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Protocol for Analysis of Mouse Membrane Array Data


Downloads:

The following downloads provide analysis tools for processing mouse membrane array data in a Windows-PC environment using Microsoft Office tools.  The macros embedded in these Microsoft Excel workbooks were designed to work with Clontech Atlas Mouse 1.2 arrays.  The macros are written in Visual Basic and can be modified in VB Editor for use with other array designs.


Statistical Considerations:

We routinely obtain 3 replicates of each experimental condition when using the Clontech Atlas arrays (single spots for each gene).  The uncertainty that lies behind individual gene measurements can be variously calculated as the standard deviation of the determinations or the coefficient of variation can be used.  Since we are usually interested in the statistical significance of differences between an experimental condition and a control, we prefer the student t-test as a means for calculating the probability, based on the uncertainty of the measurements in both conditions, that gene expression differs significantly between the conditions.  We use the standard deviation of the mean of the log ratios, within the context of the P value, to indicate significant up- or down-regulation of gene expression.  This approach is meaningful where the expression level of the majority of genes does not change significantly between conditions and where the researcher is interested in genes that show substantially different expression.  The standard deviation for the log ratios is calculated and only those genes that differ by more than 3 standard deviations (99.9% confidence in each tail) from the mean of the log ratio (usually zero, or no change) are considered.


Array Data Analysis in Excel:

The first VB macro, (embedded in MouseCruncher.xls) assigns the gene name to each spot by its coordinate (location) on the array and normalizes individual hybridization replicates by expressing the signal intensity for each spot as a percentage of the sum of all spot intensities. The second macro (embedded in MouseAnalysis.xls) streamlines statistical analysis of experimental replicates by application of the student t-test to calculate p-values that indicate confidence levels for the significance of the ratio of experimentals to controls, based on the uncertainty of individual genes in the 3 replicates, introduces a threshold value, calculates expression ratios between experimental and control conditions, and calculates an additional statistical metric, the standard deviation of the mean of the log ratios. Step-by-step instructions follow:

Open the workbook called "MouseCruncher", being sure to enable macros and open as read-only. [This workbook has two worksheets, named: ARVDATA and DataAnalysis. The "ARVDATA" worksheet is blank and the "data-analysis" worksheet contains annotation information to assign the gene name to each spot on the image.] Open the .XLS file that contains the exported raw data from Array Vision. Select colums A-C, and copy/paste this information into the blank "ARVDATA" worksheet of the "MouseCruncher" workbook beginning at cell A1. To run the macro, choose Tools on the toolbar, select Macros, highlight "allanalysis3" and click Run. Save the crunched data as "condition-replicate-crunched" following your standardized file-naming scheme.

The second workbook (MouseAnalysis) is used to execute the student t-test on two replicate data sets for two conditions and calculates the log ratio and the standard deviation of the mean of the log ratios. [The MouseAnalysis workbook has four worksheets named: "enterdata", "PRAW", "PLN",and "AllAnalysis".] Open the 6 "condition-replicate-crunched" files (3 each for control and experimental conditions) and the "MouseAnalysis" workbook. The 6 data sets are sequentially copied and pasted beginning with the first replicate of the control condition followed by the second and third replicates of the control, then the first, second, and third replicates of the experimental. Select columns A-C of the crunched data set in the "DataAnalysis" worksheet in the "condition-replicate-crunched" and copy/paste into the corresponding 3 columns of the "enterdata" worksheet in the "MouseAnalysis" workbook at the appropriate cell on row 1. The process is repeated for the remaining 5 replicates. To run the macro, choose Tools, select Macros, "AllAnalysis9", and click Run. Save the file as "condition-replicate-analysis", following your file-naming scheme. 


Workbooks and Macros

Workbook

Macro

Subroutine

Purpose

MouseCruncher allanalysis3

copy1

copies and pastes data from ARVDATA to DataAnalysis worksheets

MouseCruncher allanalysis3

calcpctl2

normalizes data by expressing each spot as percentage of sum of all spot intensities

Workbook

Macro

Subroutine

Purpose

MouseAnalysis AllAnalysis9

spotsort1

sorts the 6 data sets individually by spot number

MouseAnalysis AllAnalysis9

CalcAvg2

calculates averages of volumes and pct values for the control and test replicates

MouseAnalysis AllAnalysis9

copyvaluesintoPRaw3

copies and pastes pct values into a separate spreadsheet for calculation of p values

MouseAnalysis AllAnalysis9

CalcPRaw4

calculates the Pvalue for the raw data by application of the student t-test

MouseAnalysis AllAnalysis9

CalcLn5

copies pct values into a separate spreadsheet and natural log transforms data

MouseAnalysis AllAnalysis9

CalcPLn6

calculates the Pvalue for the log transformed data by application of the student t-test

MouseAnalysis AllAnalysis9

CopyValuesintoAnalysis7

copies and pastes data used for ratio calculations into separate spreadsheet

MouseAnalysis AllAnalysis9

CalculateRatios8

calculates ratio of Test/Control, reorganizes data, and calculates log (10) of ratio


Directory Structure:

Array Analysis
indent User Name
   indent Project Name
      indent Images (.gel TIFF image files)
      indent Export (.xls raw data files from ArrayVision)
      indent Crunched (.xls crunched image files created in "MouseCruncher")
      indent Analysis (.xls files with ratio calculations created in “MouseAnalysis”)

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OU Bioinformatics Core Facility @ Advanced Center for Genome Technology | Credits | updated:19 Oct 2005