BIOL398-01/S11:Week 11

From OpenWetWare

Revision as of 09:58, 29 March 2011 by Kam D. Dahlquist (Talk | contribs)
Jump to: navigation, search
BIOL398-01: Biomathematical Modeling

MATH 388-01: Survey of Biomathematics

Loyola Marymount University

Home       People        Metabolic Pathways       Gene Regulatory Pathways       LionShare       Help      

This journal entry is due on Tuesday, April 5 at midnight PDT (Wednesday night/Thursday morning). NOTE new due date and that the server records the time as Eastern Daylight Time (EDT). Therefore, midnight will register as 03:00.

Contents

Individual Journal Assignment

  • Store this journal entry as "username Week 11" (i.e., this is the text to place between the square brackets when you link to this page).
  • Create the following set of links. (HINT: you can do all of this easily by adding them to your template and then using the template on your pages.)
    • Link to your journal entry from your user page.
    • Link back from your journal entry to your user page.
    • Link to this assignment from your journal entry.
    • Don't forget to add the "BIOL398-01/S11" category to the end of your wiki page.

Microarray Data Analysis

Background

This is a list of steps required to analyze DNA microarray data.

  1. Quantitate the fluorescence signal in each spot
  2. Calculate the ratio of red/green fluorescence
  3. Log transform the ratios
  4. Normalize the ratios on each microarray slide
    • Steps 1-4 are performed by the GenePix Pro software.
    • You will perform the following steps:
  5. Normalize the ratios for a set of slides in an experiment
  6. Perform statistical analysis on the ratios
  7. Compare individual genes with known data
    • Steps 5-7 are performed in Microsoft Excel
  8. Pattern finding algorithms (clustering)
  9. Map onto biological pathways
    • We will use software called STEM for the clustering and mapping
  10. Create mathematical model of transcriptional network

Each group will analyze a different microarray dataset:

  • Wild type data from the Schade et al. (2004) paper you read last week.
  • Wild type data from the Dahlquist lab.
  • Δgln3 data from the Dahlquist lab.

For your assignment this week, you will keep an electronic laboratory notebook on your individual wiki page that records all the manipulations you perform on the data and the answers to the questions throughout the protocol.

You will download your assigned Excel spreadsheet from LionShare. Because the Dahlquist Lab data is unpublished, please do not post it on this public wiki. Instead, keep the file(s) on LionShare, which is protected by a password.

Experimental Design

On the spreadsheet, each row contains the data for one gene (one spot on the microarray). The first column (labeled "MasterIndex") numbers the rows in the spreadsheet so that we can match the data from different experiments together later. The second column (labeled "ID") contains the gene identifier from the Saccharomyces Genome Database. Each subsequent column contains the log2 ratio of the red/green fluorescence from each microarray hybridized in the experiment (steps 1-4 above having been done for you by the scanner software).

Each of the column headings from the data begin with the experiment name ("Schade" for Schade wild type data, "wt" for Dahlquist wild type data, and "dGLN3" for the Dahlquist Δgln3 data). "LogFC" stands for "Log2 Fold Change" which is the Log2 red/green ratio. The timepoints are designated as "t" followed by a number in minutes. Replicates are numbered as "-0", "-1", "-2", etc. after the timepoint.

For the Schade data, the timepoints are t0, t10, t30, t120, t12h (12 hours), and t60 (60 hours) of cold shock at 10°C.

For the Dahlquist data (both wild type and Δgln3), the timepoints are t15, t30, t60 (cold shock at 13°C) and t90 and t120 (cold shock at 13°C followed by 30 or 60 minutes of recovery at 30°C). Note that the experimental designs are different.

  1. Begin by recording in your wiki the number of replicates for each time point in your data. For the group assigned to the Schade data, compare the number of replicates with what is stated in the Materials and Methods for the paper. Is it the same? If not, how is it different?

Normalize the ratios for a set of slides in an experiment

To scale and center the data (between-chip normalization) perform the following operations:

  • Insert a new Worksheet into your Excel file, and name it "scaled_centered".
  • Go back to the "compiled_raw_data" worksheet, Select All and Copy. Go to your new "scaled_centered" worksheet, click on the upper, left-hand cell (cell A1) and Paste.
  • Insert two rows in between the top row of headers and the first data row.
  • In cell A2, type "Average" and in cell A3, type "StdDev".
  • You will now compute the Average log ratio for each chip (each column of data). In cell C2, type the following equation:
=AVERAGE(C4:C6190)

and press "Enter". Excel is computing the average value of the cells specified in the range given inside the parentheses. Instead of typing the cell designations, you can left-click on the beginning cell (let go of the mouse button), scroll down to the bottom of the worksheet, and shift-left-click on the ending cell.

  • You will now compute the Standard Deviation of the log ratios on each chip (each column of data). In cell B3, type the following equation:
=STDEV(C4:C6190)

and press "Enter".

