Open Source S/R Software

PAMGuide is acoustic analysis software for the characterisation of the acoustic environment from sound recordings. PAMGuide can be used to produce calibrated spectrograms and statistical analyses of sound levels, and is provided in both MATLAB and R. A Tutorial on getting started with PAMGuide can be downloaded here: http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12330/suppinfo PAMGuide was published as supplementary material to the following Open Access journal article: Merchant, N.D., Fristrup, K.M., Johnson, M.P., Tyack, P.L., Witt, M.J., Blondel, P., Parks, S.E. (2015). Measuring acoustic habitats. Methods in Ecology and Evolution. http://dx.doi.org/10.1111/2041-210X.12330

CyberUnits is a cross-platform class library for rapid development of high-performance computer simulations in life sciences. It supports modelling for biomedical cybernetics and systems biology with Object Pascal.

EigenMS is a normalization method implemented in R (and older version in Matlab) available as a set of two functions that should be used in a sequence. Please download EigenMS.zip file (latest version). Latest version uploaded in October 2017 has a bugfix for single treatment group normalization. Rescaling has been omitted from 2015. EigenMS utilizes SVD to detect bias trends in the data and eliminates them. EigenMS eliminates effects from known and unknown factors and can be utilized for any -omic platform. We have shown its utility in LC-MS/MS and metabolomics in the following two papers: 1) PMID: 19602524. "Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition". Karpievitch YV, Taverner T, Adkins JN, Callister SJ, Anderson GA, Smith RD, Dabney AR. Bioinformatics 2009 2) "Metabolomics data normalization with EigenMS" Karpievitch YV, Nikolic SB, Wilson R, Sharman JE, Edwards LM. PLoS One 2014

An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.

RIPE (Regulatory network Inference from joint Perturbation and Expression data) is a novel three-step method that integrates both perturbation data and steady state gene expression data in order to estimate a regulatory network. The ripe package is written in R, with additional functionality provided by a MATLAB executable file. The executable file uses a runtime engine called the MATLAB Compiler Runtime (MCR). The executable for different architectures is distributed on this site together with the R package itself.

Implematation of robust depth-based inference tools for microarray data (a scale curve, to measure the dispersion of a set of curves, a rank test to decide if two groups of curves come from the same population, and classification techniques).

Quick reference for switching between mathematical computation environments for computer algebra, numeric processing and data visualisation. Examples are Matlab, IDL, SPlus, and their open-source counterparts Octave, Scilab, Python+NumPy and R.

Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab.