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Filter Expression Matrix
CoExpression

v.1.2.2

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Filter an expression matrix using either Log Odds Ratio (LOR) or ANalysis of VAriance (ANOVA) algorithms.

This method filters differentially expressed genes from the Expression Matrix and generates a FeatureSet and filtered Expression Matrix. Begin by selecting or importing both the Expression Matrix and the Genome associated with the Expression Matrix using the Add Data button. If the Expression Matrix was not associated with a Genome when it was imported, please run the method Associate Expression Matrix to Genome Features on the Expression Matrix before running this method. Select either of the filter options that use the Number of Features, or a P-value cutoff to filter differentially expressed genes. If both the Number of Features and the P-value cutoff are populated, the method will default to using the Number of Features with the selected filtering method. Provide names for the output filtered Expression Matrix and FeatureSet and then run the method.

Description of filtering methods to do differential Expression:

Team members who developed & deployed algorithm in KBase: Shinjae Yoo, Paramvir Dehal, Roman Sutormin, Michael Sneddon, Srividya Ramakrishnan, Pavel Novichkov, Keith Keller, Sunita Kumari, Priya Ranjan, Fei He, Jim Thomason, Vivek Kumar.

For questions, e-mail help@kbase.us


App Specification:

https://github.com/sjyoo/coexpression/tree/77803912cdb5fb1ed2535add11ccaa04bcb678f3/ui/narrative/methods/expression_toolkit_filter_expression

Module Commit: 77803912cdb5fb1ed2535add11ccaa04bcb678f3