qpcr - a python package for easy and versatile qPCR data analysis for small-scale datasets and high-throughput

New features in this version New qpcr.stats module

qpcr now offers T-tests and ANOVA analyses on qpcr.Results objects. Tests are offered to compare the groups within assays or assays across groups. P-values from multiple T-tests are automatically integrated into the results preview figures. At the core of the module is the new Evaluator class that performs statistical evaluations on results and produces Comparison objects that store the related p-values.

For convenience, stand-alone functions are directly available to perform statistical tests:

• assaywise_ttests
• groupwise_ttests
• assaywise_anova
• groupwise_anova

Note: This does not affect the properties of the qpcr.Results.stats() data frame.

It is not necessary anymore to call setup_cols manually before adding data using add_Ct, add_dCt, and add_ddCt. They will do so if necessary.

The main functionality has not been altered.