Gain access to the Spark Catalog API making use of the sparklyr API. Catalog <https://spark.apache.org/docs/2.4.3/api/java/org/apache/spark/sql/catalog/Catalog.html> is the interface for managing a metastore (aka metadata catalog) of relational entities (e.g. database(s), tables, functions, table columns and temporary views).

Sample and cell filtering as well as visualisation of output metrics from Cell Ranger by Grace X.Y. Zheng et al. (2017) <doi:10.1038/ncomms14049>. CRMetrics allows for easy plotting of output metrics across multiple samples as well as comparative plots including statistical assessments of these. CRMetrics allows for easy removal of ambient RNA using SoupX by Matthew D Young and Sam Behjati (2020) <doi:10.1093/gigascience/giaa151> or CellBender by Stephen J Fleming et al. (2022) <doi:10.1101/791699>. Furthermore, it is possible to preprocess data using Pagoda2 by Nikolas Barkas et al. (2021) <https://github.com/kharchenkolab/pagoda2> or Seurat by Yuhan Hao et al. (2021) <doi:10.1016/j.cell.2021.04.048> followed by embedding of cells using Conos by Nikolas Barkas et al. (2019) <doi:10.1038/s41592-019-0466-z>. Finally, doublets can be detected using scrublet by Samuel L. Wolock et al. (2019) <doi:10.1016/j.cels.2018.11.005> or DoubletDetection by Gayoso et al. (2020) <doi:10.5281/zenodo.2678041>. In the end, cells are filtered based on user input for use in downstream applications.

This package implements Dirichlet multinomial modeling of relative abundance data using functionality provided by the Stan software. The purpose of this package is to provide a user friendly way to interface with Stan that is suitable for those new to modeling. For more regarding the modeling mathematics and computational techniques we use see our publication in Molecular Ecology Resources titled Dirichlet multinomial modeling outperforms alternatives for analysis of ecological count data (Harrison et al. 2020 <doi:10.1111/1755-0998.13128>).

This package implements the adaptive designs for integrated phase I/II trials of drug combinations via continual reassessment method (CRM) to evaluate toxicity and efficacy simultaneously for each enrolled patient cohort based on Bayesian inference. It supports patients assignment guidance in a single trial using current enrolled data, as well as conducting extensive simulation studies to evaluate operating characteristics before the trial starts. It includes various link functions such as empiric, one-parameter logistic, two-parameter logistic, and hyperbolic tangent, as well as considering multiple prior distributions of the parameters like normal distribution, gamma distribution and exponential distribution to accommodate diverse clinical scenarios. Method using Bayesian framework with empiric link function is described in: Wages and Conaway (2014) <doi:10.1002/sim.6097>.

This package provides a wrapper for the U.S. Census Bureau APIs that returns data frames of Census data and metadata. Available datasets include the Decennial Census, American Community Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, Population Estimates and Projections, and more.

Jointly model the accuracy of cognitive responses and item choices within a Bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.

Imports conversation transcripts into R, concatenates them into a single dataframe appending event identifiers, cleans and formats the text, then yokes user-specified psycholinguistic database values to each word. ConversationAlign then computes alignment indices between two interlocutors across each transcript for >40 possible semantic, lexical, and affective dimensions. In addition to alignment, ConversationAlign also produces a table of analytics (e.g., token count, type-token-ratio) in a summary table describing your particular text corpus.

This package provides functions and a workflow to easily and powerfully calculating specificity, sensitivity and ROC curves of biomarkers combinations. Allows to rank and select multi-markers signatures as well as to find the best performing sub-signatures, now also from single-cell RNA-seq datasets. The method used was first published as a Shiny app and described in Mazzara et al. (2017) <doi:10.1038/srep45477> and further described in Bombaci & Rossi (2019) <doi:10.1007/978-1-4939-9164-8_16>, and widely expanded as a package as presented in the bioRxiv pre print Ferrari et al. <doi:10.1101/2022.01.17.476603>.

This package provides access to consolidated information from the Brazilian Federal Government Payment Card. Includes functions to retrieve, clean, and organize data directly from the Transparency Portal <https://portaldatransparencia.gov.br/download-de-dados/cpgf/> and a curated dataset hosted on the Open Science Framework <https://osf.io/z2mxc/>. Useful for public spending analysis, transparency research, and reproducible workflows in auditing or investigative journalism.

