Tutorial:Chromosome Overview Networks in GenMAPP-CS

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This tutorial is still under construction.

This tutorial outlines a specialized GennMAPP-CS workflow for viewing data on chromosome maps. The main utility for this type of analysis is to assess whether there are patterns in the data localized to a certain chromosome or chromosome location. Chromosome maps for several species are available in xgmml format: human, mouse, rat, yeast, c.elegans, fruit fly.

For the purposes of this tutorial, we will use the mouse chromosome map and expression data from a mouse cell line. The data is available here and has been described here.

Note: The chromosome network used in this tutorial is large and may take a long time to load depending on the specifics of your system.

Load data

  • In the Database panel of Workspaces, select the mouse database. Detailed instructions on how to select a database are available in the Expression Analysis tutorial.
  • Import the data file under Import dataset from table... in the Actions menu. For detailed instructions on how to use the GenMAPP-CS Dataset Import, refer to the Expression Analysis tutorial.

Load network

  • From the Actions menu, select Open network file... and select the xgmml chromosome map.

chromosome map chromosome map detail

Structure of the chromosome map

The chromosome maps were created using information from Ensembl and have the following organization:

  • The map includes only protein coding genes.
  • Genes are arranged in horizontal lines representing chromosomes.
  • Each chromosome is organized into a positive and negative strand.
  • Genes all have the same arbitrary width and height, regardless of gene size.
  • Information on gene length and start and stop position are included as attributes.

Create criteria

  • Using the Criteria Mapper, create one criteria for genes over-expressed in the S49 cells as compared to wild type cells:

Criteria builder

Viewing the data on the network

Once you create, apply and save the criteria, the data will be displayed on the network and should look something like this:

Chromosome map with data

Genes meeting the criteria (up-regulated) are colored orange and genes not meeting the criteria are colored grey. Any gene not included in the data is colored white, and because of the scale of this map they are difficult to see at this resolution. However, even at this resolution it is clear that chromosome 6 has a large number of up-regulated genes as compared to other chromosomes. This apparent up-regulation is due to a duplication of chromosome 6 in the S49 cell line. Viewing data in the context of chromosome location can be a useful tool for identifying previously unknown chromosome abnormalities.