Showing 27 of total 27 results (show query)
bioc
IRanges:Foundation of integer range manipulation in Bioconductor
Provides efficient low-level and highly reusable S4 classes for storing, manipulating and aggregating over annotated ranges of integers. Implements an algebra of range operations, including efficient algorithms for finding overlaps and nearest neighbors. Defines efficient list-like classes for storing, transforming and aggregating large grouped data, i.e., collections of atomic vectors and DataFrames.
Maintained by Hervé Pagès. Last updated 2 months ago.
infrastructuredatarepresentationbioconductor-packagecore-package
22 stars 16.09 score 2.1k scripts 1.8k dependentsbioc
S4Vectors:Foundation of vector-like and list-like containers in Bioconductor
The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, Factor, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).
Maintained by Hervé Pagès. Last updated 2 months ago.
infrastructuredatarepresentationbioconductor-packagecore-package
18 stars 16.05 score 1.0k scripts 1.9k dependentsbioc
MultiAssayExperiment:Software for the integration of multi-omics experiments in Bioconductor
Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of standard data classes for individual assays, and allowing subsetting by genomic ranges or rownames. Facilities are provided for reshaping data into wide and long formats for adaptability to graphing and downstream analysis.
Maintained by Marcel Ramos. Last updated 2 months ago.
infrastructuredatarepresentationbioconductorbioconductor-packagegenomicsnci-itcrtcgau24ca289073
71 stars 14.95 score 670 scripts 127 dependentsbioc
BiocGenerics:S4 generic functions used in Bioconductor
The package defines many S4 generic functions used in Bioconductor.
Maintained by Hervé Pagès. Last updated 2 months ago.
infrastructurebioconductor-packagecore-package
12 stars 14.22 score 612 scripts 2.2k dependentsbioc
MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics
MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.
Maintained by Laurent Gatto. Last updated 16 days ago.
immunooncologyinfrastructureproteomicsmassspectrometryqualitycontroldataimportbioconductorbioinformaticsmass-spectrometryproteomics-datavisualisationcpp
131 stars 12.76 score 772 scripts 36 dependents
vincentarelbundock
tinytable:Simple and Configurable Tables in 'HTML', 'LaTeX', 'Markdown', 'Word', 'PNG', 'PDF', and 'Typst' Formats
Create highly customized tables with this simple and dependency-free package. Data frames can be converted to 'HTML', 'LaTeX', 'Markdown', 'Word', 'PNG', 'PDF', or 'Typst' tables. The user interface is minimalist and easy to learn. The syntax is concise. 'HTML' tables can be customized using the flexible 'Bootstrap' framework, and 'LaTeX' code with the 'tabularray' package.
Maintained by Vincent Arel-Bundock. Last updated 8 days ago.
264 stars 12.26 score 562 scripts 10 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 20 days ago.
float-matrixhpclinear-algebramatrixfortranopenblasopenmp
46 stars 10.53 score 228 scripts 42 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
flowCore:flowCore: Basic structures for flow cytometry data
Provides S4 data structures and basic functions to deal with flow cytometry data.
Maintained by Mike Jiang. Last updated 5 months ago.
immunooncologyinfrastructureflowcytometrycellbasedassayscpp
10.17 score 1.7k scripts 59 dependents
robinhankin
Brobdingnag:Very Large Numbers in R
Very large numbers in R. Real numbers are held using their natural logarithms, plus a logical flag indicating sign. Functionality for complex numbers is also provided. The package includes a vignette that gives a step-by-step introduction to using S4 methods.
Maintained by Robin K. S. Hankin. Last updated 7 months ago.
5 stars 9.92 score 77 scripts 70 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
tomasfryda
h2o:R Interface for the 'H2O' Scalable Machine Learning Platform
R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Generalized Additive Models (GAM), ANOVA GLM, Cox Proportional Hazards, K-Means, PCA, ModelSelection, Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).
Maintained by Tomas Fryda. Last updated 1 years ago.
3 stars 8.20 score 7.8k scripts 11 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
cran
timeSeries:Financial Time Series Objects (Rmetrics)
'S4' classes and various tools for financial time series: Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions.
Maintained by Georgi N. Boshnakov. Last updated 6 months ago.
2 stars 7.89 score 146 dependentsbioc
flowWorkspace:Infrastructure for representing and interacting with gated and ungated cytometry data sets.
This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.
Maintained by Greg Finak. Last updated 23 days ago.
immunooncologyflowcytometrydataimportpreprocessingdatarepresentationzlibopenblascpp
7.89 score 576 scripts 10 dependentsbioc
TreeSummarizedExperiment:TreeSummarizedExperiment: a S4 Class for Data with Tree Structures
TreeSummarizedExperiment has extended SingleCellExperiment to include hierarchical information on the rows or columns of the rectangular data.
Maintained by Ruizhu Huang. Last updated 5 months ago.
datarepresentationinfrastructure
7.87 score 251 scripts 15 dependentsbioc
ncdfFlow:ncdfFlow: A package that provides HDF5 based storage for flow cytometry data.
