Normalization and Gene p-Value Estimation: Issues in Microarray Data Processing | Zendy

Katrin Fundel | Zendy; Robert Küffner | Zendy; Thomas Aigner | Zendy; Ralf Zimmer | Zendy

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Normalization and Gene p-Value Estimation: Issues in Microarray Data Processing

Author(s) -

Katrin Fundel,

Robert Küffner,

Thomas Aigner,

Ralf Zimmer

Publication year - 2008

Publication title -

bioinformatics and biology insights

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.556

H-Index - 23

ISSN - 1177-9322

DOI - 10.4137/bbi.s441

Subject(s) - normalization (sociology) , gene expression profiling , microarray analysis techniques , computational biology , microarray , gene expression , dna microarray , gene chip analysis , database normalization , gene , biology , data set , data mining , computer science , bioinformatics , genetics , pattern recognition (psychology) , artificial intelligence , sociology , anthropology

Numerous methods exist for basic processing, e.g. normalization, of microarray gene expression data. These methods have an important effect on the final analysis outcome. Therefore, it is crucial to select methods appropriate for a given dataset in order to assure the validity and reliability of expression data analysis. Furthermore, biological interpretation requires expression values for genes, which are often represented by several spots or probe sets on a microarray. How to best integrate spot/probe set values into gene values has so far been a somewhat neglected problem.

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