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Visual Mining Methods for RNA-Seq Data: Data Structure, Dispersion Estimation and Significance Testing
2013
Journal of Data Mining in Genomics & Proteomics
In an analysis of RNA-Seq data from soybeans, initial significance testing using one software package produced very different gene lists from those yielded by another. How can this happen? This paper demonstrates how the disparities between the results were investigated, and can be explained. This type of contradiction can occur more generally in high-throughput analyses. To explore the model fitting and hypothesis testing, we implemented an interactive graphic that allows the exploration of
doi:10.4172/2153-0602.1000139
fatcat:wigyxmzdcrfx7ak4mcykpyrs5a