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Biomedical subjects

T Boes

Publications and source records attributed to T Boes.

2 recordsLinked to original sources

Normalization for Affymetrix GeneChips.

OBJECTIVES: The high density oligonucleotide microarrays from Affymetrix (Affymetrix GeneChips) are very popular in biomedical research. They enable to study the expression of thousands of genes simultaneously. In experiments with multiple arrays, normalization techniques are used to reduce the so-called obscuring variation, i.e. the technical variation that is of non-biological origin. Several different normalization methods have been proposed during the last years. METHODS: We review published results about the comparison of normalization methods proposed for Affymetrix GeneChips. RESULTS: The quantile normalization seems to perform favorably regarding precision (low variance), accuracy (low bias), and practicability (low computing time). However, according to very recent results, this normalization method can have an impact on the biological variability and, therefore, appears to be less than optimal from this point of view. CONCLUSION: Although the quantile normalization may be recommendable, more investigations based on more data sets are needed so that the different normalization methods can be evaluated on widely differing data.

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Software packages for quantitative microarray-based gene expression analysis.

Microarray technology enables researchers to investigate the expression of several thousand genes simultaneously. The whole transcriptional response of these genes in normal cells or tissue, in disease condition, as an response to biological, genetical or chemical stimuli or during normal biological processes such as cell cycle or embryonic development can be investigated. This leads to a huge amount of data, from which the relevant information has to be extracted by statistical and computational methods. Several software packages for the analysis of gene expression data are available, both commercially and freely. They differ particularly with regard to the implemented analytical methods, the graphical display and the manageability. In this paper the commercial software packages arraySCOUT, GeneSpring and Spotfire DecisionSite for Functional Genomics are compared and their applicability for analysis of gene expression data is studied. Small artificial and application test datasets are used to compare the computational results of the software packages. As far as possible results are verified with standard statistical software package SAS.

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