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Journal Article

MACAT—microarray chromosome analysis tool

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Heinig,  Matthias
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Georgi,  Benjamin
Max Planck Society;

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Citation

Toedling, J., Schmeier, S., Heinig, M., Georgi, B., & Roepcke, S. (2005). MACAT—microarray chromosome analysis tool. Bioinformatics, 21(9), 2112-2113. doi:10.1093/bioinformatics/bti183.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-8661-5
Abstract
By linking differential gene expression to the chromosomal localization of genes, one can investigate microarray data for characteristic patterns of expression phenomena involving sizeable parts of specific chromosomes. We have implemented a statistical approach for identifying significantly differentially expressed chromosome regions. We demonstrate the applicability of the approach on a publicly available data set on acute lymphocytic leukemia.