Package Name | Access | Summary | Updated |
---|---|---|---|

r-plotluck | public | Examines the characteristics of a data frame and a formula to automatically choose the most suitable type of plot out of the following supported options: scatter, violin, box, bar, density, hexagon bin, spine plot, and heat map. The aim of the package is to let the user focus on what to plot, rather than on the "how" during exploratory data analysis. It also automates handling of observation weights, logarithmic axis scaling, reordering of factor levels, and overlaying smoothing curves and median lines. Plots are drawn using 'ggplot2'. | 2019-07-20 |

r-platetools | public | Collection of functions for working with multi-well microtitre plates, mainly 96, 384 and 1536 well plates. | 2019-07-20 |

r-pmcmrplus | public | For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided. | 2019-07-20 |

r-plotroc | public | Most ROC curve plots obscure the cutoff values and inhibit interpretation and comparison of multiple curves. This attempts to address those shortcomings by providing plotting and interactive tools. Functions are provided to generate an interactive ROC curve plot for web use, and print versions. A Shiny application implementing the functions is also included. | 2019-07-20 |

r-plumber | public | Gives the ability to automatically generate and serve an HTTP API from R functions using the annotations in the R documentation around your functions. | 2019-07-20 |

r-plsdof | public | The plsdof package provides Degrees of Freedom estimates for Partial Least Squares (PLS) Regression. Model selection for PLS is based on various information criteria (aic, bic, gmdl) or on cross-validation. Estimates for the mean and covariance of the PLS regression coefficients are available. They allow the construction of approximate confidence intervals and the application of test procedures. Further, cross-validation procedures for Ridge Regression and Principal Components Regression are available. | 2019-07-20 |

pyfmmlib | public | Python wrappers for FMMLIB2D and FMMLIB3D | 2019-07-20 |

r-plspm | public | Partial Least Squares Path Modeling (PLS-PM) analysis for both metric and non-metric data, as well as REBUS analysis. | 2019-07-20 |

r-plsvarsel | public | Interfaces and methods for variable selection in Partial Least Squares. The methods include filter methods, wrapper methods and embedded methods. Both regression and classification is supported. | 2019-07-20 |

r-taxize | public | Interacts with a suite of web 'APIs' for taxonomic tasks, such as getting database specific taxonomic identifiers, verifying species names, getting taxonomic hierarchies, fetching downstream and upstream taxonomic names, getting taxonomic synonyms, converting scientific to common names and vice versa, and more. | 2019-07-20 |

xgboost | public | Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow | 2019-07-20 |

py-xgboost-cpu | public | Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow | 2019-07-20 |

py-xgboost | public | Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow | 2019-07-20 |

r-pool | public | Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Currently the only supported pooled objects are 'DBI' connections. | 2019-07-20 |

r-xgboost-cpu | public | 2019-07-20 | |

r-xgboost | public | 2019-07-20 | |

r-polycor | public | Computes polychoric and polyserial correlations by quick "two-step" methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases. | 2019-07-20 |

libxgboost | public | 2019-07-20 | |

r-mixomics | public | Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares. | 2019-07-20 |

r-precrec | public | Accurate calculations and visualization of precision-recall and ROC (Receiver Operator Characteristics) curves. | 2019-07-20 |

r-purrrlyr | public | Some functions at the intersection of 'dplyr' and 'purrr' that formerly lived in 'purrr'. | 2019-07-20 |

r-qtlrel | public | This software provides tools for quantitative trait mapping in populations such as advanced intercross lines where relatedness among individuals should not be ignored. It can estimate background genetic variance components, impute missing genotypes, simulate genotypes, perform a genome scan for putative quantitative trait loci (QTL), and plot mapping results. It also has functions to calculate identity coefficients from pedigrees, especially suitable for pedigrees that consist of a large number of generations, or estimate identity coefficients from genotypic data in certain circumstances. | 2019-07-20 |

r-propr | public | An R package to calculate proportionality between vectors of compositional data | 2019-07-20 |

r-profvis | public | Interactive visualizations for profiling R code. | 2019-07-20 |

r-princurve | public | Fitting a principal curve to a data matrix in arbitrary dimensions. Hastie and Stuetzle (1989) <doi:10.2307/2289936>. | 2019-07-20 |

r-proxyc | public | Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. Among several built-in similarity/distance measures, computation of correlation, cosine similarity and Euclidean distance is particularly fast. | 2019-07-20 |

r-ptw | public | Parametric Time Warping aligns patterns, i.e. it aims to put corresponding features at the same locations. The algorithm searches for an optimal polynomial describing the warping. It is possible to align one sample to a reference, several samples to the same reference, or several samples to several references. One can choose between calculating individual warpings, or one global warping for a set of samples and one reference. Two optimization criteria are implemented: RMS (Root Mean Square error) and WCC (Weighted Cross Correlation). Both warping of peak profiles and of peak lists are supported. | 2019-07-20 |

r-cyphr | public | Encryption wrappers, using low-level support from 'sodium' and 'openssl'. 'cyphr' tries to smooth over some pain points when using encryption within applications and data analysis by wrapping around differences in function names and arguments in different encryption providing packages. It also provides high-level wrappers for input/output functions for seamlessly adding encryption to existing analyses. | 2019-07-20 |

