Spatiotemporal ICA improves the selection of differentially expressed genes

نویسندگان

  • Emilie Renard
  • Andrew E. Teschendorff
  • P.-A. Absil
چکیده

Selecting differentially expressed genes with respect to some phenotype of interest is a difficult task, especially in the presence of confounding factors. We propose to use a spatiotemporal independent component analysis to model those factors, and to combine information from different spatiotemporal parameter values to improve the set of selected genes. We show on real datasets that the proposed method allows to significantly increase the proportion of genes related to the phenotype of interest in the final selection.

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تاریخ انتشار 2016