Roche SPPs

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(University of Graz P07 )

The SPP for the data analysis of RT-PCR runs from ABI SYBRGreen and Roche LightCycler assays is based on QPCR, a web application for the management of RT-PCR data, which covers the complete analysis workflow. Created by Stephan Pabinger at Graz University of Technology (Graz, Austria), QPCR supports the determination of the Cq value and amplification efficiency, technical and biological replicate handling, incorporation of sample or target specific efficiency, normalization using single or multiple reference genes, inter-run calibration, and fold change calculation. Additionally, the QPCR includes statistical tests to evaluate differences between samples groups.

A tutorial is available form here. For details regarding QPCR, please see the official userguide.

QPCR can be accessed via the following URL http://esus.genome.tugraz.at/rtpcr

Contents

Registration & Login

To register as a new user, please sent an e-mail to QPCR@genome.tugraz.at . Otherwise, follow the "login" link to access your data directory and past data analyses.
After the first login click on "User settings", select "AnalyzerCy0" as the "Preferred Cq Analyzer" and "AnalyzerMiner" as the "Preferred Efficiency Analyzer" and press "Update" to make your selection permanent.

Data Upload & File Parsing

To upload the created files into the QPCR application, select "Upload & Parse" in the left navigation panel. Data files can be uploaded separately or in batches using the multiple file upload interface. When uploading a file the the correct file type has to be specified. Currently there are 2 file types available:

  • File (.SDS – Applied Biosystems, .IXO – Roche, .CSV generic)
  • Export File (Clipped Files, Component Files, DeltaRn Files, XML Files)

After successful data upload, the thermocycler files have to be parsed and analysed to be available for further analysis. The parsing step extracts the raw data from the uploaded files and during the analysis step Cq and efficency values for each populated well are calculated. Clicking on "Parse" displayes the files which are not linked to a run and therefore have not been parsed yet. Each file can be accompanied by a maximum number of three additional export files (Export file) which are automatically linked to the respective raw file.

  • Important: Export files need to contain the name of the main file (e.g.: SDS: myFile.sds; rn: myFile_clipped.txt) in order to be correctly identified by the system.

For each Main File – Export file combination check the "parse" and "analyze" boxes. Pressing "Submit" starts parsing and analyzing the selected files in the background and creates a run for each file. The methods used during analysis have been set previously in the user settings interface.

Clicking on the "Progress Information" link displays a list of currently running analysis task with the approximate degree of completion.

To have a look at the newly created runs go to "Run -> Find Runs". Each parsed file is associated with a run which represents a performed qPCR run (qPCR experiment). By clicking on the gird icon you are linked to the plate layout. The chart symbol is a direct link to the charts of the run.

Experiment Definition

After you have taken a look at the generated runs and evaluated the parsed and analyzed results it is necessary to create a new experiment. Experiments consist of one or many runs (e.g.: experiment is spread over multiple plates because of the limited amount of wells on one plate) which are analyzed together. To create an experiment click on "Experiment" in the left navigation panel and select "New Experiment". Define name, date, and description and choose the runs which should be combined in this experiment. Multiple runs are selected by holding the ctrl key. Save the experiment by clicking "Create".

Normalization

To normalize an experiment go to "Experiment" -> "Find Experiment" and click on the name of the experiment. Press "Go" to and select your reference gene(s) in the "Reference Genes" tab. Press the "Analyze" button in the lower left corner to start the normalization. Normalized values are displayed in tabular form and can be exported for further analysis.

Differential Expression Analysis

From the normalized values table press the "Show" button close to "Perform Statistical Test". Here you can define which samples should be included in the test and which samples or which class should act as reference. Choose the "Benjamini-Hochberg" as the "Testing correction" method and use the default values for the other settings. Press "Analyze" to determine differentially expressed genes between your sample groups. This brings you to a page, where you can export the results (via the "Export" button) and where the results are displayed in graphical form.

Citing QPCR

In the event that this work leads to publication, please cite QPCR in the following manner:

Pabinger S, Thallinger GG, Snajder R, Eichhorn H, Rader R, Trajanoski Z. QPCR: Application for real-time PCR data management and analysis. BMC Bioinformatics. 2009;10(1):268.


Back to RT-PCR Standard Processing Procedures 

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