Index

• P-SCAN Functions
• Pre-requisites and installation
• How to operate P-SCAN
• Step 1. To generate a file containing spot intensities and addresses
• Step 2. To compare spot intensities between different filters and generate a list of over and underexpressed genes
• Step 3. To visually examine pairs of spots reported as differentially expressed
• Step 4. For sophisticated statistical analysis, to prepare a file containing intensities of all filters to be opened in statistical packages like JMP
• Reference
• Contact information
• Acknowledgement

P-SCAN Functions:

Step 1: For each image generate a file containing spot intensities and addresses.

Step 2: Compare spot intensities between different filters and generate a list of over and under expressed genes.

Step 3: Visually examine pairs of spots reported as differentially expressed.

Step 4: For sophisticated statistical analysis, prepare a file containing intensities of all filters to be opened in statistical packages like JMP. JMP provides a user with a three way connection between a replica of the image, scatter plot/histogram, and peak intensities. Having observed the scatter plot, one can trace its features to actual locations in the filter. Conversely one can subtract defective artifactual areas on a filter from the scatter plot and remove their distorting influences. Also multiple scatter plots for time course studies are possible within this package.

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Pre-requisites and installation:

1) ~128 MB RAM

2) P-SCAN (http://abs.cit.nih.gov/pscan) is written in MATLAB.
 

Install MATLAB 5.2 (http://www.mathworks.com) before using P-SCAN.

Set MATLAB memory to ~128 MB.

Place the P-SCAN directory on your hard disk.

APPEND P-SCAN to the MATLAB path as follows:

     MAC  users should click on the icon with a picture of two folders.  This activates the MATLAB Path browser.  On the left side of the path browser, find the P-SCAN folder and highlight it.  Click on the APPEND button in the center of the path browser.  Finally, click on the Save button in the bottom right of the path browser and then close.

    PC  users should click on the icon with a picture of two folders.  This activates the MATLAB Path browser.  Click on the Browse button to locate the P-SCAN folder.  Next, click in the space labeled "Current Directory" to insure the P-SCAN path is highlighted.  Then select the Path menu item "Add to Path..."    Most importantly, select "Add to back".   Then click OK.  Finally, from the File menu of the Path Browser choose "Save Path"  and exit the Path Browser.

     UNIX  users should cd to their home directory and create a directory there called
matlab
In the matlab directory, create a file startup.m containing the following
path(path,'insert pscan path here')
where 'insert pscan path here' should be replaced by the location of pscan on the users computer;  for example, '/usr/people/pscanuser/P-SCAN_1.2'

     MATLAB 6.1  users should click on the File menu and select "Set Path". In the Set Path window, click the "Add Folder..." button, locate the P-SCAN_1.2 folder, and highlight it with a single click. Then click "OK". Next, click the "Move to Bottom" button. Finally, click Save and Close.

In the command window type "pscan".

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How to operate P-SCAN:

Step 1. To generate a file containing spot intensities and addresses:

1. For images from MOLECULAR DYNAMICS scanners proceed to B.


For images from FUJI scanners, create an info file for each image and place it in the same directory as the image. The info file is obtained from the "FILE" menu item of MacBas. The name of the info file is the image name plus the ending ".inf".

2. Type "pscan" in the MATLAB command window.


Click the OK button.

Choose one company from the menu.

In some cases a menu for choosing the source (for example, human, mouse, rat, etc.) may also appear, and the source of the filter must be selected.
Choose the first track "Find spot intensities in an image".

Find the file containing the image by using the dialog box and click
"open".

Choose one of 2 scanner types.

The image should now be visible.

3. If many filters are in one file, crop to one filter. While cropping try to allow a boundary of 1 cm around the image. Cropping is accomplished by clicking twice - first in the upper left hand corner then in the lower right hand corner.
4. Enter 3 letters in the file naming box. The output file will contain these 3 letters. It is used to distinguish between different filters on the same image.
5. One needs to orient the image parallel to the margins with the first row of landing lights at the top. To accomplish this click on two spots within one column of dots. The first dot will be for the bottom orientation and the second for the top of the desired final

position of the image. Clicking on two dots calculates the angle of inclination of the image and rotates it through that angle.
6. Clicking on the "CHECK ALIGNMENT" button draws cross hairs. Check if one column of spots lines up along the vertical hair and if one row of spots lines up along the horizontal hair. If not, redo the rotation. If satisfied with the alignment click "Proceed". The image is converted into logarithmic scale.
7. For most filters, the image must be segmented into constituent grids. To accomplish this, click as closely as possible to (but not directly on) the top left spot and bottom right spot. You can redo this step if necessary. If satisfied press "proceed".
8. The program presents one segment at a time for grid placement. Click the top left and bottom right spots and a grid will be laid on one segment. One can alter this grid by using buttons on the window or redoing it entirely. Click "proceed" to continue through the remaining segments of the image.
9. After grids have been placed on all segments, P-SCAN evaluates peak heights of all spots and prints out a file with addresses and intensities of all spots.

Step 2. To compare spot intensities between different filters and generate a list of over and underexpressed genes:

[Note to GLASS users - make sure a gene list file is stored on the computer.]

1.  
1. If entering P-SCAN anew, type "pscan" in the MATLAB command window. Otherwise, proceed to A-2.


Click the OK button.

Choose one company from the menu

Choose second track "Compare pairs of files interactively".

