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For an introduction to using the DE, see Using the Discovery Environment. Please work through the tutorial and add your comments on the bottom of this page, or email comments to support@cyverse.org. Thank you. |
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SARTools does not intend to replace edgeR: it simply provides an environment to go with them. For more details about the methodology behind edgeR, the user should read their documentation and papers. In addition, the current app is not intended to perform edgeR's GLM. That version is currently under progress. |
Introduction and Overview
DESeq2 estimates differentially expressed gene lists based on a negative binomial distribution model. Previous methods for identifying differentially expressed gene lists assumed a Poisson distribution; however, Poisson does not account for variation (or overdispersion) found in expression data. DESeq2 uses a negative binomial distribution (similar to edgeR), assuming variance in the case of few replicates.
The input is a tab-delimited file containing genes and their expression values. The results include files detailing the results of differential expression testing (one that includes all of the results, and one that only includes the results that exceed a minimum false-discovery rate). Also included for visualization purposes are plots of the estimated dispersions, the log fold changes against the mean normalized counts and a histogram of p-values. The plots are purely for visualization purposes and may not be necessary for all users.
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