Journal article Open Access

Key aspects of analyzing microarray gene-expression data

Chen, James J.


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  <dc:creator>Chen, James J.</dc:creator>
  <dc:date>2007-05-01</dc:date>
  <dc:description>One major challenge with the use of microarray technology is the analysis of massive amounts of gene-expression data for various applications. This review addresses the key aspects of the microarray gene-expression data analysis for the two most common objectives: class comparison and class prediction. Class comparison mainly aims to select which genes are differentially expressed across experimental conditions. Gene selection is separated into two steps: gene ranking and assigning a significance level. Class prediction uses expression profiling analysis to develop a prediction model for patient selection, diagnostic prediction or prognostic classification. Development of a prediction model involves two components: model building and performance assessment. It also describes two additional data analysis methods: gene-class testing and multiple ordering criteria.</dc:description>
  <dc:identifier>https://zenodo.org/record/1236433</dc:identifier>
  <dc:identifier>10.2217/14622416.8.5.473</dc:identifier>
  <dc:identifier>oai:zenodo.org:1236433</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/publicdomain/zero/1.0/legalcode</dc:rights>
  <dc:title>Key aspects of analyzing microarray gene-expression data</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
</oai_dc:dc>
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