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Marine Regions Data from 'Marineregions.org'
Tools to get marine regions data from < http://www.marineregions.org/>. Includes tools to get region metadata, as well as data in 'GeoJSON' format, as well as Shape files. Use cases include using data downstream to visualize 'geospatial' data by marine region, mapping variation among different regions, and more.
Tools for Eurostat Open Data
Tools to download data from the Eurostat database < http://ec.europa.eu/eurostat> together with search and manipulation utilities.
Omics Data Integration Project
Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares.
Chordalysis R Package
Learning the structure of graphical models from datasets with thousands of variables. More information about the research papers detailing the theory behind Chordalysis is available at < http://www.francois-petitjean.com/Research> (KDD 2016, SDM 2015, ICDM 2014, ICDM 2013). The R package development site is < https://github.com/HerrmannM/Monash-ChoR>.
Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry Data
Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions modeling oriented towards flow-cytometry data preprocessing applications.
Deprecated 'classic' 'Rcpp' 'API'
The 'RcppClassic' package provides a deprecated C++ library which facilitates the integration of R and C++. New projects should use the new 'Rcpp' 'API' in the 'Rcpp' package.
Exploring the Phylogenetic Signal in Continuous Traits
A collection of tools to explore the phylogenetic signal in univariate and multivariate data. The package provides functions to plot traits data against a phylogenetic tree, different measures and tests for the phylogenetic signal, methods to describe where the signal is located and a phylogenetic clustering method.
R-Based Wikipedia Client
Provides an interface to the Wikipedia web application programming interface (API), using internet connexion.Three functions provide details for a specific Wikipedia page : all links that are present, all pages that link to, all the contributions (revisions for main pages, and discussions for talk pages). Two functions provide details for a specific user : all contributions, and general information (as name, gender, rights or groups). It provides additional information compared to others packages, as WikipediR. It does not need login. The multiplex network that can be constructed from the results of the functions of WikipediaR can be modeled as Stochastic Block Model as in Barbillon P., Donnet, S., Lazega E., and Bar-Hen A. : Stochastic Block Models for Multiplex networks: an application to networks of researchers, ArXiv 1501.06444, http://arxiv.org/abs/1501.06444.
'Rcpp' Integration for the 'Blaze' High-Performance C++ Math Library
'Blaze' is an open-source, high-performance C++ math library for dense and sparse arithmetic. With its state-of-the-art Smart Expression Template implementation 'Blaze' combines the elegance and ease of use of a domain-specific language with 'HPC'-grade performance, making it one of the most intuitive and fastest C++ math libraries available. The 'Blaze' library offers: - high performance through the integration of 'BLAS' libraries and manually tuned 'HPC' math kernels - vectorization by 'SSE', 'SSE2', 'SSE3', 'SSSE3', 'SSE4', 'AVX', 'AVX2', 'AVX-512', 'FMA', and 'SVML' - parallel execution by 'OpenMP', C++11 threads and 'Boost' threads ('Boost' threads are disabled in 'RcppBlaze') - the intuitive and easy to use API of a domain specific language - unified arithmetic with dense and sparse vectors and matrices - thoroughly tested matrix and vector arithmetic - completely portable, high quality C++ source code. The 'RcppBlaze' package includes the header files from the 'Blaze' library with disabling some functionalities related to link to the thread and system libraries which make 'RcppBlaze' be a header-only library. Therefore, users do not need to install 'Blaze' and the dependency 'Boost'. 'Blaze' is licensed under the New (Revised) BSD license, while 'RcppBlaze' (the 'Rcpp' bindings/bridge to 'Blaze') is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that since 'Blaze' has committed to 'C++14' commit to 'C++14' which does not used by most R users from version 3.0, we will use the version 2.6 of 'Blaze' which is 'C++98' compatible to support the most compilers and system.
Geophysics, Continuum Mechanics, Gravity Modeling
Codes for analyzing various problems of geophysics, continuum mechanics and gravity models.