Showing 34 of total 34 results (show query)
rspatial
terra:Spatial Data Analysis
Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Maintained by Robert J. Hijmans. Last updated 22 hours ago.
geospatialrasterspatialvectoronetbbprojgdalgeoscpp
560 stars 17.65 score 17k scripts 856 dependentsrspatial
raster:Geographic Data Analysis and Modeling
Reading, writing, manipulating, analyzing and modeling of spatial data. This package has been superseded by the "terra" package <https://CRAN.R-project.org/package=terra>.
Maintained by Robert J. Hijmans. Last updated 2 days ago.
163 stars 17.23 score 58k scripts 562 dependents
r-forge
Matrix:Sparse and Dense Matrix Classes and Methods
A rich hierarchy of sparse and dense matrix classes, including general, symmetric, triangular, and diagonal matrices with numeric, logical, or pattern entries. Efficient methods for operating on such matrices, often wrapping the 'BLAS', 'LAPACK', and 'SuiteSparse' libraries.
Maintained by Martin Maechler. Last updated 21 days ago.
1 stars 17.23 score 33k scripts 12k dependents
quanteda
quanteda:Quantitative Analysis of Textual Data
A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and n-grams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Maintained by Kenneth Benoit. Last updated 3 months ago.
corpusnatural-language-processingquantedatext-analyticsonetbbcpp
851 stars 16.65 score 5.4k scripts 52 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
r-lib
bit64:A S3 Class for Vectors of 64bit Integers
Package 'bit64' provides serializable S3 atomic 64bit (signed) integers. These are useful for handling database keys and exact counting in +-2^63. WARNING: do not use them as replacement for 32bit integers, integer64 are not supported for subscripting by R-core and they have different semantics when combined with double, e.g. integer64 + double => integer64. Class integer64 can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, characters and factors as well as many elementwise and summary functions. Many fast algorithmic operations such as 'match' and 'order' support inter- active data exploration and manipulation and optionally leverage caching.
Maintained by Michael Chirico. Last updated 18 days ago.
35 stars 14.91 score 1.5k scripts 3.2k dependents
greta-dev
greta:Simple and Scalable Statistical Modelling in R
Write statistical models in R and fit them by MCMC and optimisation on CPUs and GPUs, using Google 'TensorFlow'. greta lets you write your own model like in BUGS, JAGS and Stan, except that you write models right in R, it scales well to massive datasets, and it’s easy to extend and build on. See the website for more information, including tutorials, examples, package documentation, and the greta forum.
Maintained by Nicholas Tierney. Last updated 19 days ago.
566 stars 12.53 score 396 scripts 6 dependentsbioc
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 dependentsbioc
TFBSTools:Software Package for Transcription Factor Binding Site (TFBS) Analysis
TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matirx (PFM), Position Weight Matirx (PWM) and Information Content Matrix (ICM). It can also scan putative TFBS from sequence/alignment, query JASPAR database and provides a wrapper of de novo motif discovery software.
Maintained by Ge Tan. Last updated 18 days ago.
motifannotationgeneregulationmotifdiscoverytranscriptionalignment
28 stars 12.36 score 1.1k scripts 18 dependents
satijalab
SeuratObject:Data Structures for Single Cell Data
Defines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved coordinates. Provides data access methods and R-native hooks to ensure the Seurat object is familiar to other R users. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.
Maintained by Paul Hoffman. Last updated 2 years ago.
25 stars 11.69 score 1.2k scripts 88 dependentsbioc
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 dependentsr-forge
Rmpfr:Interface R to MPFR - Multiple Precision Floating-Point Reliable
Arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental ("special") functions. To this end, the package interfaces to the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library which itself is based on the 'GMP' (GNU Multiple Precision) Library.
Maintained by Martin Maechler. Last updated 5 months ago.
11.30 score 316 scripts 141 dependents
pik-piam
magclass:Data Class and Tools for Handling Spatial-Temporal Data
Data class for increased interoperability working with spatial-temporal data together with corresponding functions and methods (conversions, basic calculations and basic data manipulation). The class distinguishes between spatial, temporal and other dimensions to facilitate the development and interoperability of tools build for it. Additional features are name-based addressing of data and internal consistency checks (e.g. checking for the right data order in calculations).
Maintained by Jan Philipp Dietrich. Last updated 24 days ago.
