DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It models the expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.

A streamgraph is a type of stacked area chart. It represents the evolution of a numeric variable for several groups. Areas are usually displayed around a central axis, and edges are rounded to give a flowing shape. This package provides an htmlwidget for building streamgraph visualizations.

This package provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.

This R package provides functions to create formattable vectors and data frames. Formattable vectors are printed with text formatting, and formattable data frames are printed with multiple types of formatting in HTML to improve the readability of data presented in tabular form rendered in web pages.

Pinentry-rofi is a simple graphical user interface for passphrase or PIN when required by gpg or other software. It is using the Rofi application launcher as the user interface. Which makes it combined with rofi-pass a good front end for password-store.

cl-rmath is a simple, autogenerated foreign interface for the standalone R API libRmath. There has been no effort to provide a high-level interface for the original library, instead, this library is meant to serve as a building block for such an interface.

Test::Run is an improved test harness, originally based on Test::Harness version 2.xx by Michael G. Schwern, Andy Lester and others.

The top-level "Test::Run" by itself does not do much. You should refer to Task::Test::Run::AllPlugins for more detailed instructions.

This package provides example datasets for the iModMix package, including gene, protein, and metabolite partial correlation matrices derived from ccRCC4 and FloresData_K_TK studies. The data are preprocessed and ready to use for testing, demonstrating iModMix workflows, and exploring correlation networks.

Download Barcode, UMI, and Set (BUS) format of 10x datasets from within R. This package accompanies the package BUSpaRse, which can load BUS format into R as a sparse matrix, and which has utility functions related to using the C++ command line package bustools.

Computes low-dimensional point representations of high-dimensional numerical data according to the data visualization method Adaptable Radial Axes described in: Manuel Rubio-Sánchez, Alberto Sanchez, and Dirk J. Lehmann (2017) "Adaptable radial axes plots for improved multivariate data visualization" <doi:10.1111/cgf.13196>.

Modeling the correlation transitions under specified distributional assumptions within the realm of discretization in the context of the latency and threshold concepts. The details of the method are explained in Demirtas, H. and Vardar-Acar, C. (2017) <DOI:10.1007/978-981-10-3307-0_4>.

Around 10% of almost any predictive modeling project is spent in predictive modeling, funModeling and the book Data Science Live Book (<https://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables dataViz', assessing model performance and other functions.

Splits date and time of day components from continuous datetime objects, then plots them using grammar of graphics ('ggplot2'). Plots can also be decorated with solar cycle information (e.g., sunset, sunrise, etc.). This is useful for visualising data that are associated with the solar cycle.

Methodology that combines feature selection, model tuning, and parsimonious model selection with Genetic Algorithms (GA) proposed in Martinez-de-Pison (2015) <DOI:10.1016/j.asoc.2015.06.012>. To this objective, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.

Companion toolbox for structural equation models fitted with lavaan'. Provides post-estimation diagnostics and graphics that operate directly on a fitted object using its estimates and covariance, and refits auxiliary models when needed. The package relies on lavaan (Rosseel, 2012) <doi:10.18637/jss.v048.i02>.

This package provides functions and datasets for readers of the book "Le logiciel R: Maitriser le langage, Effectuer des analyses statistiques" by Lafaye de Micheaux, Drouilhet and Liquet (2011) <doi:10.1007/978-2-8178-0115-5>. The documentation and help pages are written in French.

Analyse and visualise multi electrode array data at the single electrode and whole well level, downstream of AxIS Navigator 3.6.2 Software processing. Compare bursting parameters between time intervals and recordings using the bar chart visualisation functions. Compatible with 12- and 24- well plates.

The package is used for calibrating the design parameters for single-to-double arm transition design proposed by Shi and Yin (2017). The calibration is performed via numerical enumeration to find the optimal design that satisfies the constraints on the type I and II error rates.

This package provides functions to generate or sample from all possible splits of features or variables into a number of specified groups. Also computes the best split selection estimator (for low-dimensional data) as defined in Christidis, Van Aelst and Zamar (2019) <arXiv:1812.05678>.

This package provides a step-down procedure for controlling the False Discovery Proportion (FDP) in a competition-based setup, implementing Dong et al. (2020) <arXiv:2011.11939>. Such setups include target-decoy competition (TDC) in computational mass spectrometry and the knockoff construction in linear regression.

Total variation denoising can be used to approximate a given sequence of noisy observations by a piecewise constant sequence, with adaptively-chosen break points. An efficient linear-time algorithm for total variation denoising is provided here, based on Johnson (2013) <doi:10.1080/10618600.2012.681238>.

This package implements the Whale Optimization Algorithm(WOA) for k-medoids clustering, providing tools for effective and efficient cluster analysis in various data sets. The methodology is based on "The Whale Optimization Algorithm" by Mirjalili and Lewis (2016) <doi:10.1016/j.advengsoft.2016.01.008>.

This package provides comprehensive methods to measure disclosure risk and data utility for anonymized and synthetic data. Implements attribution-based risk metrics including Correct Attribution Probability (CAP), Targeted CAP (TCAP), Within Equivalence Class Attribution Probability (WEAP), and RAPID (Risk of Attribute Prediction-Induced Disclosure). Also provides distance-based privacy metrics such as Distance to Closest Record (DCR), Nearest Neighbor Distance Ratio (NNDR), and Identical Match Share (IMS). Utility assessment includes propensity score analysis, distribution comparisons, and various statistical tests. Methods are based on Taub et al. (2018) <doi:10.1007/978-3-319-99771-1_9> and related literature. Designed for integration with simPop S4 classes.

This package provides a normalization method for single-cell UMI count data using a variance stabilizing transformation. The transformation is based on a negative binomial regression model with regularized parameters. As part of the same regression framework, this package also provides functions for batch correction, and data correction.