  • Excel will now do some work for you. Copy these two equations (cells C2 and C3) and paste them into the empty cells in the rest of the columns. Excel will automatically change the equation to match the cell designations for those columns.
  • You have now computed the average and standard deviation of the log ratios for each chip. Now we will actually do the scaling and centering based on these values.
  • Insert a new column to the right of each data column and label the top of the column as with the same name as the column to the left, but adding "_sc" for scaled and centered to the name. For example, "wt_LogFC_t15-1_sc"
  • In cell D4, type the following equation:
=(C4-$C$2)/$C$3

In this case, we want the data in cell C4 to have the average subtracted from it (cell C2) and be divided by the standard deviation (cell C3). We use the dollar sign symbols surrounding the "C" to tell Excel to always reference that cell in the equation, even though we will paste it for the entire column. Why is this important?

  • Copy and paste this equation into the entire column.
  • Repeat the scaling and centering equation for each of the columns of data. Be sure that your equation is correct for the column you are calculating.

Perform statistical analysis on the ratios

We are going to perform this step on the scaled and centered data you produced in the previous step.

  • Insert a new worksheet into your Excel spreadsheet and name it "statistics".
  • Go back to the "scaling_centering" worksheet and copy the first column ("ID").
  • Paste the data into the first column of your new "statistics" worksheet.
  • Go back to the "scaling_centering" worksheet and copy Column C ("A1_scaled_centered).
  • Go to your new worksheet and click on the B1 cell. Select "Paste Special" from the Edit menu. A window will open: click on the radio button for "Values" and click OK. This will paste the numerical result into your new worksheet instead of the equation which must make calculations on the fly.
  • Go to a new column on the right of your worksheet. Type the header "Avg_LogFC_A", "Avg_LogFC_B", and "Avg_LogFC_C" into the top cell of the next three columns.
  • Compute the average log fold change for the replicates for each patient by typing the equation:
=AVERAGE(B2:E2)

into cell N2. Copy this equation and paste it into the rest of the column.

  • Create the equation for patients B and C and paste it into their respective columns.
  • Now you will compute the average of the averages. Type the header "Avg_LogFC_all" into the first cell in the next empty column. Create the equation that will compute the average of the three previous averages you calculated and paste it into this entire column.
  • Insert a new column next to the "Avg_LogFC_all" column that you computed in the previous step. Label the column "Tstat". This will compute a T statistic that tells us whether the scaled and centered average log ratio is significantly different than 0 (no change). Enter the equation:
=AVERAGE(N2:P2)/(STDEV(N2:P2)/SQRT(number of replicates))

(NOTE: in this case the number of replicates is 3. Be careful that you are using the correct number of parentheses.) Copy the equation and paste it into all rows in that column.

  • Label the top cell in the next column "Pvalue". In the cell below the label, enter the equation:
=TDIST(ABS(R2),degrees of freedom,2)

The number of degrees of freedom is the number of replicates minus one, so in our case there are 2 degrees of freedom. Copy the equation and paste it into all rows in that column.

  • Insert a new worksheet and name it "forGenMAPP".
  • Go back to the "statistics" worksheet and Select All and Copy.
  • Go to your new sheet and click on cell A1 and select Paste Special, click on the Values radio button, and click OK. We will now format this worksheet for import into GenMAPP.
  • Select Columns B through Q (all the fold changes). Select the menu item Format > Cells. Under the number tab, select 2 decimal places. Click OK.
  • Select Columns R and S. Select the menu item Format > Cells. Under the number tab, select 4 decimal places. Click OK.
  • Select Columns N through S and Cut. Select Column B by left-clicking on the "B" at the top of the column. Then right-click on the Column B header and select "Insert Cut Cells". This will insert the data without writing over your existing columns.
  • Delete Rows 2 and 3 where it says "Average" and "StDev" so that your data rows with gene IDs are immediately below the header row 1.
  • Insert a column to the right of the "ID" column. Type the header "SystemCode" into the top cell of this column. Fill the entire column (each cell) with the letter "N".
  • Select the menu item File > Save As, and choose "Text (Tab-delimited) (*.txt)" from the file type drop-down menu. Excel will make you click through a couple of warnings because it doesn't like you going all independent and choosing a different file type than the native .xls. This is OK. Your new *.txt file is now ready for import into GenMAPP. But before we do that, we want to know a few things about our data as shown in the next section.
    • Upload both the .xls and .txt files that you have just created to your journal page in the class wiki. Make sure that your file name is distinct from your other classmates so that nobody overwrites anyone else's file.

Shared Journal Assignment

  • Store your journal entry in the shared Class Journal Week 11 page. If this page does not exist yet, go ahead and create it (congratulations on getting in first :) )
  • Link to your journal entry from your user page.
  • Link back from the journal entry to your user page.
  • Sign your portion of the journal with the standard wiki signature shortcut (~~~~).
  • Add the "BIOL398-01/S11" category to the end of the wiki page (if someone has not already done so).

Reflection

Personal tools