The SeqSQC is designed to identify problematic samples in NGS data, including samples with gender mismatch, contamination, cryptic relatedness, and population outlier.

Cicero computes putative cis-regulatory maps from single-cell chromatin accessibility data. It also extends the monocle package for use in chromatin accessibility data.

This package contains class definitions for two-color spotted microarray data. It also includes functions for data input, diagnostic plots, normalization and quality checking.

This package is a compatibility wrapper to replace the orphaned package by Romain Francois. New applications should use the openssl or base64enc package instead.

This package provides tools to fit a variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth curve models.

Create rich and fully interactive 3D visualizations of molecular data. Visualizations can be included in Shiny apps and R markdown documents, or viewed from the R console and RStudio Viewer. r3dmol includes an extensive API to manipulate the visualization after creation, and supports getting data out of the visualization into R. Based on the 3dmol.js and the htmlwidgets R package.

This package provides a Tidy implementation of grouping sets', rollup and cube - extensions of the group_by clause that allow for computing multiple group_by clauses in a single statement. For more detailed information on these functions, please refer to "Enhanced Aggregation, Cube, Grouping and Rollup" <https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C+Grouping+and+Rollup>.

This package provides a collection of fast statistical and utility functions for data analysis. Functions for regression, maximum likelihood, column-wise statistics and many more have been included. C++ has been utilized to speed up the functions. References: Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>.

This package provides functions to retrieve data and metadata from providers that disseminate data by means of SDMX web services. SDMX (Statistical Data and Metadata eXchange) is a standard that has been developed with the aim of simplifying the exchange of statistical information. More about the SDMX standard and the SDMX Web Services can be found at: <https://sdmx.org>.

recoup calculates and plots signal profiles created from short sequence reads derived from Next Generation Sequencing technologies. The profiles provided are either sumarized curve profiles or heatmap profiles. Currently, recoup supports genomic profile plots for reads derived from ChIP-Seq and RNA-Seq experiments. The package uses ggplot2 and ComplexHeatmap graphics facilities for curve and heatmap coverage profiles respectively.

This package provides a computational resource designed to accurately detect microbial nucleic acids while filtering out contaminants and false-positive taxonomic assignments from standard transcriptomic sequencing of mammalian tissues. For more details, see Ghaddar (2023) <doi:10.1038/s43588-023-00507-1>. This implementation leverages the polars package for fast and systematic microbial signal recovery and denoising from host tissue genomic sequencing.

Non-linear inversion for hypocenter estimation and analysis of seismic data collected continuously, or in trigger mode. The functions organize other functions from RSEIS and GEOmap to help researchers pick, locate, and store hypocenters for detailed seismic investigation. Error ellipsoids and station influence are estimated via jackknife analysis. References include Iversen, E. S., and J. M. Lees (1996)<doi:10.1785/BSSA0860061853>.

Adaptive wavelet lifting transforms for signal denoising using optimal local neighbourhood regression, from Nunes et al. (2006) <doi:10.1007/s11222-006-6560-y>.

This package provides functions to implement a Hwang(2021) <doi:10.2139/ssrn.3866876> estimator, which bounds an omitted variable bias using auxiliary data.

Regression for data too large to fit in memory. This package functions exactly like the biglm package, but works with later versions of R.

This package provides a collection of functions to analyse, visualize and interpret wind data and to calculate the potential energy production of wind turbines.

Wraps the CIRCE (<https://github.com/ohdsi/circe-be>) Java library allowing cohort definition expressions to be edited and converted to Markdown or SQL'.

This package implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis. Reference: Li et al. (2023) <arXiv:2306.04700>.

The funFEM algorithm (Bouveyron et al., 2014) allows to cluster functional data by modeling the curves within a common and discriminative functional subspace.

Integrates with your RMarkdown documents to automatically publish figures to the <https://GoFigr.io> service. Supports both knitr and interactive execution within RStudio'.

This package implements a flexible nonlinear modelling framework for nonstationary generalized extreme value analysis in hydroclimatology following Cannon (2010) <doi:10.1002/hyp.7506>.

This package provides a set of functions to analyse and compare texts, using classical text mining functions, as well as those from theoretical ecology.

This package provides tools for probabilistic taxon assignment with informatic sequence classification trees. See Wilkinson et al (2018) <doi:10.7287/peerj.preprints.26812v1>.

Evaluation and optimization of the Fisher Information Matrix in NonLinear Mixed Effect Models using Markov Chains Monte Carlo for continuous and discrete data.