A model-based scan statistic for identifying extreme chromosomal regions of gene expression in human tumors | Zendy

Albert M. Levin | Zendy; D. Ghosh | Zendy; Kathleen R. Cho | Zendy; Sharon L.R. Kardia | Zendy

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A model-based scan statistic for identifying extreme chromosomal regions of gene expression in human tumors

Author(s) -

Albert M. Levin,

D. Ghosh,

Kathleen R. Cho,

Sharon L.R. Kardia

Publication year - 2005

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bti417

Subject(s) - statistic , computational biology , gene , gene expression , gene expression profiling , human genome , classifier (uml) , dna microarray , false discovery rate , biology , computer science , genetics , genome , artificial intelligence , statistics , mathematics

The analysis of gene expression data in its chromosomal context has been a recent development in cancer research. However, currently available methods fail to account for variation in the distance between genes, gene density and genomic features (e.g. GC content) in identifying increased or decreased chromosomal regions of gene expression.

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