This package provides methods for the analysis of how ecological drivers affect the multifunctionality of an ecosystem based on methods of Byrnes et al. 2016 <doi:10.1111/2041-210X.12143> and Byrnes et al. 2022 <doi:10.1101/2022.03.17.484802>. Most standard methods in the literature are implemented (see vignettes) in a tidy format.

Local linear estimation of psychometric functions. Provides functions for nonparametric estimation of a psychometric function and for estimation of a derived threshold and slope, and their standard deviations and confidence intervals.For more details see Zychaluk and Foster (2009) <doi:10.3758/APP.71.6.1414> and Foster and Zychaluk (2007) <doi:10.1109/MSP.2007.4286564>.

Implementation of Warnes & Raftery's MCGibbsit run-length and convergence diagnostic for a set of (not-necessarily independent) Markov Chain Monte Carlo (MCMC) samplers. It combines the quantile estimate error-bounding approach of the Raftery and Lewis MCMC run length diagnostic `gibbsit` with the between verses within chain approach of the Gelman and Rubin MCMC convergence diagnostic.

Implementation of commonly used p-value-based and parametric multiple testing procedures (computation of adjusted p-values and simultaneous confidence intervals) and parallel gatekeeping procedures based on the methodology presented in the book "Multiple Testing Problems in Pharmaceutical Statistics" (edited by Alex Dmitrienko, Ajit C. Tamhane and Frank Bretz) published by Chapman and Hall/CRC Press 2009.

Normalize data to minimize the difference between sample plates (batch effects). For given data in a matrix and grouping variable (or plate), the function normn_MA normalizes the data on MA coordinates. More details are in the citation. The primary method is Multi-MA'. Other fitting functions on MA coordinates can also be employed e.g. loess.

Programmatic interface to several NASA Earth Observation OPeNDAP servers (Open-source Project for a Network Data Access Protocol) (<https://www.opendap.org/>). Allows for easy downloads of MODIS subsets, as well as other Earth Observation datacubes, in a time-saving and efficient way : by sampling it at the very downloading phase (spatially, temporally and dimensionally).

This package contains a collection of functions for performing different kinds of calculation that are of interest to someone following a diet plan. Calculators for the Basal Metabolic Rate are based on Mifflin et al. (1990) <doi:10.1093/ajcn/51.2.241> and McArdle, W. D., Katch, F. I., & Katch, V. L. (2010, ISBN:9780812109917).

Simple and flexible quizzes in shiny'. Easily create quizzes from various pre-built question and choice types or create your own using htmltools and shiny packages as building blocks. Integrates with larger shiny applications. Ideal for non-web-developers such as educators, data scientists, and anyone who wants to assess responses interactively in a small form factor.

Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of dynamic survival models with shrinkage priors. Details on the algorithms used are provided in Wagner (2011) <doi:10.1007/s11222-009-9164-5>, Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006> and Cadonna et al. (2020) <doi:10.3390/econometrics8020020>.

Visualization and analysis of spatially resolved transcriptomics data. The spatialGE R package provides methods for visualizing and analyzing spatially resolved transcriptomics data, such as 10X Visium, CosMx, or csv/tsv gene expression matrices. It includes tools for spatial interpolation, autocorrelation analysis, tissue domain detection, gene set enrichment, and differential expression analysis using spatial mixed models.

Efficient procedure for fitting regularization paths between L1 and L0, using the MC+ penalty of Zhang, C.H. (2010)<doi:10.1214/09-AOS729>. Implements the methodology described in Mazumder, Friedman and Hastie (2011) <DOI: 10.1198/jasa.2011.tm09738>. Sparsenet computes the regularization surface over both the family parameter and the tuning parameter by coordinate descent.

This package provides a bridge is created between existing robust open-source record linkage algorithms and an urgently needed user-friendly platform that removes financial and technical barriers, setting a new standard for data interoperability in public health and bioinformatics. The fastLink algorithms are used for matching. Ted Enamorado et al. (2019) <doi:10.1017/S0003055418000783>.

Download geographic shapes from the United States Census Bureau TIGER/Line Shapefiles <https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html>. Functions support downloading and reading in geographic boundary data. All downloads can be set up with a cache to avoid multiple downloads. Data is available back to 2000 for most geographies.

The biodbHmdb library is an extension of the biodb framework package that provides access to the HMDB Metabolites database. It allows to download the whole HMDB Metabolites database locally, access entries and search for entries by name or description. A future version of this package will also include a search by mass and mass spectra annotation.

This package includes gene set collections that are used for the Ensemble of Gene Set Enrichment Analyses (EGSEA) method for gene set testing. It includes Human and Mouse versions of the MSidDB (Subramanian, et al. (2005) PNAS, 102(43):15545-15550) and GeneSetDB (Araki, et al. (2012) FEBS Open Bio, 2:76-82) collections.

This package provides an interface to any collection of data sets within a single iSEE web-application. The main functionality of this package is to define a custom landing page allowing app maintainers to list a custom collection of data sets that users can selected from and directly load objects into an iSEE web-application.

This package provides a fast, convenient tool to identify the TSSs of miRNAs by integrating the data of H3K4me3 and Pol II as well as combining the conservation level and sequence feature, provided within both command-line and graphical interfaces, which achieves a better performance than the previous non-cell-specific methods on miRNA TSSs.

survClust is an outcome weighted integrative clustering algorithm used to classify multi-omic samples on their available time to event information. The resulting clusters are cross-validated to avoid over overfitting and output classification of samples that are molecularly distinct and clinically meaningful. It takes in binary (mutation) as well as continuous data (other omic types).

TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matrix (PFM), Position Weight Matrix (PWM) and Information Content Matrix (ICM). It can also scan putative TFBS from sequence/alignment, query JASPAR database and provides a wrapper of de novo motif discovery software.

ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. It contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.

The wordspace package turns R into an interactive laboratory for empirical research on distributional semantic models (DSM). It consists of a small set of carefully designed functions, most of which

• encapsulate non-trivial R operations in a user-friendly manner or

• provide efficient and memory-lean C implementations of key operations.

Rudel is a collaborative editing environment for GNU Emacs. Its purpose is to share buffers with other users in order to edit the contents of those buffers collaboratively. Rudel supports multiple backends to enable communication with other collaborative editors using different protocols, though currently Obby (for use with the Gobby editor) is the only fully-functional one.

The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. Under the local randomization approach, RD designs can be interpreted as randomized experiments inside a window around the cutoff. This package provides tools to perform randomization inference for RD designs under local randomization: rdrandinf() to perform hypothesis testing using randomization inference, rdwinselect() to select a window around the cutoff in which randomization is likely to hold, rdsensitivity() to assess the sensitivity of the results to different window lengths and null hypotheses and rdrbounds() to construct Rosenbaum bounds for sensitivity to unobserved confounders. See Cattaneo, Titiunik and Vazquez-Bare (2016) <https://rdpackages.github.io/references/Cattaneo-Titiunik-VazquezBare_2016_Stata.pdf> for further methodological details.

This package provides a method for modeling genetic data as a combination of discrete layers, within each of which relatedness may decay continuously with geographic distance. This package contains code for running analyses (which are implemented in the modeling language rstan') and visualizing and interpreting output. See the paper for more details on the model and its utility.