A locally adaptive statistical procedure (LAP) to identify differentially expressed chromosomal regions / Callegaro, A; Basso, D; Bicciato, Silvio. - In: BIOINFORMATICS. - ISSN 1367-4803. - STAMPA. - 22:21(2006), pp. 2658-2666. [10.1093/bioinformatics/btl455]
Callegaro, A; Basso, D; Bicciato, Silvio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/421441
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