r-psychotools | public | Infrastructure for psychometric modeling such as data classes (for item response data and paired comparisons), basic model fitting functions (for Bradley-Terry, Rasch, parametric logistic IRT, generalized partial credit, rating scale, multinomial processing tree models), extractor functions for different types of parameters (item, person, threshold, discrimination, guessing, upper asymptotes), unified inference and visualizations, and various datasets for illustration. Intended as a common lightweight and efficient toolbox for psychometric modeling and a common building block for fitting psychometric mixture models in package "psychomix" and trees based on psychometric models in package "psychotree". | 2019-07-20 |

r-prettydoc | public | Creating tiny yet beautiful documents and vignettes from R Markdown. The package provides the 'html_pretty' output format as an alternative to the 'html_document' and 'html_vignette' engines that convert R Markdown into HTML pages. Various themes and syntax highlight styles are supported. | 2019-07-20 |

r-prophet | public | Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. | 2019-07-20 |

r-prroc | public | Computes the areas under the precision-recall (PR) and ROC curve for weighted (e.g., soft-labeled) and unweighted data. In contrast to other implementations, the interpolation between points of the PR curve is done by a non-linear piecewise function. In addition to the areas under the curves, the curves themselves can also be computed and plotted by a specific S3-method. References: Davis and Goadrich (2006) <doi:10.1145/1143844.1143874>; Keilwagen et al. (2014) <doi:10.1371/journal.pone.0092209>; Grau et al. (2015) <doi:10.1093/bioinformatics/btv153>. | 2019-07-20 |

r-ppcor | public | Calculates partial and semi-partial (part) correlations along with p-value. | 2019-07-20 |

r-preseqr | public | Originally as an R version of Preseq <doi:10.1038/nmeth.2375>, the package has extended its functionality to predict the r-species accumulation curve (r-SAC), which is the number of species represented at least r times as a function of the sampling effort. When r = 1, the curve is known as the species accumulation curve, or the library complexity curve in high-throughput genomic sequencing. The package includes both parametric and nonparametric methods, as described by Deng C, et al. (2018) <arXiv:1607.02804v3>. | 2019-07-20 |

r-propcis | public | Computes two-sample confidence intervals for single, paired and independent proportions. | 2019-07-20 |

r-powerlaw | public | An implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region. | 2019-07-20 |

r-probably | public | Models can be improved by post-processing class probabilities, by: recalibration, conversion to hard probabilities, assessment of equivocal zones, and other activities. 'probably' contains tools for conducting these operations. | 2019-07-20 |

r-qlcmatrix | public | Extension of the functionality of the Matrix package for using sparse matrices. Some of the functions are very general, while other are highly specific for special data format as used for quantitative language comparison (QLC). | 2019-07-20 |

r-printr | public | Extends the S3 generic function knit_print() in 'knitr' to automatically print some objects using an appropriate format such as Markdown or LaTeX. For example, data frames are automatically printed as tables, and the help() pages can also be rendered in 'knitr' documents. | 2019-07-20 |

r-ptxqc | public | Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite. Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) 'doi:10.1021/acs.jproteome.5b00780'. | 2019-07-20 |

r-qiimer | public | Open QIIME output files in R, compute statistics, and create plots from the data. | 2019-07-20 |

r-tsibbledata | public | Provides diverse datasets in the 'tsibble' data structure. These datasets are useful for learning and demonstrating how tidy temporal data can tidied, visualised, and forecasted. | 2019-07-20 |

r-qtlcharts | public | Web-based interactive charts (using D3.js) for the analysis of experimental crosses to identify genetic loci (quantitative trait loci, QTL) contributing to variation in quantitative traits. | 2019-07-20 |

r-pvclust | public | An implementation of multiscale bootstrap resampling for assessing the uncertainty in hierarchical cluster analysis. It provides AU (approximately unbiased) p-value as well as BP (bootstrap probability) value for each cluster in a dendrogram. | 2019-07-20 |

harfbuzz | public | An OpenType text shaping engine. | 2019-07-20 |

r-rbamtools | public | Provides an R interface to functions of the 'SAMtools' C-Library by Heng Li <http://www.htslib.org/>. | 2019-07-20 |

r-ragg | public | Anti-Grain Geometry (AGG) is a high-quality and high-performance 2D drawing library. The 'ragg' package provides a set of graphic devices based on AGG to use as alternative to the raster devices provided through the 'grDevices' package. | 2019-07-20 |

r-randomforestsrc | public | Fast OpenMP parallel computing of Breiman's random forests for survival, competing risks, regression and classification based on Ishwaran and Kogalur's popular random survival forests (RSF) package. Handles missing data and now includes multivariate, unsupervised forests, quantile regression and solutions for class imbalanced data. New fast interface using subsampling and confidence regions for variable importance. | 2019-07-20 |

r-rcppgsl | public | 'Rcpp' integration for 'GNU GSL' vectors and matrices The 'GNU Scientific Library' (or 'GSL') is a collection of numerical routines for scientific computing. It is particularly useful for C and C++ programs as it provides a standard C interface to a wide range of mathematical routines. There are over 1000 functions in total with an extensive test suite. The 'RcppGSL' package provides an easy-to-use interface between 'GSL' data structures and R using concepts from 'Rcpp' which is itself a package that eases the interfaces between R and C++. This package also serves as a prime example of how to build a package that uses 'Rcpp' to connect to another third-party library. The 'autoconf' script, 'inline' plugin and example package can all be used as a stanza to write a similar package against another library. | 2019-07-20 |

r-randomizr | public | Generates random assignments for common experimental designs and random samples for common sampling designs. | 2019-07-20 |

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