Welcome to the Comparing Copy Number Variations Between Tumors and Normals Using the Affymetrix MIP Array Tutorial!ΒΆ

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Updated: February 7th, 2012

Level: Intermediate

Packages: CNV Analysis Package, Power Seat

Contents: Jump to Table of Contents

This tutorial leads you through analyzing MIP (Molecular Inversion Probe) copy number data, as provided by Affymetrix, to detect differences between 17 normal and 25 tumor samples. Though this tutorial applies specifically to Affymetrix MIP data, the concepts can be applied to any copy number project where two or more sets of samples are being compared.

Requirements

To complete this tutorial you will need to download and unzip the following file, which includes several datasets.

Files included in the above ZIP file:

  • Affy MIP CN 300K Marker Map.dsm - MIP Marker Map file
  • MIP CN Transformation.doc - MIP CN Transformation script documentation
  • MIP CN Transformation.py - MIP CN Transformation script
  • MIP_Copy_Number.txt - Example Copy Number Data
  • MIP_Sample_Table.xls - Sample Dataset

Download the data, MIP Marker Map/Annotation and MIP CN Transformation script above. For more information about the script see: http://www.goldenhelix.com/SNP_Variation/scripts/pages/MIPCNTransformation.html

Save the Affy MIP CN 300K Marker Map.dsm file to your SVS Marker Maps directory. You can access this directory by opening SVS and going to Tools > Open Folder > Marker Maps Folder. Another way to access this folder, and also view and manage all marker maps, is through the Manage Marker Maps window. To access this window, choose Tools > Manage Marker Maps. From here you could click on the View MarkerMaps Folder button (Figure 1) to access the same directory.

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Figure 1. Manage Marker Maps window

Save the MIP CN Transformation.py file to the following directory: *..\Application Data\Golden Helix SVS\UserScripts\Spreadsheet\Edit\

You can access this directory by opening SVS and going to Tools > Open Folder > User Scripts Folder and then navigating to Spreadsheet \ Edit.

Next topic

1. Importing and Transforming MIP and Sample Data