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henrikbengtsson

matrixStats:Functions that Apply to Rows and Columns of Matrices (and to Vectors)

High-performing functions operating on rows and columns of matrices, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e.g. binMeans(), madDiff() and weightedMedian().

Maintained by Henrik Bengtsson. Last updated 3 months ago.

matrixperformancevector

208 stars 18.09 score 20k scripts 2.3k dependents

bioc

DelayedArray:A unified framework for working transparently with on-disk and in-memory array-like datasets

Wrapping an array-like object (typically an on-disk object) in a DelayedArray object allows one to perform common array operations on it without loading the object in memory. In order to reduce memory usage and optimize performance, operations on the object are either delayed or executed using a block processing mechanism. Note that this also works on in-memory array-like objects like DataFrame objects (typically with Rle columns), Matrix objects, ordinary arrays and, data frames.

Maintained by Hervé Pagès. Last updated 2 months ago.

infrastructuredatarepresentationannotationgenomeannotationbioconductor-packagecore-packageu24ca289073

27 stars 15.59 score 538 scripts 1.2k dependents

rfastofficial

Rfast:A Collection of Efficient and Extremely Fast R Functions

A collection of fast (utility) functions for data analysis. Column and row wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions. References: a) Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>. b) Tsagris M. and Papadakis M. (2018). Forward regression in R: from the extreme slow to the extreme fast. Journal of Data Science, 16(4): 771--780. <doi:10.6339/JDS.201810_16(4).00006>. c) Chatzipantsiou C., Dimitriadis M., Papadakis M. and Tsagris M. (2020). Extremely Efficient Permutation and Bootstrap Hypothesis Tests Using Hypothesis Tests Using R. Journal of Modern Applied Statistical Methods, 18(2), eP2898. <doi:10.48550/arXiv.1806.10947>. d) Tsagris M., Papadakis M., Alenazi A. and Alzeley O. (2024). Computationally Efficient Outlier Detection for High-Dimensional Data Using the MDP Algorithm. Computation, 12(9): 185. <doi:10.3390/computation12090185>. e) Tsagris M. and Papadakis M. (2025). Fast and light-weight energy statistics using the R package Rfast. <doi:10.48550/arXiv.2501.02849>.

Maintained by Manos Papadakis. Last updated 1 months ago.

openblascppopenmp

147 stars 12.67 score 1.2k scripts 174 dependents

bioc

SparseArray:High-performance sparse data representation and manipulation in R

The SparseArray package provides array-like containers for efficient in-memory representation of multidimensional sparse data in R (arrays and matrices). The package defines the SparseArray virtual class and two concrete subclasses: COO_SparseArray and SVT_SparseArray. Each subclass uses its own internal representation of the nonzero multidimensional data: the "COO layout" and the "SVT layout", respectively. SVT_SparseArray objects mimic as much as possible the behavior of ordinary matrix and array objects in base R. In particular, they suppport most of the "standard matrix and array API" defined in base R and in the matrixStats package from CRAN.

Maintained by Hervé Pagès. Last updated 12 days ago.

infrastructuredatarepresentationbioconductor-packagecore-packageopenmp

9 stars 12.47 score 79 scripts 1.2k dependents

bioc

sparseMatrixStats:Summary Statistics for Rows and Columns of Sparse Matrices

High performance functions for row and column operations on sparse matrices. For example: col / rowMeans2, col / rowMedians, col / rowVars etc. Currently, the optimizations are limited to data in the column sparse format. This package is inspired by the matrixStats package by Henrik Bengtsson.

Maintained by Constantin Ahlmann-Eltze. Last updated 5 months ago.

infrastructuresoftwaredatarepresentationcpp

54 stars 11.98 score 174 scripts 130 dependents

bioc

DelayedMatrixStats:Functions that Apply to Rows and Columns of 'DelayedMatrix' Objects

A port of the 'matrixStats' API for use with DelayedMatrix objects from the 'DelayedArray' package. High-performing functions operating on rows and columns of DelayedMatrix objects, e.g. col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized.

Maintained by Peter Hickey. Last updated 3 months ago.

infrastructuredatarepresentationsoftware

16 stars 11.86 score 211 scripts 112 dependents

bioc

MatrixGenerics:S4 Generic Summary Statistic Functions that Operate on Matrix-Like Objects

S4 generic functions modeled after the 'matrixStats' API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. Other package developers can import this package and handle a different matrix implementations without worrying about incompatibilities.

Maintained by Peter Hickey. Last updated 3 months ago.

infrastructuresoftwarebioconductor-packagecore-package

12 stars 11.64 score 129 scripts 1.3k dependents

bnprks

BPCells:Single Cell Counts Matrices to PCA

> Efficient operations for single cell ATAC-seq fragments and RNA counts matrices. Interoperable with standard file formats, and introduces efficient bit-packed formats that allow large storage savings and increased read speeds.

Maintained by Benjamin Parks. Last updated 2 months ago.

zlibhdf5cpp

184 stars 7.48 score 172 scripts

cran

fBasics:Rmetrics - Markets and Basic Statistics

Provides a collection of functions to explore and to investigate basic properties of financial returns and related quantities. The covered fields include techniques of explorative data analysis and the investigation of distributional properties, including parameter estimation and hypothesis testing. Even more there are several utility functions for data handling and management.

Maintained by Georgi N. Boshnakov. Last updated 7 months ago.

