1. User Accounts
    • When you first visit the website, you have to create a new user account.
    • Create a new user account with an Email and a Password. The Email will be used to send Job Status updates.
    • Click on "New User Sign Up" to create a new user account.
    • Click on "Log In" to login with your already created user account credentials.

  2. Upload Phenotype Data File
    • Click the "Upload Phenotype File" button on the sidebar to start a new analysis.
    • Select your preferred file, and make sure it is in CSV format or Tab-delimited format. The first column should have the official CC strain name or it's Alias name. Each row is a unique animal. The order of the remaining columns containing phenotype data is not important, but one column should be named "Sex" and denoted as M or F. The file can contain multiple phenotype columns.
    • If the phenotype data does not appear on the main web page:
      • The notifications menu in the top right corner may show a specific error.
      • Open the "Field Separator Options" menu to change "Delimitor" and/or "Quote" setting and reupload the file.
    • Enter a name for the analysis session, and click "Save Analysis" to proceed.

  3. Inspect Phenotype Data
    • Click on any numeric column on the data table. Below the data table, plots will appear.
    • Histogram, QQ, Histogram (Normalized), and QQ (Normalized) plots will appear once the file is correctly uploaded.
    • You can specify the type of Data Transformation by selecting: "Sqrt", "Log", "Auto" or "Rank-Z"
    • Automatically manage outlier strains, and manually manage selected strains for a single column.

  4. Run QTL Analysis
    • Select one or more columns, then click the green "Run QTL" button to run analysis.
    • You should receive an email confirmation that your job was submitted.
    • The "Job Status" in the side panel tracks your analyses.
    • Click the refresh button in the sidebar to see updates.

  5. View QTL Analysis Results
    • If a job is labeled "F", the QTL Analysis has finished.
    • Reload the page, to get the results from the server.
    • Click a phenotype column on which the QTL Analysis was run.
    • The QTL results will appear below the data table.

  6. Generate Report of QTL Results
    • To export QTL results obtained for this session, click the "Generate PDF" button, which should appear if correct phenotype columns are selected.
    • You will be prompted to download a PDF report and / or a folder of JPEG figures at 300 dpi, which also includes a PDF and HTML report.

  7. Contact Us
    • Please email konganti[AT]tamu.edu for any unexpected errors, questions or concerns about the web app.



  • Version 1.5 - January 16 2019
    • Bug Fix: Fixed a bug wherein analysis completion emails were not being sent.
    • Bug Fix: Fixed a bug wherein selecting GigaMUGA or Build 38 (mm10) resulted in Error in eigen(WQK, symmetric = TRUE, only.values = TRUE): infinite or missing values in x error.
    • Bug Fix: Fixed a bug wherein Genes within the significant QTL interval plot would show Cannot get genes within QTL interval as Proximal > Distal.
    • Bug Fix: Fixed a bug wherein spaces and special characters in the column name of the uploaded phenotype file causes unexpected errors.

  • Version 1.4 - August 20 2018
    • Bug Fix: Fixed a bug wherein reports were not being generated when "QTL" analysis has not yet been done for selected Phenotype columns.
    • Feature: Yay! Added ability to handle Phenotype data with multiple individuals per strain. Please re-upload your data if you have previously uploaded the Phenotype data that contains mulitple entries per individual.

  • Version 1.3 - July 02 2018
    • Bug Fix: If a Phenotype column contains negative values, SQRT transform returns imaginary numbers. This error check now prevents the app from crashing.

  • Version 1.2 - June 26 2018
    • Bug Fix: In the generated PDF and HTML report files, "QTL" plots now include a title to differentiate between multiple Phenotypes.
    • Bug Fix: Incorrectly rendered app title in the PDF and HTML report files has been fixed.

  • Version 1.1 - June 22 2018
    • Feature: Added ability to display "Allele Effects" plot even though no significant QTL have been identified.
    • Feature: Added horizontal scroll to the display of the uploaded Phenotype table.
    • Bug Fix: Fixed a bug wherein "F" character in sex column was being converted to "FALSE" during file upload.

  • Version 1.0 - May 18 2018
    • Initial release of gQTL v1.0 in May 2018.




Phenotype Data

Multiple phenotype columns can be selected to run QTL analysis simultaneously. To edit the selected strains for a phenotype column, select a single column and the "Selected Strains" Checkbox and Plots will appear for that phenotype.
Select a Phenotype Column Click on a phenotype column of your choice on the table anywhere other than the column header.
Note: We have automatically created unique strain names as we see that your data set contains multiple individuals per strain.
Check Strains for each phenotype Select a single phenotype column to manually check selected strains. Autoremove outlier strains: Outlier values for a selected phenotype column will be removed from subsequent analysis.
Tip: Select a single phenotype column to view outlier strains and basic plots below.
auto: Shapiro-Wilk's test chooses best transform between log and sqrt. rankZ: Recommended if you have hundreds or thousands of phenotypes.

* Read CC Status before making a decision to choose genome build.
Prune Probablity Matrix
Checking this option will set all the CC founder genotype probability values below 0.005 to a very low value, 1e-20.
Run options

Perform QTL Analysis and Render Plots Warning: it will take a while!


Generate Report