5 stars 11.16 score 412 scripts 56 dependentsbioc
universalmotif:Import, Modify, and Export Motifs with R
Allows for importing most common motif types into R for use by functions provided by other Bioconductor motif-related packages. Motifs can be exported into most major motif formats from various classes as defined by other Bioconductor packages. A suite of motif and sequence manipulation and analysis functions are included, including enrichment, comparison, P-value calculation, shuffling, trimming, higher-order motifs, and others.
Maintained by Benjamin Jean-Marie Tremblay. Last updated 5 months ago.
motifannotationmotifdiscoverydataimportgeneregulationmotif-analysismotif-enrichment-analysissequence-logocpp
28 stars 11.04 score 342 scripts 12 dependents
wrathematics
float:32-Bit Floats
R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off. The internal representation is an S4 class, which allows us to keep the syntax identical to that of base R's. Interaction between floats and base types for binary operators is generally possible; in these cases, type promotion always defaults to the higher precision. The package ships with copies of the single precision 'BLAS' and 'LAPACK', which are automatically built in the event they are not available on the system.
Maintained by Drew Schmidt. Last updated 21 days ago.
float-matrixhpclinear-algebramatrixfortranopenblasopenmp
46 stars 10.53 score 228 scripts 42 dependents
kaskr
RTMB:'R' Bindings for 'TMB'
Native 'R' interface to 'TMB' (Template Model Builder) so models can be written entirely in 'R' rather than 'C++'. Automatic differentiation, to any order, is available for a rich subset of 'R' features, including linear algebra for dense and sparse matrices, complex arithmetic, Fast Fourier Transform, probability distributions and special functions. 'RTMB' provides easy access to model fitting and validation following the principles of Kristensen, K., Nielsen, A., Berg, C. W., Skaug, H., & Bell, B. M. (2016) <DOI:10.18637/jss.v070.i05> and Thygesen, U.H., Albertsen, C.M., Berg, C.W. et al. (2017) <DOI:10.1007/s10651-017-0372-4>.
Maintained by Kasper Kristensen. Last updated 2 months ago.
54 stars 10.49 score 394 scripts 9 dependentsbioc
Cardinal:A mass spectrometry imaging toolbox for statistical analysis
Implements statistical & computational tools for analyzing mass spectrometry imaging datasets, including methods for efficient pre-processing, spatial segmentation, and classification.
Maintained by Kylie Ariel Bemis. Last updated 3 months ago.
softwareinfrastructureproteomicslipidomicsmassspectrometryimagingmassspectrometryimmunooncologynormalizationclusteringclassificationregression
48 stars 10.32 score 200 scriptsbioc
matter:Out-of-core statistical computing and signal processing
Toolbox for larger-than-memory scientific computing and visualization, providing efficient out-of-core data structures using files or shared memory, for dense and sparse vectors, matrices, and arrays, with applications to nonuniformly sampled signals and images.
Maintained by Kylie A. Bemis. Last updated 4 months ago.
infrastructuredatarepresentationdataimportdimensionreductionpreprocessingcpp
57 stars 9.52 score 64 scripts 2 dependents
reinhardfurrer
spam:SPArse Matrix
Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64). Documentation about 'spam' is provided by vignettes included in this package, see also Furrer and Sain (2010) <doi:10.18637/jss.v036.i10>; see 'citation("spam")' for details.
Maintained by Reinhard Furrer. Last updated 2 months ago.
1 stars 9.36 score 420 scripts 439 dependentsbioc
ScaledMatrix:Creating a DelayedMatrix of Scaled and Centered Values
Provides delayed computation of a matrix of scaled and centered values. The result is equivalent to using the scale() function but avoids explicit realization of a dense matrix during block processing. This permits greater efficiency in common operations, most notably matrix multiplication.
Maintained by Aaron Lun. Last updated 2 months ago.
8.44 score 10 scripts 105 dependents
andreyshabalin
MatrixEQTL:Matrix eQTL: Ultra Fast eQTL Analysis via Large Matrix Operations
Matrix eQTL is designed for fast eQTL analysis on large datasets. Matrix eQTL can test for association between genotype and gene expression using linear regression with either additive or ANOVA genotype effects. The models can include covariates to account for factors as population stratification, gender, and clinical variables. It also supports models with heteroscedastic and/or correlated errors, false discovery rate estimation and separate treatment of local (cis) and distant (trans) eQTLs. For more details see Shabalin (2012) <doi:10.1093/bioinformatics/bts163>.
Maintained by Andrey A Shabalin. Last updated 2 years ago.
