Tutorial.1-channel
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Tutorial.1-channel

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VAMPIRE: One-channel Microarray Tutorial 2005.02.17 This tutorial will take you through the typical steps needed to interpret a set of one-channel microarray data. The data set used for this tutorial was obtained from a study of the effects of thiazolidinediones on 3T3-L1 adipocytes. We will use this set to explore the physiological responses of these cells to treatment. Sample Editor The first step will be to load the data set into the VAMPIRE microarray analysis platform through the sample editor. You will load the file “tutorial.1-channel.txt” as a table of measurements on the Affymetrix U74Av2 array. You may enter whatever description you wish. Note the file format of the tutorial file. Lines that are blank or are preceded by the # character are ignored. The first interpreted line contains the titles of each of the samples contained in the file. The first column contains the names of each feature. Each successive column contains gene expression measurements for each sample. Note: Data should not be log-transformed before loading into VAMPIRE. Normalized data from RMA, CORGON, dChip, etc should be used with caution, as these tools have profound effects on the variance structure, and can prevent the variance structure of the data from being adequately modeled. For Affymetrix chips, we recommend MAS 5.0/GCOS scores. For Agilent chips, we recommend the processed signal intensities. Group Editor Next, you will learn how to group related ...

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VAMPIRE: One-channel Microarray Tutorial
2005.02.17
This tutorial will take you through the typical steps needed to interpret a set of one-channel microarray
data. The data set used for this tutorial was obtained from a study of the effects of thiazolidinediones
on 3T3-L1 adipocytes. We will use this set to explore the physiological responses of these cells to
treatment.
Sample Editor
The first step will be to load the data set into the VAMPIRE microarray analysis platform through the
sample editor. You will load the file “tutorial.1-channel.txt” as a
table
of measurements on the
Affymetrix
U74Av2
array. You may enter whatever description you wish. Note the file format of the
tutorial file. Lines that are blank or are preceded by the # character are ignored. The first interpreted
line contains the titles of each of the samples contained in the file. The first column contains the
names of each feature. Each successive column contains gene expression measurements for each
sample.
Note: Data should
not
be log-transformed before loading into VAMPIRE. Normalized data from
RMA, CORGON, dChip, etc should be used with caution, as these tools have profound effects
on the variance structure, and can prevent the variance structure of the data from being
adequately modeled. For Affymetrix chips, we recommend MAS 5.0/GCOS scores. For Agilent
chips, we recommend the processed signal intensities.
Group Editor
Next, you will learn how to group related samples. For the analysis that we will be performing, it is
necessary to create groups for the conditions that we wish to compare.
Select the
U74Av2
array type and create the following groups:
Group name
Contents
control
con1, con2, con3
tzd
pio1, pio2, tzd3, tzd4, tzd5, tzd6, tzd7, tzd8
pio
pio1, pio2
Variance Modeler
With all of the necessary groups and categories defined, you will need to create an unpaired variance
model to estimate the error structure of the data set that you’ve submitted. Create an “unpaired” model
for each sample group. Be sure to select the
U74Av2
array type and select “none” for normalization.
Each time you click on “Build Model”, a job will be submitted to the database, which will be
processed in the order which it was received. If no other jobs are running, this step will typically take
about 20 minutes. In the meantime, we may go ahead and create the statistical test that we wish to run.
When the variance modeling job is completed, the model itself may be viewed by selecting it from the
navigation bar on the left. Parameter values and their MCMC simulation errors will be reported in the
results section of the page. In this section, there are a number of critical values that must be examined
to ensure the reliability of this analysis.
Check the following:
1. cutoff(quantile) should be a value greater than 0 and less than 0.8.
2. the A parameters should be similar between groups
3. the B parameters should be similar between groups
If any of these conditions are not true, the results of the significance test should be treated with caution,
because it is likely that the cutoff procedure was not able to identify a stable estimate of the variance
parameters. This can occur for a number of reasons:
1. the raw data was pre-processed with a complex normalization algorithm, introducing
normalization artifact
2. the raw data contains control probes that do not share the variance structure of the rest of the
data set (Agilent arrays)
Significance Tester
Finally, you will create a significance test based on the model that you created to identify which array
features are differentially-expressed between the two experimental conditions. Select the
U74Av2
array type, and create an “unpaired” test.
Select the following:
Sample group 1 – control
Sample group 2 – tzd
Variance model 1 – control
Variance model 2 – tzd
Create a second test with the following:
Sample group 1 – control
Sample group 2 – pio
Variance model 1 – control
Variance model 2 – pio
After an additional 10-15 minutes, this job should complete and you will be able to download the
results of the VAMPIRE analysis. Simply select the significance threshold that you desire, and click
download. The results may be downloaded either as a tab-delimited text file or as a VAMPIREResults
XML file.
GOby
GOby has two functions that may be useful for the interpretation of microarray data.
1. The “Annotate” function may be used to construct an annotated table of differentially-
expressed genes from multiple statistical tests.
2. Alternatively, you may wish to use GOby to identify functional groups that are
overrepresented in the list of differentially-expressed features. Click on “New” in the
navigation bar on the left. Then, simply select the test you wish to interpret, select a
significance threshold, and click “analyze”. The GOby analysis job will take approximately
30 minutes to complete. The results may subsequently be viewed as a series of HTML web
pages, or downloaded as GObyReport XML documents.