Identifiers in biological databases connect different levels of metadata, phenotype data or genotype data. This tool is designed to easily convert identifiers within or between different biological databases (Wang, Shixiang, et al. (2021) <DOI:10.1371/journal.pgen.1009557>).

Adaptive estimation of the first-order intensity function of a spatio-temporal point process using kernels and variable bandwidths. The methodology used for estimation is presented in González and Moraga (2022). <doi:10.48550/arXiv.2208.12026>.

This package provides methods and models for analysing multigraphs as introduced by Shafie (2015) <doi:10.21307/joss-2019-011>, including methods to study local and global properties <doi:10.1080/0022250X.2016.1219732> and goodness of fit tests.

This package contains functions for data preparation, prediction of transition probabilities, estimating semi-parametric regression models and for implementing nonparametric estimators for other quantities. See Meira-Machado and Roca-Pardiñas (2011) <doi:10.18637/jss.v038.i03>.

Disk-based implementation of Functional Pruning Optimal Partitioning with up-down constraints <doi:10.18637/jss.v101.i10> for single-sample peak calling (independently for each sample and genomic problem), can handle huge data sets (10^7 or more).

Bayesian toolbox for quantitative proteomics. In particular, this package provides functions to generate synthetic datasets, execute Bayesian differential analysis methods, and display results as, described in the associated article Marie Chion and Arthur Leroy (2023) <arXiv:2307.08975>.

Singular spectrum analysis (SSA) decomposes a time series into interpretable components like trends, oscillations, and noise without strict distributional and structural assumptions. For method details see Golyandina N, Zhigljavsky A (2013). <doi:10.1007/978-3-642-34913-3>.

This package provides a simple authentification mechanism for single shiny applications. Authentification and password change functionality are performed calling user provided functions that typically access some database backend. Source code of main applications is protected until authentication is successful.

Calculates non-parametric estimates of the sample size, power and confidence intervals for the win-ratio. For more detail on the theory behind the methodologies implemented see Yu, R. X. and Ganju, J. (2022) <doi:10.1002/sim.9297>.

These tools implement in R a fundamental part of the software PACTA (Paris Agreement Capital Transition Assessment), which is a free tool that calculates the alignment between financial portfolios and climate scenarios (<https://www.transitionmonitor.com/>). Financial institutions use PACTA to study how their capital allocation decisions align with climate change mitigation goals. This package matches data from corporate lending portfolios to asset level data from market-intelligence databases (e.g. power plant capacities, emission factors, etc.). This is the first step to assess if a financial portfolio aligns with climate goals.

Create densities, probabilities, random numbers, quantiles, and maximum likelihood estimation for several distributions, mainly the symmetric and asymmetric power exponential (AEP), a.k.a. the Subbottin family of distributions, also known as the generalized error distribution. Estimation is made using the design of Bottazzi (2004) <https://ideas.repec.org/p/ssa/lemwps/2004-14.html>, where the likelihood is maximized by several optimization procedures using the GNU Scientific Library (GSL)', translated to C++ code, which makes it both fast and accurate. The package also provides methods for the gamma, Laplace, and Asymmetric Laplace distributions.

This package implements a variety of persistent homology algorithms. It provides an interface for

• computing persistence cohomology of sparse and dense data sets

• visualizing persistence diagrams

• computing lowerstar filtrations on images

• computing representative cochains

This module provides a facility for creating non-modifiable variables in Perl. This is useful for configuration files, headers, etc. It can also be useful as a development and debugging tool for catching updates to variables that should not be changed.

CiteProc is a citation processor interface and citation data API based on the CSL specifications. To actually process citations, a dedicated processor engine is required: a pure Ruby engine is available in the citeproc-ruby gem.

The package provides virtual fonts and LaTeX support files for mathematical calligraphic fonts based on the rsfs Adobe Type 1 fonts, with the slant substantially reduced. The output is quite similar to that from the Adobe Mathematical Pi script font.

Benchmarks for Machine Learning Analysis of the Gene Sets. The package contains a list of pathways and gene expression data sets used in "Identifying Tightly Regulated and Variably Expressed Networks by Differential Rank Conservation (DIRAC)" (2010) by Eddy et al.

Expression profiling using microarray technology to prove if Hypoxia Promotes Efficient Differentiation of Human Embryonic Stem Cells to Functional Endothelium by Prado-Lopez et al. (2010) Stem Cells 28:407-418. Full data available at Gene Expression Omnibus series GSE37761.

This package provides an interface in R to cell atlas approximations. See the vignette under "Getting started" for instructions. You can also explore the reference documentation for specific functions. Additional interfaces and resources are available at <https://atlasapprox.readthedocs.io>.

This package provides functions to calculate Gray Level Co-occurrence Matrix(GLCM), RGB-based Vegetative Index(RGB VI) and Normalized Difference Vegetation Index(NDVI) family image features. GLCM calculations are based on Haralick (1973) <doi:10.1109/TSMC.1973.4309314>.

This package provides static and interactive maps of the Comoro Islands at four administrative levels: country, island, prefecture, and commune. Includes tools for choropleth visualisation using ggplot2 and leaflet', and functions to retrieve the underlying spatial datasets as sf objects.

Allows you to define rules which can be used to verify a given dataset. The package acts as a thin wrapper around more powerful data packages such as dplyr', data.table', arrow', and DBI ('SQL'), which do the heavy lifting.

This package provides a statistically and computationally efficient debiasing method for conducting valid inference on the high-dimensional linear regression function with missing outcomes. The reference paper is Zhang, Giessing, and Chen (2023) <doi:10.48550/arXiv.2309.06429>.

This package provides a principled framework for sampling Virtual Control Group (VCG) using energy distance-based covariate balancing. The package offers visualization tools to assess covariate balance and includes a permutation test to evaluate the statistical significance of observed deviations.

Cluster functional data using phase and amplitude components of each function. By weighting phase and amplitude variation differently, clustering results can be obtained from multiple perspectives. Routines for synchronization, functional k-means clustering, and functional k-medians clustering are provided.