A novel method for the analysis of Serial Analysis of Gene Expression (SAGE) data
A seriation approach for visualization-driven discovery of co-expression patterns in Serial Analysis of Gene Expression (SAGE) data.
This article reports on a novel application of the statistical method called seriation for the identification of co-expressed genes in Serial Analysis of Gene Expression Data (SAGE). The performance of seriation was compared to that of a state-of-the-art clustering method using simulated and real SAGE data. A particular advantage of seriation over clustering is the fewer number of false positive co-expressed genes identified by the method. The study suggests that the use of seriation in the analysis of expression data should be further examined.
Full citation
Morozova O, Morozov V, Hoffman B, Helgason CD, Marra MA. A Seriation Approach for Visualization-Driven Discovery of Co-Expression Patterns in Serial Analysis of Gene Expression (SAGE) Data. PLoS ONE. 2008 Sep. 3(9):e3205.
Further details of this publication can be found online at:
article via PLoS ONE http://dx.plos.org/10.1371/journal.pone.000320
Full citation
Morozova O, Morozov V, Hoffman B, Helgason CD, Marra MA. A Seriation Approach for Visualization-Driven Discovery of Co-Expression Patterns in Serial Analysis of Gene Expression (SAGE) Data. PLoS ONE. 2008 Sep. 3(9):e3205.
Further details of this publication can be found online at:
article via PLoS ONE http://dx.plos.org/10.1371/journal.pone.000320
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Dec 16, 2008