GenePattern Team Blog


Creating a GenePattern Module

Posted on Saturday, December 15, 2012 at 11:36AM by The GenePattern Team

The following tutorial shows you how to create a new GenePattern module (in GenePattern 3.4 and up). Only the GenePattern team can create or install modules on the GenePattern public server. Therefore, to create a module, you need to have a local GenePattern server installed (see the download and …

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Importing Data from caArray to GenePattern

Posted on Tuesday, October 30, 2012 at 12:36PM by The GenePattern Team

Overview

caArray is an open-source, web and programmatically accessible array data management system. caArray guides the annotation and exchange of array data using a federated model of local installations whose results are shareable across the cancer Biomedical Informatics Grid (caBIG®). caArray furthers translational cancer research through acquisition, dissemination and aggregation …

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October 2012 Java 6 update and GenePattern visualizer issues

Posted on Friday, October 26, 2012 at 02:47PM by David Eby

UPDATE MARCH 17, 2017 : Java applet visualizers no longer work in any browser. Please click here to read the blog post.


(Originally posted 2012-11-09)

Oracle recently released an update to their Java 6 platform which could cause problems for GenePattern users.  The update disables the underlying technologies used by several …

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GenePattern blog

Posted on Friday, October 26, 2012 at 01:49PM by David Eby

Welcome to the GenePattern blog!  We are launching this as a place where we can post important news and announcements for the GenePattern community with more detail than can fit into a system announcement or tweet. Feel free to give us feedback and ask questions using the Comments section below …

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Using ComparativeMarkerSelection for Differential Expression Analysis

Posted on Sunday, September 30, 2012 at 12:32PM by The GenePattern Team

Overview

In GenePattern, you use the ComparativeMarkerSelection module to identify the genes (if any) that are differentially expressed between two phenotype classes. Typically, this is a three-step process:

  1. Run the PreprocessDataset module to preprocess the expression data.
    PreprocessDataset removes platform noise and genes that have little variation. It takes an …

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