74 stars 8.31 score 612 scripts 3 dependents
r-hyperspec
hyperSpec:Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)
Comfortable ways to work with hyperspectral data sets, i.e. spatially or time-resolved spectra, or spectra with any other kind of information associated with each of the spectra. The spectra can be data as obtained in XRF, UV/VIS, Fluorescence, AES, NIR, IR, Raman, NMR, MS, etc. More generally, any data that is recorded over a discretized variable, e.g. absorbance = f(wavelength), stored as a vector of absorbance values for discrete wavelengths is suitable.
Maintained by Claudia Beleites. Last updated 10 months ago.
data-wranglinghyperspectralimaginginfrarednmrramanspectroscopyuv-visxrf
16 stars 8.10 score 233 scripts 2 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.
184 stars 7.48 score 172 scripts
trevorhastie
softImpute:Matrix Completion via Iterative Soft-Thresholded SVD
Iterative methods for matrix completion that use nuclear-norm regularization. There are two main approaches.The one approach uses iterative soft-thresholded svds to impute the missing values. The second approach uses alternating least squares. Both have an 'EM' flavor, in that at each iteration the matrix is completed with the current estimate. For large matrices there is a special sparse-matrix class named "Incomplete" that efficiently handles all computations. The package includes procedures for centering and scaling rows, columns or both, and for computing low-rank SVDs on large sparse centered matrices (i.e. principal components).
Maintained by Trevor Hastie. Last updated 4 years ago.
10 stars 7.47 score 253 scripts 22 dependentsbioc
ResidualMatrix:Creating a DelayedMatrix of Regression Residuals
Provides delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. Also supports partial computation of residuals where selected factors are to be preserved in the output matrix. Implements a number of efficient methods for operating on the delayed matrix of residuals, most notably matrix multiplication and calculation of row/column sums or means.
Maintained by Aaron Lun. Last updated 3 months ago.
softwaredatarepresentationregressionbatcheffectexperimentaldesign
1 stars 6.83 score 6 scripts 10 dependents
shabbychef
madness:Automatic Differentiation of Multivariate Operations
An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via 'forward accumulation'.
Maintained by Steven E. Pav. Last updated 4 years ago.
31 stars 6.59 score 28 scripts 3 dependentskaskr
RTMBp:'R' Bindings for 'TMB'
Native 'R' interface to 'TMB' (Template Model Builder) so models can be written entirely in 'R' rather than 'C++'. Automatic differentiation, to any order, is available for a rich subset of 'R' features, including linear algebra for dense and sparse matrices, complex arithmetic, Fast Fourier Transform, probability distributions and special functions. 'RTMBp' provides easy access to model fitting and validation following the principles of Kristensen, K., Nielsen, A., Berg, C. W., Skaug, H., & Bell, B. M. (2016) <DOI:10.18637/jss.v070.i05> and Thygesen, U.H., Albertsen, C.M., Berg, C.W. et al. (2017) <DOI:10.1007/s10651-017-0372-4>.
Maintained by Kasper Kristensen. Last updated 2 months ago.
51 stars 6.44 score 1 scriptsbioc
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 6 days ago.
infrastructuredatarepresentationdataimportsinglecellrnaseqcpp
1 stars 5.32 score 9 scripts 1 dependentsr-forge
arrayhelpers:Convenience Functions for Arrays
Some convenient functions to work with arrays.
Maintained by C. Beleites. Last updated 5 years ago.
5.08 score 32 scripts 27 dependentsbioc
BufferedMatrix:A matrix data storage object held in temporary files
A tabular style data object where most data is stored outside main memory. A buffer is used to speed up access to data.
Maintained by Ben Bolstad. Last updated 4 months ago.
4.73 score 6 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
henrikbengtsson
R.huge:Methods for Accessing Huge Amounts of Data [deprecated]
DEPRECATED. Do not start building new projects based on this package. Cross-platform alternatives are the following packages: bigmemory (CRAN), ff (CRAN), BufferedMatrix (Bioconductor). The main usage of it was inside the aroma.affymetrix package. (The package currently provides a class representing a matrix where the actual data is stored in a binary format on the local file system. This way the size limit of the data is set by the file system and not the memory.)
Maintained by Henrik Bengtsson. Last updated 1 years ago.
3.88 score 2 scripts 5 dependents
cran
salad:Simple Automatic Differentiation
Handles both vector and matrices, using a flexible S4 class for automatic differentiation. The method used is forward automatic differentiation. Many functions and methods have been defined, so that in most cases, functions written without automatic differentiation in mind can be used without change.
Maintained by Hervé Perdry. Last updated 3 months ago.
2.48 score