Provides HDF5 storage based methods and functions for manipulation of flow cytometry data.
Maintained by Mike Jiang. Last updated 3 months ago.
immunooncologyflowcytometryzlibcpp
7.56 score 96 scripts 11 dependentsrobinhankin
onion:Octonions and Quaternions
Quaternions and Octonions are four- and eight- dimensional extensions of the complex numbers. They are normed division algebras over the real numbers and find applications in spatial rotations (quaternions), and string theory and relativity (octonions). The quaternions are noncommutative and the octonions nonassociative. See the package vignette for more details.
Maintained by Robin K. S. Hankin. Last updated 1 months ago.
6 stars 7.27 score 43 scripts 3 dependentsbioc
DRIMSeq:Differential transcript usage and tuQTL analyses with Dirichlet-multinomial model in RNA-seq
The package provides two frameworks. One for the differential transcript usage analysis between different conditions and one for the tuQTL analysis. Both are based on modeling the counts of genomic features (i.e., transcripts) with the Dirichlet-multinomial distribution. The package also makes available functions for visualization and exploration of the data and results.
Maintained by Malgorzata Nowicka. Last updated 5 months ago.
immunooncologysnpalternativesplicingdifferentialsplicinggeneticsrnaseqsequencingworkflowstepmultiplecomparisongeneexpressiondifferentialexpression
6.91 score 136 scripts 2 dependentsandreyshabalin
filematrix:File-Backed Matrix Class with Convenient Read and Write Access
Interface for working with large matrices stored in files, not in computer memory. Supports multiple non-character data types (double, integer, logical and raw) of various sizes (e.g. 8 and 4 byte real values). Access to parts of the matrix is done by indexing, exactly as with usual R matrices. Supports very large matrices. Tested on multi-terabyte matrices. Allows for more than 2^32 rows or columns. Allows for quick addition of extra columns to a filematrix. Cross-platform as the package has R code only.
Maintained by Andrey A Shabalin. Last updated 6 years ago.
8 stars 6.51 score 45 scripts 2 dependentsbioc
Structstrings:Implementation of the dot bracket annotations with Biostrings
The Structstrings package implements the widely used dot bracket annotation for storing base pairing information in structured RNA. Structstrings uses the infrastructure provided by the Biostrings package and derives the DotBracketString and related classes from the BString class. From these, base pair tables can be produced for in depth analysis. In addition, the loop indices of the base pairs can be retrieved as well. For better efficiency, information conversion is implemented in C, inspired to a large extend by the ViennaRNA package.
Maintained by Felix G.M. Ernst. Last updated 5 months ago.
dataimportdatarepresentationinfrastructuresequencingsoftwarealignmentsequencematchingbioconductorrnarna-structural-analysisrna-structuresequencesstructures
4 stars 6.46 score 3 scripts 4 dependentsbioc
VanillaICE:A Hidden Markov Model for high throughput genotyping arrays
Hidden Markov Models for characterizing chromosomal alteration in high throughput SNP arrays.
Maintained by Robert Scharpf. Last updated 5 months ago.
5.36 score 63 scripts 1 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 scorebioc
ReducedExperiment:Containers and tools for dimensionally-reduced -omics representations
Provides SummarizedExperiment-like containers for storing and manipulating dimensionally-reduced assay data. The ReducedExperiment classes allow users to simultaneously manipulate their original dataset and their decomposed data, in addition to other method-specific outputs like feature loadings. Implements utilities and specialised classes for the application of stabilised independent component analysis (sICA) and weighted gene correlation network analysis (WGCNA).
Maintained by Jack Gisby. Last updated 2 months ago.
geneexpressioninfrastructuredatarepresentationsoftwaredimensionreductionnetworkbioconductor-packagebioinformaticsdimensionality-reduction
3 stars 4.13 score 8 scriptsbioc
MultimodalExperiment:Integrative Bulk and Single-Cell Experiment Container
MultimodalExperiment is an S4 class that integrates bulk and single-cell experiment data; it is optimally storage-efficient, and its methods are exceptionally fast. It effortlessly represents multimodal data of any nature and features normalized experiment, subject, sample, and cell annotations, which are related to underlying biological experiments through maps. Its coordination methods are opt-in and employ database-like join operations internally to deliver fast and flexible management of multimodal data.
Maintained by Lucas Schiffer. Last updated 5 months ago.
datarepresentationinfrastructuresinglecell
4.00 score 3 scripts
adamkocsis
via:Virtual Arrays
The base class 'VirtualArray' is defined, which acts as a wrapper around lists allowing users to fold arbitrary sequential data into n-dimensional, R-style virtual arrays. The derived 'XArray' class is defined to be used for homogeneous lists that contain a single class of objects. The 'RasterArray' and 'SfArray' classes enable the use of stacked spatial data instead of lists.
Maintained by Adam T. Kocsis. Last updated 2 years ago.
3 stars 3.18 score 8 scripts