Experiment Performed Using:

Standard RT² PCR Array    
Custom RT² PCR Array  
Single or Multi-Gene qPCR Assays

File:                            
* File must be a MS Excel Sheet (in .XLS format, not .XLSX).


Excel Templates for Formatting your Experimental Data:

Cataloged PCR Array

Custom PCR Array                 

Single/Multi-Gene Assays


For Custom PCR Arrays - Data Analysis Patches
Convert your custom array raw data into the compatible format for your customized Data Analysis Template.

96-well 384-well
8 genes x 12 samples 8 genes x 48 samples
12 genes x 8 samples 12 genes x 32 samples
16 genes x 6 samples 16 genes x 24 samples
24 genes x 4 samples 24 genes x 16 samples
32 genes x 3 samples 32 genes x 12 samples
48 genes x 2 samples  48 genes x 8 samples
 96 genes x 1 samples  64 genes x 6 samples
  96 genes x 4 samples
  128 genes x 3 samples
  192 genes x 2 samples


Example: Properly Formatted Data Upload Templates

New to RT² Data Analaysis? Learn more by:

Notes:

  1. Please note that you must complete all of your work with the PCR Array Data Analysis Web Portal in the same session. Your data is not stored on a server, so all work is lost once the session (or your web browser) is closed. Be sure to export all processed data and results to an Excel file saved on your local computer.
  2. Please set your screen resolution to 1024 X 768 or greater, if possible.
  3. Turn off any window pop-up blockers. The software will launch separate windows for viewing the plots and charts.

Instructions 

  1. Choose the experiment that was performed: Standard/Cataloged RT² Profiler PCR Array, Custom RT² PCR Array or individual assays

    1. If you selected Standard RT² PCR Array then Enter the PCR Array Pathway Number from the drop-down list.
    2. If you selected Custom RT² PCR Array then Enter the Custom Array ID (ex. CAPX####) in the text field.
    3. If your experiment used individual primer assays then select Single or Multi-Gene qPCR Assays.
  2. Browse and select the MS Excel file containing your PCR data with a maximum number of 100 samples. Click "Upload".

  3. Analysis Setup page:

    1. In the "Basic Setup" section, assign samples to different groups. At least two groups are needed, where one of those groups must be the control group. Click "Update" when finished. You may exclude samples from the analysis by selecting "Exclude" on the drop down menu.
    2. Review the "Data QC" section to assess each groups' PCR reproducibility, reverse transcription efficiency, and the presence of genomic DNA contamination.
    3. The "Select Housekeeping Genes" section allows you to remove or add preferred housekeeping genes for data normalization by clicking the appropriate checkboxes. Click "Update" when finished.
    4. Review the "Data Overview" section to see each group's distribution of threshold cycle values and the average of the raw data in each group.
  4. Analysis page:
    1. See the "Average Ct", "2^(- Ct)", "Fold Change", "p-value", and "Fold Regulation" sections for the results processed by the software from your data. The "Fold Change" and "p-value" results are used by the software in subsequent graphical analyses.
  5. Plots and Charts page:
    1. Heat Map
      1. Define Groups to be compared and whether to report the fold-change results as a log transformation or not (default recommended). Click "Update" once changes have been made. Click "Export Data" to download the results as an Excel file.
    2. Scatter Plot and Volcano Plot
      1. Define Groups to be compared. Choose the fold-change boundary (and p-value for Volcano Plot) of interest. Click "Update".
      2. Click on symbols to identify gene and fold-change (and p-value for Volcano Plot); mouse over table entries to point to symbol on plot.
      3. Click check boxes to remove genes from or add genes to plot. Click "Update".
      4. Click "Export Data" to download the results as an Excel file.
    3. Clustergram
      1. Sort samples by "Array" or by "Group".
      2. Select "Join Type". The default of "Average" is recommended.
      3. Cluster in "1-D" by genes only or in "2-D" by genes and samples.
      4. Color code the graph by "Genes", "Samples" or "Entire Dataset". The default of "Genes" is recommended.
      5. Choose whether or not to display the gene symbols and array or group names.
      6. Click check boxes to remove genes from or add genes to plot.
      7. Click "Update".
    4. Multigroup Plot
      1. Click check boxes to add genes to or remove genes from plots.
      2. Choose results to plot on the y-axis, either "AVG Delta Ct", "2^Delta Ct", or "Fold Change".
      3. Click "Update".
      4. Review either the line plot (above) or the column chart (below).
  6. Click "Export Data" to download a MS Excel file containing all raw and processed data from the "Readout" and "Analysis Result" sections.
  7. What's Next page:

    1. Examine experimental solutions for identifying the mechanisms behind the observed changes in gene expression.