Fit linear models to overdispersed count data. The package can estimate the overdispersion and fit repeated models for matrix input. It is designed to handle large input datasets as they typically occur in single cell RNA-seq experiments.
This package provides a syntax highlighter for R code based on the results of the R parser. It supports rendering in HTML and LaTeX markup. It includes a custom Sweave driver performing syntax highlighting of R code chunks.
This package provides functions for the truncated normal distribution with mean equal to mean
and standard deviation equal to sd
. It includes density, distribution, quantile, and expected value functions, as well as a random generation function.
This package provides fundamental physical constants (quantity, value, uncertainty, unit) for SI and non-SI units, plus unit conversions based on the data from NIST, USA.
Radix trees, or tries, are key-value data structures optimized for efficient lookups, similar in purpose to hash tables. This package provides an implementation of radix trees for use in R programming and in developing packages with Rcpp.
This crates aims ease the interaction with huggingface. It aims to be compatible with huggingface_hub python package, but only implements a smaller subset of functions.
Spring is a Ruby on Rails application preloader. It speeds up development by keeping your application running in the background so the application does need to boot it every time you run a test, rake task or migration.
This package contains functions to download, cache and read in Excel version of the RAM Legacy Stock Assessment Data Base, an online compilation of stock assessment results for commercially exploited marine populations from around the world. The database is named after Dr. Ransom A. Myers whose original stock-recruitment database, is no longer being updated. More information about the database can be found at <https://ramlegacy.org/>. Ricard, D., Minto, C., Jensen, O.P. and Baum, J.K. (2012) <doi:10.1111/j.1467-2979.2011.00435.x>.
This function conducts variation partitioning and hierarchical partitioning to calculate the unique, shared (referred as to "common") and individual contributions of each predictor (or matrix) towards explained variation (R-square and adjusted R-square) on canonical analysis (RDA,CCA and db-RDA), applying the algorithm of Lai J.,Zou Y., Zhang J.,Peres-Neto P.(2022) Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.Methods in Ecology and Evolution,13: 782-788 <DOI:10.1111/2041-210X.13800>.
ViennaCL
is a free open-source linear algebra library for computations on many-core architectures (GPUs, MIC) and multi-core CPUs. The library is written in C++ and supports CUDA', OpenCL
', and OpenMP
(including switches at runtime). I have placed these libraries in this package as a more efficient distribution system for CRAN. The idea is that you can write a package that depends on the ViennaCL
library and yet you do not need to distribute a copy of this code with your package.
An implementation of Bayesian online changepoint detection (Adams and MacKay
(2007) <doi:10.48550/arXiv.0710.3742>
) with an option for probability based outlier detection and removal (Wendelberger et. al. (2021) <doi:10.48550/arXiv.2112.12899>
). Building on the independent multivariate constant mean model implemented in the R package ocp', this package models multivariate data as multivariate normal about a linear trend, defined by user input covariates, with an unstructured error covariance. Changepoints are identified based on a probability threshold for windows of points.
This package provides an easy way to report the results of regression analysis, including: 1. Proportional hazards regression from function coxph of package survival'; 2. Conditional logistic regression from function clogit of package survival'; 3. Ordered logistic regression from function polr of package MASS'; 4. Binary logistic regression from function glm of package stats'; 5. Linear regression from function lm of package stats'; 6. Risk regression model for survival analysis with competing risks from function FGR of package riskRegression
'; 7. Multilevel model from function lme of package nlme'.
We curated 147 of expression array, from 3 species(human,mouse,rat), 3 companies('Affymetrix','Illumina','Agilent'), by aligning the Fasta sequences of all probes of each platform to their corresponding reference genome, and then annotate them to genes.
Visualizing the types and distribution of elements within bio-sequences. At the same time, We have developed a geom layer, geom_rrect()
, that can generate rounded rectangles. No external references are used in the development of this package.
This package provides functions to create and select graphical themes for the base plotting system. Contains: 1) several custom pre-made themes 2) mechanism for creating new themes by making persistent changes to the graphical parameters of base plots.
Create descriptive file names with ease. New file names are automatically (but optionally) time stamped and placed in date stamped directories. Streamline your analysis pipeline with input and output file names that have informative tags and proper file extensions.
Supports fMRI
(functional magnetic resonance imaging) analysis tasks including reading in CIFTI', GIFTI and NIFTI data, temporal filtering, nuisance regression, and aCompCor
(anatomical Components Correction) (Muschelli et al. (2014) <doi:10.1016/j.neuroimage.2014.03.028>).
This package provides a ggplot2 extension for visualizing vector fields in two-dimensional space. Provides flexible tools for creating vector and stream field layers, visualizing gradients and potential fields, and smoothing vector and scalar data to estimate underlying patterns.
This is a dataset package for GANPA, which implements a network-based gene weighting approach to pathway analysis. This package includes data useful for GANPA, such as a functional association network, pathways, an expression dataset and multi-subunit proteins.
Providing publication-ready graphs for Multiple sequence alignment. Moreover, it provides a unique solution for visualizing the multiple sequence alignment without the need to do the alignment in each run which is a big limitation in other available packages.
Interacts with the Glassdoor API <https://www.glassdoor.com/developer/index.htm>. Allows the user to search job statistics, employer statistics, and job progression, where Glassdoor provides a breakdown of other jobs a person did after their current one.
Simple handling of survey data. Smart handling of meta-information like e.g. variable-labels value-labels and scale-levels. Easy access and validation of meta-information. Useage of value labels and values respectively for subsetting and recoding data.
This package provides a runtime type system, allowing users to define and implement interfaces, enums, typed data.frame/data.table, as well as typed functions. This package enables stricter type checking and validation, improving code structure, robustness and reliability.
This package provides model fitting, prediction, and plotting for joint models of longitudinal and multiple time-to-event data, including methods from Rizopoulos (2012) <doi:10.1201/b12208>. Useful for handling complex survival and longitudinal data in clinical research.