:: DESCRIPTION
CORREP is a Bioconductor package to estimate correlation between two variables with replicates
::DEVELOPER
Dongxiao Zhu, Ph.D
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Bioinformatics. 2007 Sep 1;23(17):2298-305. Epub 2007 Jun 22.
Multivariate correlation estimator for inferring functional relationships from replicated genome-wide data.
Zhu D, Li Y, Li H.
:: DESCRIPTION
CorSig: A General Framework for Estimating Statistical Significance of Correlation and Its Application to Gene Co-expression Analysis.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: MORE INFORMATION
Citation
PLoS One. 2013 Oct 23;8(10):e77429. doi: 10.1371/journal.pone.0077429. eCollection 2013.
CorSig: a general framework for estimating statistical significance of correlation and its application to gene co-expression analysis.
Wang HQ1, Tsai CJ.
:: DESCRIPTION
SIAMCAT is a modular framework for the statistical inference of associations between microbial communities and host phenotypes, such as disease states in clinical case-control studies. SIAMCAT is based on LASSO models, which offer distinctive advantages for model interpretation and microbial biomarker selection and avoid overfitting issues that can arise in naive combinations of feature selection and cross-validation.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
:: DESCRIPTION
GNU MCSim is a simulation and statistical inference tool for algebraic or differential equation systems. Other programs have been created to the same end, the Matlab family of graphical interactive programs being some of the more general and easy to use. Still, many available tools are not optimal for performing computer intensive and sophisticated Monte Carlo analyses. GNU MCSim was created specifically to this end: to perform Monte Carlo analyses in an optimized, and easy to maintain environment.
::DEVELOPER
:: SCREENSHOTS
Commmand Line
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models.
Bois FY.
Bioinformatics. 2009 Jun 1;25(11):1453-4.
