Quick Start

See the video tutorial: Getting Started
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. In less than 10 minutes you'll run your first analysis and review the results.
Note that this hands on tutorial was created with GenePattern 3.6

Start GenePattern

To start GenePattern:

  1. Open a web browser, such a Mozilla Firefox, Internet Explorer, or Safari.
  2. Enter the URL of the public GenePattern server:https://cloud.genepattern.org/.
  3. Enter your user name and password and then click Sign In.
    If you do not have a GenePattern account, select Click to register.

    GenePattern displays its home page.

1 Click the GenePattern icon to return to this home page at any time.
2 The upper right corner shows your user name.
3 The navigation bar provides access to other pages.
4 The Modules & Pipelines panel lists the analyses that you can run. Enter the first few characters of a module or pipeline name in the search box to locate that analysis. Click the all radio button to list the analyses alphabetically.
5 The center pane is the main display pane, which GenePattern uses to display information and to prompt you for input. Notice the protocols listed here.
6 The Recent Jobs panel lists the most recent analyses that you have run and their results files. The Uploads panel lists files that you have copied to the GenePattern server. When you start GenePattern for the first time, these panels are empty.

Run an Analysis

As an example, you will run the ComparativeMarkerSelection analysis. This analysis finds the genes in a dataset file that are most closely correlated with the two classes of samples in that dataset. You will run the analysis on an example dataset, all_aml_train.res, that contains gene expression data from Golub and Slonim et al. (1999). In that paper, the authors used clustering and prediction algorithms to find genes that distinguish between two subtypes of leukemia, ALL and AML. The dataset consists of 38 bone marrow samples (27 ALL, 11 AML) obtained from acute leukemia patients.

To run the ComparativeMarkerSelection analysis:

  1. In the Modules & Pipelines panel, locate and select ComparativeMarkerSelection. One easy way to do this: type the first few characters of the name into the search box and click on ComparativeMarkerSelection when it appears in the list of matching analyses.

    GenePattern displays the ComparativeMarkerSelection parameters.

  2. For the input file parameter, click the Add Path or URL button and enter the following URL: https://datasets.genepattern.org/data/all_aml/all_aml_train.gct
  3. For the cls file parameter, click the Add Path or URL button and enter the following URL: https://datasets.genepattern.org/data/all_aml/all_aml_train.cls

  4. Click Run to start the analysis. GenePattern sends the analysis job to the GenePattern server and displays the Job Status page. After a few moments, GenePattern changes the status icon from running running to complete complete and displays the analysis results.

View the Analysis Results

To examine the results of the ComparativeMarkerSelection analysis, run the ComparativeMarkerSelectionViewer:

  1. Click the menu icon icon next to the all_aml_train.comp.marker.odf results file to display a menu of the commands you can use to work with the file.
  2. From the menu, select ComparativeMarkerSelectionViewer.

    GenePattern displays the ComparativeMarkerSelectionViewer parameters. The comparative marker selection filename parameter is automatically set to the all_aml_train.comp.marker.odf results file.

  3. For the dataset filename parameter, click the Add Path or URL button and select the file that you analyzed using the ComparativeMarkerSelection module: https://datasets.genepattern.org/data/all_aml/all_aml_train.gct .

  4. Click Run to start the viewer.
  5. The ComparativeMarkerSelectionViewer appears:

  6. In the ComparativeMarkerSelectionViewer:
    • The Score column shows the value of the metric used to correlate gene expression and phenotype. A high score indicates correlation with the first phenotype (upregulated in ALL) and a low score indicates correlation with the second phenotype (upregulated in AML).
    • The middle columns, FDR through FWER, provide different ways to measure the significance of the score. The lower the value the more significant the result. For example, you might choose to measure significance using the false discovery rate (FDR) and set a significance cutoff of FDR < .05. Using this measure, you would focus on genes with the lowest and highest scores, where the measure of significance for the score was an FDR < .05.
  7. In GenePattern, click Modules & Pipelines to return to the home page.

On the home page, the Recent Jobs pane shows the analysis jobs that you have run on the GenePattern server and the associated analysis results files. Click the job name or number for an analysis to redisplay the Job Status page for that job.

Exit from GenePattern

To exit from GenePattern:

  1. Click Sign Out in the top right corner of the title bar.
  2. Close the web browser window.

Learn More about GenePattern

The following documents provide more information about GenePattern:

Concepts Introduces GenePattern: its primary objects (modules, pipelines, suites) and its client-server architecture. Other GenePattern documentation assumes that you are familiar with this information.
Video Tutorials Lists the GenePattern training videos.
Tutorial Provides a 40 minute hands-on tour of GenePattern.
User Guide Fully describes GenePattern.
Modules Lists the modules and pipelines available from the Broad Institute, with links to their documentation.
File Formats Describes all file formats and provides instructions for creating input files for GenePattern.
Release Notes Describes new features and known issues in the current release.
Frequently Asked Questions Answers commonly asked questions about GenePattern.

We welcome your feedback. If you have suggestions, comments, or questions please visit our forum https://groups.google.com/g/genepattern-help.