2. If already in P-SCAN, return to the "MAIN MENU".


Choose the second track "Compare pairs of files interactively".

2. Choose one output file from P-SCAN (1st .pXX file).


Choose the file for the comparison (2nd .pXX file).

Choose the gene list.

P-SCAN draws a scatter plot and presents it on a log-log scale. The rectangular box depicts the background cutoff. Spots above the upper (lower) line are over (under) expressed 2-fold. To examine spots 3, 5, 10, 100, 1000 fold over/under click the appropriate button on the left.

One can manually alter the background cutoff as well as the upper/lower lines. Click on the desired button on the right. The old lines disappear and cross hairs appear. Click at the desired location and the new line(s) will pass through that point. The altered numerical values will appear on the message boxes.

3. Click the "Show genes over/under" button to see a list of gene names and ratios together with addresses. This window obscures the scatter plot. After examining the gene list you can return to the scatter plot by closing the gene list window (click the box at the upper left corner of the window to close it).

 
4. To save files containing over/underexpressed genes click the "Save

genes over/under" button.

Step 3. To visually examine pairs of spots reported as differentially expressed:

Having compared two images, one obtains a list of spots differentially expressed by a significant amount. One would like to visually verify the differential expression by referring back to relevant areas in the original filters. Here we provide a tool wherein the reader can supply the address of a given spot and obtain slices of an image centered at that spot in a given number of filters. This enables a visual verification of the authenticity of the calculated difference, or a dismissal of the same as having resulted either from bleeds of neighbouring spots or some other artifact.

Users must supply lists of addresses of the spots they would like to visualise. This can be done in two ways: a) enter the address one at a time using the keyboard. b) enter an entire file of addresses. This can be done by reading in an output file from track 3 or by saving a file of genes expressed over/under from the scatter plot in track 2 and reading this file in.

1. If one is comparing only a few spots (4-5) proceed to B. If one is perusing a long list of spots, have a file ready as explained in the introduction of this step before proceeding to B.
2.  
1. If entering P-SCAN anew, type "pscan" in the MATLAB command window.


Click the OK button.

Choose one company from the menu.

Choose third track "Compare filter images at address".

2. If already in P-SCAN, return to "MAIN MENU".


Choose third track "Compare filter images at address"

3. Change the directory in the dialog box into one which contains files being compared. All files that are to be compared to each other should reside in one directory. Provide an output file name for a file that will receive data in this track. (This file is created only if the button "add to list" is clicked in F.)
4. Choose all the .mat files of filters being compared.


(If these were produced with older versions of P-SCAN, the user may be prompted for the names of the .pXX files, as well. P-SCAN may also prompt the user to select the .mat files which correspond with the .pXX files.)

5. To compare only a few spots, click "Input from keyboard" and enter the addresses by hand.


To enter a list by file name click "input from file" and choose the file in the dialog box.

6. Image slices of corresponding spots will be presented to you per address. To save information pertaining to a pair, click "Add to list"; otherwise, click "Skip".

Step 4. For sophisticated statistical analysis, to prepare a file containing intensities of all filters to be opened in statistical packages like JMP:

JMP provides a user with a three way connection between a replica of the image scatter plot/histogram and peak intensities. Having observed the scatter plot, one can trace its features to actual locations in the filter. Conversely, one can subtract defective artifactual areas on a filter from the scatter plot and remove their distorting influences. Also, multiple scatter plots tracing time courses are available in this package.

One needs a single file containing peak intensities of all filters under study for this analysis. This track creates such a file with the following features:

1. two columns per image - peak heights (arithmetical) and the logarithm of peak heights
2. four columns per pair of images (A and B) compared: A/B,B/A,log(A)-log(B),log(B)-log(A)
3. gene list as supplied by the company.

We add layout information that enables drawing a replica of the filter and also information on spot kind.

1. Choose Track 4 "Combine several files into one".
2. For images where the lattice reliably locates the spot center choose P1 (or P3 for Genome Systems); otherwise choose P2 (or P4 for Genome Systems) as peak heights.

 
3. Choose the gene list that corresponds to the filters chosen.
4. In the list box choose files of all images that are to be collectively studied. To do so, change the directory in the dialog box to that which contains the files to be combined. All of these files should reside in one directory. Provide a name for the combined output file in the lower portion of the dialog box.
5. Choose files that are to be paired in comparison. Doing so will ensure that ratios of peak heights between them (arithmetical and logarithmic) are made available in the output file.
6. Clicking "Next" creates one combined output file (to be opened in JMP).

"Development of a Prostate cDNA Microarray and Statistical Gene Expression Analysis Package"; A. J. Carlisle, V. V. Prabhu, A. Elkahloun, J. Hudson, J. M. Trent, W. M. Linehan, E. D. Williams, M. R. Emmert-Buck, L. A. Liotta, P. J. Munson, and D. B. Krizman; Molecular Carcinogenesis 28:12-22 (2000)

Contact information

P. J. Munson munson@helix.nih.gov, V. V. Prabhu prabhu@helix.nih.gov, and L. Young lynny@helix.nih.gov

Analytical Biostatistics Section; Mathematical and Statistical Computing Laboratory; Center for Information Technology; Building 12A, Room 2039; National Institutes of Health; Bethesda, MD 20892

Acknowledgement

This manual was translated into HTML by Eric Faden.

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Last modified 24 September 1999