This package is an R package designed for QC, analysis, and exploration of single cell RNA-seq data. It easily enables widely-used analytical techniques, including the identification of highly variable genes, dimensionality reduction; PCA, ICA, t-SNE, standard unsupervised clustering algorithms; density clustering, hierarchical clustering, k-means, and the discovery of differentially expressed genes and markers.

Lambert W x F distributions are a generalized framework to analyze skewed, heavy-tailed data. It is based on an input/output system, where the output random variable (RV) Y is a non-linearly transformed version of an input RV X ~ F with similar properties as X, but slightly skewed (heavy-tailed). The transformed RV Y has a Lambert W x F distribution. This package contains functions to model and analyze skewed, heavy-tailed data the Lambert Way: simulate random samples, estimate parameters, compute quantiles, and plot/ print results nicely. The most useful function is Gaussianize, which works similarly to scale, but actually makes the data Gaussian. A do-it-yourself toolkit allows users to define their own Lambert W x MyFavoriteDistribution and use it in their analysis right away.

When analyzing data, plots are a helpful tool for visualizing data and interpreting statistical models. This package provides a set of simple tools for building plots incrementally, starting with an empty plot region, and adding bars, data points, regression lines, error bars, gradient legends, density distributions in the margins, and even pictures. The package builds further on R graphics by simply combining functions and settings in order to reduce the amount of code to produce for the user. As a result, the package does not use formula input or special syntax, but can be used in combination with default R plot functions.

This package provides an interface from R to Python modules, classes, and functions. When calling into Python, R data types are automatically converted to their equivalent Python types. When values are returned from Python to R they are converted back to R types.

Estimate generalized additive mixed models via a version of function gamm from the mgcv package, using the lme4 packagefor estimation.

Assertthat is an extension to stopifnot() that makes it easy to declare the pre and post conditions that your code should satisfy, while also producing friendly error messages so that your users know what they've done wrong.

This package provides tools to enumerates the partitions, unequal partitions, and restricted partitions of an integer; the three corresponding partition functions are also given.

Fit Conway-Maxwell Poisson (COM-Poisson or CMP) regression models to count data (Sellers & Shmueli, 2010) <doi:10.1214/09-AOAS306>. The package provides functions for model estimation, dispersion testing, and diagnostics. Zero-inflated CMP regression (Sellers & Raim, 2016) <doi:10.1016/j.csda.2016.01.007> is also supported.

This package provides a more comfortable interface to work with R data or source files in a key-value fashion.

This package contains a simple SMTP client which provides a portable solution for sending email, including attachments, from within R.

This package provides an enum-type representation of vectors and representation of intervals, including a method of coercing variables in data frames.

This package provides conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems.

This package provides a fast match replacement for cases that require repeated look-ups. It is slightly faster that R's built-in match function on first match against a table, but extremely fast on any subsequent lookup as it keeps the hash table in memory.

This package provides a forest plot that allows for multiple confidence intervals per row, custom fonts for each text element, custom confidence intervals, text mixed with expressions, and more. The aim is to extend the use of forest plots beyond meta-analyses. This is a more general version of the original rmeta package's forestplot() function and relies heavily on the grid package.

This package is an implementation of about 6 major classes of statistical regression models. Currently only fixed-effects models are implemented, i.e., no random-effects models. Many (150+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE, using Fisher scoring. VGLMs can be loosely thought of as multivariate generalised linear models.

Sending functions to remote processes can be wasteful of resources because they carry their environments with them. With this package, it is easy to create functions that are isolated from their environment. These isolated functions, also called crates, print to the console with their total size and can be easily tested locally before being sent to a remote.

This package runs R-code present in a pandoc markdown file and includes the resulting output in the resulting markdown file. This file can then be converted into any of the output formats supported by pandoc. The package can also be used as an engine for writing package vignettes.

This package provides a series of additional Tcl commands and Tk widgets with style and various functions to supplement the tcltk package

Provides implementations of functions which have been introduced in R since version 3.0.0. The backports are conditionally exported which results in R resolving the function names to the version shipped with R (if available) and uses the implemented backports as fallback. This way package developers can make use of the new functions without worrying about the minimum required R version.

In putative Transcription Factor Binding Sites (TFBSs) identification from sequence/alignments, we are interested in the significance of certain match scores. TFMPvalue provides the accurate calculation of a p-value with a score threshold for position weight matrices, or the score with a given p-value. It is an interface to code originally made available by Helene Touzet and Jean-Stephane Varre, 2007, Algorithms Mol Biol:2, 15. Touzet and Varre (2007).

This package facilitates mapping by making natural earth map data from https://www.naturalearthdata.com/ more easily available to R users.

This package is a toolkit for working with Bezier curves and splines. The package provides functions for point generation, arc length estimation, degree elevation and curve fitting.

This package provides a collection of dimensionality reduction techniques from R packages and provides a common interface for calling the methods.

This package provides .C64(), an enhanced version of .C() and .Fortran() from the R foreign function interface. .C64() supports long vectors, arguments of type 64-bit integer, and provides a mechanism to avoid unnecessary copies of read-only and write-only arguments. This makes it a convenient and fast interface to C/C++ and Fortran code.