2 stars 7.19 score 131 dependents

spkaluzny

splus2R:Supplemental S-PLUS Functionality in R

Currently there are many functions in S-PLUS that are missing in R. To facilitate the conversion of S-PLUS packages to R packages, this package provides some missing S-PLUS functionality in R.

Maintained by Stephen Kaluzny. Last updated 1 years ago.

1 stars 6.56 score 82 scripts 30 dependents

rje42

rje:Miscellaneous Useful Functions for Statistics

A series of functions in some way considered useful to the author. These include methods for subsetting tables and generating indices for arrays, conditioning and intervening in probability distributions, generating combinations, fast transformations, and more...

Maintained by Robin Evans. Last updated 1 years ago.

6.50 score 173 scripts 10 dependents

bioc

SCArray:Large-scale single-cell omics data manipulation with GDS files

Provides large-scale single-cell omics data manipulation using Genomic Data Structure (GDS) files. It combines dense and sparse matrices stored in GDS files and the Bioconductor infrastructure framework (SingleCellExperiment and DelayedArray) to provide out-of-memory data storage and large-scale manipulation using the R programming language.

Maintained by Xiuwen Zheng. Last updated 5 days ago.

infrastructuredatarepresentationdataimportsinglecellrnaseqcpp

1 stars 5.32 score 9 scripts 1 dependents

yunuuuu

BPCellsArray:Using BPCells as a DelayedArray Backend

Implements a DelayedArray backend for reading and writing arrays in the BPCells storage layout. The resulting BPCells*Arrays are compatible with all Bioconductor pipelines that can accept DelayedArray instances.

Maintained by Yun Peng. Last updated 8 months ago.

softwaredataimportdatarepresentationinfrastructuresingle-cell

7 stars 4.32 score

clobatofern95

GPUmatrix:Basic Linear Algebra with GPU

GPUs are great resources for data analysis, especially in statistics and linear algebra. Unfortunately, very few packages connect R to the GPU, and none of them are transparent enough to run the computations on the GPU without substantial changes to the code. The maintenance of these packages is cumbersome: several of the earlier attempts have been removed from their respective repositories. It would be desirable to have a properly maintained R package that takes advantage of the GPU with minimal changes to the existing code. We have developed the GPUmatrix package (available on CRAN). GPUmatrix mimics the behavior of the Matrix package and extends R to use the GPU for computations. It includes single(FP32) and double(FP64) precision data types, and provides support for sparse matrices. It is easy to learn, and requires very few code changes to perform the operations on the GPU. GPUmatrix relies on either the Torch or Tensorflow R packages to perform the GPU operations. We have demonstrated its usefulness for several statistical applications and machine learning applications: non-negative matrix factorization, logistic regression and general linear models. We have also included a comparison of GPU and CPU performance on different matrix operations.

Maintained by Cesar Lobato-Fernandez. Last updated 1 years ago.

3.93 score 57 scripts 1 dependents

fanhansen

creditmodel:Toolkit for Credit Modeling, Analysis and Visualization

Provides a highly efficient R tool suite for Credit Modeling, Analysis and Visualization.Contains infrastructure functionalities such as data exploration and preparation, missing values treatment, outliers treatment, variable derivation, variable selection, dimensionality reduction, grid search for hyper parameters, data mining and visualization, model evaluation, strategy analysis etc. This package is designed to make the development of binary classification models (machine learning based models as well as credit scorecard) simpler and faster. The references including: 1 Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: Development and Implementation Using SAS; 2 Bezdek, James C.FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences (0098-3004),<DOI:10.1016/0098-3004(84)90020-7>.

Maintained by Dongping Fan. Last updated 3 years ago.

4 stars 3.48 score 15 scripts

skranz

repgame:Solve discounted repeated games with monetary transfers

Solve discounted repeated games with monetary transfers using the fast Algorithms develeoped by Goldluecke and Kranz (JET, 2013)

Maintained by Sebastian Kranz. Last updated 7 years ago.

cpp

2 stars 2.00 score 3 scripts

skranz

rowmins:Quickly compute min or max of each row or column of a matrix.

Quickly compute min or max of each row or column of a matrix. Is substantially faster than the corresponding functions in matrixStats

Maintained by Sebastian Kranz. Last updated 7 years ago.

cpp

1.48 score 1 dependents

skranz

skUtils:Helper functions for repgames and dyngames

Helper functions needed by my package repgames and dyngames

Maintained by Sebastian Kranz. Last updated 4 years ago.

cpp

1.00 score

cran

SQMtools:Analyze Results Generated by the 'SqueezeMeta' Pipeline

'SqueezeMeta' is a versatile pipeline for the automated analysis of metagenomics/metatranscriptomics data (<https://github.com/jtamames/SqueezeMeta>). This package provides functions loading 'SqueezeMeta' results into R, filtering them based on different criteria, and visualizing the results using basic plots. The 'SqueezeMeta' project (and any subsets of it generated by the different filtering functions) is parsed into a single object, whose different components (e.g. tables with the taxonomic or functional composition across samples, contig/gene abundance profiles) can be easily analyzed using other R packages such as 'vegan' or 'DESeq2'. The methods in this package are further described in Puente-Sánchez et al., (2020) <doi:10.1186/s12859-020-03703-2>.

Maintained by Fernando Puente-Sánchez. Last updated 2 years ago.

1 stars 1.00 score

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