Import QPCR raw data / open existing fileDuring this first step, you can:
- Create a new project: you give a project name, choose the PCR device (for now Eppendorf, AB 7000 and AB StepOne ones are supported, but others can be easily added) and import your raw data (TXT or CSV files) of one or several plates. Some examples of these files are given with the source of pyQPCR.
- Open an existing one: pyQPCR has its own file format which is XML based. You can directly open these files (examples are in the source code of pyQPCR).
Plate settingsYou can edit the data of each well separately or select and modify a group of wells. You also can change the targets and samples properties (name, efficiency of the primers), and remove or add new ones. You can disable wells in order to not take them into account for calculations.
Standard curve calculationYou can define as "standards" the wells that contains dilutions of DNA in order to calculate PCR efficiency. Then, you precise the amount of DNA (arbitrary unit) in the different wells and the program will plot the standard curve and calculate PCR efficiency for this set of primers. This efficiency will be taken into account for subsequent relative quantifications.
Reference target and sampleFor relative quantification calculations, you must define one or several reference gene(s) and one reference sample. They can be either shared for all plates or specific of each plate.
Relative quantificationThe wells defined as "unknown" are used to calculate relative quantifications. An improved ΔΔCt method (1) allows you to obtain reliable quantifications and error. The confidence level is modifiable and can be either gaussian or calculated using a T-test.
Results, export and saveResults can be printed or exported in a pdf file containing a table with all the data and plots for standard curves and/or relatives quantifications.
HelpA Help menu is available and summarize the different functionalities of the software.
(1) qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J. Genome Biol. 2007;8(2):R19.