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. qpcr.Results.setup_cols automated It is not nec...
`pytest-cases` is a Python package leveraging the widely popular `pytest` library (Krekel et al., 20...
The package HTqPCR is designed for the analysis of cycle threshold (Ct) values from quantitative rea...
RT-qPCR results following the extraction-based and homogenization-based protocols represented as Ct ...
Fixed some package imports.When using this package to analyse your data, please, cite accordingly. G...
The first stable release of the new qpcr module.When using this package to analyse your data, please...
International audienceQuantifying changes in DNA and RNA levels is essential in numerous molecular b...
Description Analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays acro...
Description This package is based on the qBase algorithms published by Hellemans et al. in 2007. The...
This file contains normalized qPCR data for both the short-term and long-term gene candidates, as de...
Abstract Background qPCR has established itself as the technique of choice for the quantification of...
<p>qPCR results (mean expression values, expressed in relative units) for <i>Olig</i>1 and <i>Npy</i...
QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estima...
`pytest-cases` is a Python package leveraging the widely popular `pytest` library (Krekel et al., 20...
The package HTqPCR is designed for the analysis of cycle threshold (Ct) values from quantitative rea...
RT-qPCR results following the extraction-based and homogenization-based protocols represented as Ct ...
Fixed some package imports.When using this package to analyse your data, please, cite accordingly. G...
The first stable release of the new qpcr module.When using this package to analyse your data, please...
International audienceQuantifying changes in DNA and RNA levels is essential in numerous molecular b...
Description Analysis of Ct values from high throughput quantitative real-time PCR (qPCR) assays acro...
Description This package is based on the qBase algorithms published by Hellemans et al. in 2007. The...
This file contains normalized qPCR data for both the short-term and long-term gene candidates, as de...
Abstract Background qPCR has established itself as the technique of choice for the quantification of...
<p>qPCR results (mean expression values, expressed in relative units) for <i>Olig</i>1 and <i>Npy</i...
QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estima...
`pytest-cases` is a Python package leveraging the widely popular `pytest` library (Krekel et al., 20...
The package HTqPCR is designed for the analysis of cycle threshold (Ct) values from quantitative rea...
RT-qPCR results following the extraction-based and homogenization-based protocols represented as Ct ...