Detecting multivariate differentially expressed genes |
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| Authors: | Roland Nilsson José M Peña Johan Björkegren Jesper Tegnér |
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| Institution: | 1.Computational Biology, Department of Physics,Link?ping University,Link?ping,Sweden;2.Unit of Computational Medicine, King Gustaf V Research Institute, Department of Medicine,Karolinska Institutet,Stockholm,Sweden |
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| Abstract: | Background Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions
may therefore be complex and multivariate in nature. Yet, current statistical methods for detecting differential expression
merely consider the univariate difference in expression level of each gene in isolation, thus potentially neglecting many
genes of biological importance. |
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