Chapter Four Exercises

1. Analyze two 4000-gene microarray experiments using ScanAlyze.

Download the following files from the GPL7 Accession File of human melanoma cDNA microarrays submitted by Michael Bittner's group to the Gene Expression Omnibus (GEO). Files GSM24, 27, 30, 35, and 36 contrast male melanoma samples with a melanoma reference sample, while files GSM13, 17, 32, 45, and 47 contrast female melanoma samples with the same reference sample. You can download the files directly from here (clicking file names above or get them all in a .zip file here), or access them through the GEO by choosing the SOFT format option and DATA amount option for each file. You may also wish to include several of the other microarray files from the same study in your exercise.

Start by extracting the relevant information concerning spot or pixel intensity and ratios from each of the 10 files that you have downloaded. This can be done in Microsoft Excel, or with a variety of other software packages. Does background subtraction make a difference? Is the total spot intensity of mean or median pixel intensity a better measure of expression? What does the standard deviation column indicate? Do you compute the same ratios of those given in the file?

2. Compare a variety of methods for computing ratios and normalizing the microarray data.

3. Perform an Analysis of Variance of a three-treatment experiment.

Perform an Analysis of Variance of the effect of sex and melanoma type in the sample dataset. You should have three different types of measurement: male melanomas (Channel 1 in each M file), female melanomas (channel 1 in each F file), and the reference standard (Channel 2 in each file—there are twice as many of these values).

4. Use the xProfiler at NCBI online

Use it to compare gene expression data from SAGE experiments for two tissue comparisons that are of interest to you.

5. Compare several methods for clustering the data in Exercise 3.

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