- GenePattern - Landing Page
GenePattern provides hundreds of analytical tools for the analysis of gene expression (RNA-seq and microarray), sequence variation and copy number, proteomic, flow cytometry, and network analysis These tools are all available through a Web interface with no programming experience required
- GenePattern - RNA-seq Analysis
GenePattern offers a set of tools to support a wide variety of RNA-seq analyses, including short-read mapping, identification of splice junctions, transcript and isoform detection, quantitation, differential expression, quality control metrics, visualization, and file utilities
- GenePattern - Differential Expression Tutorial
The GenePattern Tutorial introduces you to GenePattern by providing step-by-step instructions for analyzing gene expression It takes approximately 40 minutes to complete Note that this hands on tutorial was created with GenePattern 3 8 0
- GenePattern - Concepts
When you download GenePattern, you install a local GenePattern server You can install a local server on a standalone machine for your personal use or on a networked machine for use by several people or an entire organization
- GenePattern - Gene Expression Analysis
The GenePattern server provides links to a GenePattern library for the Java, MATLAB, and R programming environments, which allow application developers to read and write all GenePattern standard file formats
- GenePattern - Quick Start
Note that this video tutorial was created with GenePattern 3 2 This brief tutorial introduces you to GenePattern by providing step-by-step instructions for running an analysis and viewing the results
- GenePattern - User Guide
Only the GenePattern team can create, edit, or install modules on the GenePattern public server Therefore, to edit a module, you must have a local GenePattern server installed (see Starting Your Own GenePattern Server)
- GenePattern - Frequently Asked Questions
GenePattern modules cannot analyze files with missing values If your data has missing values, one way to address the issue is to use the ImputeMissingValues KNN module to impute the missing values Your data is now in a GCT file that can be analyzed by most GenePattern modules
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