Offers a diverse collection of datasets focused on cardiovascular and heart disease research, including heart failure, myocardial infarction, aortic dissection, transplant outcomes, cardiovascular risk factors, drug efficacy, and mortality trends. Designed for researchers, clinicians, epidemiologists, and data scientists, the package features clinical, epidemiological, and simulated datasets covering a wide range of conditions and treatments such as statins, anticoagulants, and beta blockers. It supports analyses related to disease progression, treatment effects, rehospitalization, and public health outcomes across various cardiovascular patient populations.

Deconvolution of bulk RNA-Sequencing data into proportions of cells based on a reference single-cell RNA-Sequencing dataset using high-dimensional geometric methodology.

This package implements Markowitz Critical Line Algorithm ('CLA') for classical mean-variance portfolio optimization, see Markowitz (1952) <doi:10.2307/2975974>. Care has been taken for correctness in light of previous buggy implementations.

This is a one-function package that will pass only unique values to a computationally-expensive function that returns an output of the same length as the input. In importing and working with tidy data, it is common to have index columns, often including time stamps that are far from unique. Some functions to work with these such as text conversion to other variable types (e.g. as.POSIXct()), various grep()-based functions, and often the cut() function are relatively slow when working with tens of millions of rows or more.

Calculates correlation of variables and displays the results graphically. Included panel functions can display points, shading, ellipses, and correlation values with confidence intervals. See Friendly (2002) <doi:10.1198/000313002533>.

Computes a range of scatterplot diagnostics (scagnostics) on pairs of numerical variables in a data set. A range of scagnostics, including graph and association-based scagnostics described by Leland Wilkinson and Graham Wills (2008) <doi:10.1198/106186008X320465> and association-based scagnostics described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be computed. Summary and plotting functions are provided.

This package provides a versatile R package for creating and pricing custom derivatives to suit your financial needs.

Calculates centrality indices additional to the igraph package centrality functions.

Prints code that can be used to recreate R objects. In a sense it is similar to base::dput() or base::deparse() but constructive strives to use idiomatic constructors.

This package creates compact letter displays (CLDs) for pairwise comparisons from statistical post-hoc tests. Groups sharing the same letter are not significantly different from each other. Supports multiple input formats including results from stats pairwise tests, DescTools', PMCMRplus', rstatix', symmetric matrices of p-values, and data frames. Provides a consistent interface for visualizing statistical groupings across different testing frameworks.

Generates the calibration simplex (a generalization of the reliability diagram) for three-category probability forecasts, as proposed by Wilks (2013) <doi:10.1175/WAF-D-13-00027.1>.

Mainly used to build tables that are commonly presented for bio-medical/health research, such as basic characteristic tables or descriptive statistics.

This package implements the Changepoints for a Range of Penalties (CROPS) algorithm of Haynes et al. (2017) <doi:10.1080/10618600.2015.1116445> for finding all of the optimal segmentations for multiple penalty values over a continuous range.

This package provides a Shiny application to conduct comprehensive analysis of latent means including the examination of group equivalency, propensity score analysis, measurement invariance analysis, and assessment of latent mean differences of equivalent groups with invariant data. Group equivalency and propensity score analyses are implemented using the MatchIt package [Ho et al. (2011) <doi:10.18637/jss.v042.i08>], ensuring robust control for covariates. Structural equation modeling and invariance testing rely heavily on the lavaan package [Rosseel (2012) <doi:10.18637/jss.v048.i02>], providing a flexible and powerful modeling framework. The application also integrates modified functions from Hammack-Brown et al. (2021) <doi:10.1002/hrdq.21452> to support factor ratio testing and the list-and-delete procedure.

Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners. Build complex systems from simpler parts using a spectral product algebra. For light sources, compute CCT, CRI, SSI, and IES TM-30 reports. For object colors, compute optimal colors and Logvinenko coordinates. Work with the standard CIE illuminants and color matching functions, and read spectra from text files, including CGATS files. Estimate a spectrum from its response. A user guide and 9 vignettes are included.