The complete scripts from the American version of the Office television show in tibble format. Use this package to analyze and have fun with text from the best series of all time.

Perform joint segmentation on two signal dimensions derived from total read depth (intensity) and allele specific read depth (intensity) for whole genome sequencing (WGS), whole exome sequencing (WES) and SNP array data.

Routines for computing different types of linear estimators, based on instrumental variables (IVs), including the semi-parametric Stein-like (SPS) estimator, originally introduced by Judge and Mittelhammer (2004) <DOI:10.1198/016214504000000430>.

Create scaled ggplot representations of playing surfaces. Playing surfaces are drawn pursuant to rule-book specifications. This package should be used as a baseline plot for displaying any type of tracking data.

An interactive document on the topic of variance analysis using rmarkdown and shiny packages. Runtime examples are provided in the package function as well as at <https://predanalyticssessions1.shinyapps.io/chisquareVarianceTest/>.

The XML-RPC is a remote procedure call protocol based on XML'. The xmlrpc2 package is inspired by the XMLRPC package but uses the curl and xml2 packages instead RCurl and XML'.

Write YAML front matter for R Markdown and related documents. Work with YAML objects more naturally and write the resulting YAML to your clipboard or to YAML files related to your project.

This package provides a toolkit for making antigenic maps from immunological assay data, in order to quantify and visualize antigenic differences between different pathogen strains as described in Smith et al. (2004) <doi:10.1126/science.1097211> and used in the World Health Organization influenza vaccine strain selection process. Additional functions allow for the diagnostic evaluation of antigenic maps and an interactive viewer is provided to explore antigenic relationships amongst several strains and incorporate the visualization of associated genetic information.

Collection of functions to evaluate sequences, decode hidden states and estimate parameters from a single or multiple sequences of a discrete time Hidden Markov Model. The observed values can be modeled by a multinomial distribution for categorical/labeled emissions, a mixture of Gaussians for continuous data and also a mixture of Poissons for discrete values. It includes functions for random initialization, simulation, backward or forward sequence evaluation, Viterbi or forward-backward decoding and parameter estimation using an Expectation-Maximization approach.

The real-time quantitative polymerase chain reaction (qPCR) technical data sets by Ruijter et al. (2013) <doi:10.1016/j.ymeth.2012.08.011>: (i) the four-point 10-fold dilution series; (ii) 380 replicates; and (iii) the competimer data set. These three data sets can be used to benchmark qPCR methods. Original data set is available at <https://medischebiologie.nl/wp-content/uploads/2019/02/qpcrdatamethods.zip>. This package fixes incorrect annotations in the original data sets.

This package wraps common clustering algorithms in an easily extended S4 framework. Backends are implemented for hierarchical, k-means and graph-based clustering. Several utilities are also provided to compare and evaluate clustering results.

This package simulates the process of installing a package and then attaching it. This is a key part of the devtools package as it allows you to rapidly iterate while developing a package.

This package implements list environments. List environments are environments that have list-like properties. For instance, the elements of a list environment are ordered and can be accessed and iterated over using index subsetting.

This package provides methods for cluster analysis. It is a much extended version of the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) "Finding Groups in Data".

Currently there are many functions in S-PLUS that are missing in R. To facilitate the conversion of S-PLUS packages to R packages, this package provides some missing S-PLUS functionality in R.

Create and customize interactive maps using the Leaflet JavaScript library and the htmlwidgets package. These maps can be used directly from the R console, from RStudio, in Shiny applications and R Markdown documents.

This R package contains examples from the book Regression for Categorical Data, Tutz 2012, Cambridge University Press. The names of the examples refer to the chapter and the data set that is used.

blame outputs an annotated revision from each RCS file. An annotated RCS file describes the revision and date in which each line was added to the file, and the author of each line.

Clomial fits binomial distributions to counts obtained from Next Gen Sequencing data of multiple samples of the same tumor. The trained parameters can be interpreted to infer the clonal structure of the tumor.

This package provides a general tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables as described in Pounds et. al. (2009) Bioinformatics 25: 2013-2019.

This includes a set of convenience functions for working with the SummarizedExperiment class. Note that plotting functions historically in this package have been moved to the sechm package (see vignette for details).

This package implements a parametric semi-supervised mixture model. The permutation test detects markers with main or interactive effects, without distinguishing them. Possible applications include genome-wide association analysis and differential expression analysis.

Point-scale variogram deconvolution from irregular/regular spatial support according to Goovaerts, P., (2008) <doi: 10.1007/s11004-007-9129-1>; ordinary area-to-area (co)Kriging and area-to-point (co)Kriging.

Whitening is the first step of almost all blind source separation (BSS) methods. A fast implementation of whitening for BSS is implemented to serve as a lightweight dependency for packages providing BSS methods.