Showing 25 of total 25 results (show query)
rspatial
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 This package has been superseded by the "terra" package 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
bioc
SummarizedExperiment:A container (S4 class) for matrix-like assays
The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.
Maintained by Hervé Pagès. Last updated 5 months ago.
geneticsinfrastructuresequencingannotationcoveragegenomeannotationbioconductor-packagecore-package
34 stars 16.84 score 8.6k scripts 1.2k 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 dependents
ncss-tech
aqp:Algorithms for Quantitative Pedology
The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Maintained by Dylan Beaudette. Last updated 1 months ago.
digital-soil-mappingncss-technrcspedologypedometricssoilsoil-surveyusda
55 stars 11.90 score 1.2k scripts 2 dependents
cmmr
rbiom:Read/Write, Analyze, and Visualize 'BIOM' Data
A toolkit for working with Biological Observation Matrix ('BIOM') files. Read/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and beta diversity (including 'UniFrac'). Summarize counts by taxonomic level. Subset based on metadata. Generate visualizations and statistical analyses. CPU intensive operations are coded in C for speed.
Maintained by Daniel P. Smith. Last updated 11 days ago.
15 stars 9.07 score 117 scripts 6 dependents
rubenarslan
codebook:Automatic Codebooks from Metadata Encoded in Dataset Attributes
Easily automate the following tasks to describe data frames: Summarise the distributions, and labelled missings of variables graphically and using descriptive statistics. For surveys, compute and summarise reliabilities (internal consistencies, retest, multilevel) for psychological scales. Combine this information with metadata (such as item labels and labelled values) that is derived from R attributes. To do so, the package relies on 'rmarkdown' partials, so you can generate HTML, PDF, and Word documents. Codebooks are also available as tables (CSV, Excel, etc.) and in JSON-LD, so that search engines can find your data and index the metadata. The metadata are also available at your fingertips via RStudio Addins.
Maintained by Ruben Arslan. Last updated 3 months ago.
codebookdocumentationformrjson-ldmetadataspsswebapp
143 stars 8.29 score 229 scriptsbioc
hermes:Preprocessing, analyzing, and reporting of RNA-seq data
Provides classes and functions for quality control, filtering, normalization and differential expression analysis of pre-processed `RNA-seq` data. Data can be imported from `SummarizedExperiment` as well as `matrix` objects and can be annotated from `BioMart`. Filtering for genes without too low expression or containing required annotations, as well as filtering for samples with sufficient correlation to other samples or total number of reads is supported. The standard normalization methods including cpm, rpkm and tpm can be used, and 'DESeq2` as well as voom differential expression analyses are available.
Maintained by Daniel Sabanés Bové. Last updated 5 months ago.
rnaseqdifferentialexpressionnormalizationpreprocessingqualitycontrolrna-seqstatistical-engineering
11 stars 7.77 score 48 scripts 1 dependentsbioc
RBioFormats:R interface to Bio-Formats
An R package which interfaces the OME Bio-Formats Java library to allow reading of proprietary microscopy image data and metadata.
Maintained by Andrzej Oleś. Last updated 5 months ago.
dataimportbio-formatsbioconductorimage-processingopenjdk
25 stars 7.57 score 82 scripts 1 dependentsbioc
crisprBase:Base functions and classes for CRISPR gRNA design
Provides S4 classes for general nucleases, CRISPR nucleases, CRISPR nickases, and base editors.Several CRISPR-specific genome arithmetic functions are implemented to help extract genomic coordinates of spacer and protospacer sequences. Commonly-used CRISPR nuclease objects are provided that can be readily used in other packages. Both DNA- and RNA-targeting nucleases are supported.
Maintained by Jean-Philippe Fortin. Last updated 5 months ago.
crisprfunctionalgenomicsbioconductorbioconductor-packagecrispr-cas9crispr-designcrispr-targetgrnagrna-sequencegrna-sequences
5 stars 7.15 score 52 scripts 6 dependentsbioc
HiCExperiment:Bioconductor class for interacting with Hi-C files in R
R generic interface to Hi-C contact matrices in `.(m)cool`, `.hic` or HiC-Pro derived formats, as well as other Hi-C processed file formats. Contact matrices can be partially parsed using a random access method, allowing a memory-efficient representation of Hi-C data in R. The `HiCExperiment` class stores the Hi-C contacts parsed from local contact matrix files. `HiCExperiment` instances can be further investigated in R using the `HiContacts` analysis package.
Maintained by Jacques Serizay. Last updated 11 days ago.
9 stars 7.02 score 48 scripts 2 dependents
bioc
COMPASS:Combinatorial Polyfunctionality Analysis of Single Cells
COMPASS is a statistical framework that enables unbiased analysis of antigen-specific T-cell subsets. COMPASS uses a Bayesian hierarchical framework to model all observed cell-subsets and select the most likely to be antigen-specific while regularizing the small cell counts that often arise in multi-parameter space. The model provides a posterior probability of specificity for each cell subset and each sample, which can be used to profile a subject's immune response to external stimuli such as infection or vaccination.
Maintained by Greg Finak. Last updated 5 months ago.
immunooncologyflowcytometrycpp
7 stars 6.51 score 42 scriptsbioc
CoreGx:Classes and Functions to Serve as the Basis for Other 'Gx' Packages
A collection of functions and classes which serve as the foundation for our lab's suite of R packages, such as 'PharmacoGx' and 'RadioGx'. This package was created to abstract shared functionality from other lab package releases to increase ease of maintainability and reduce code repetition in current and future 'Gx' suite programs. Major features include a 'CoreSet' class, from which 'RadioSet' and 'PharmacoSet' are derived, along with get and set methods for each respective slot. Additional functions related to fitting and plotting dose response curves, quantifying statistical correlation and calculating area under the curve (AUC) or survival fraction (SF) are included. For more details please see the included documentation, as well as: Smirnov, P., Safikhani, Z., El-Hachem, N., Wang, D., She, A., Olsen, C., Freeman, M., Selby, H., Gendoo, D., Grossman, P., Beck, A., Aerts, H., Lupien, M., Goldenberg, A. (2015) <doi:10.1093/bioinformatics/btv723>. Manem, V., Labie, M., Smirnov, P., Kofia, V., Freeman, M., Koritzinksy, M., Abazeed, M., Haibe-Kains, B., Bratman, S. (2018) <doi:10.1101/449793>.
Maintained by Benjamin Haibe-Kains. Last updated 5 months ago.
softwarepharmacogenomicsclassificationsurvival
6.36 score 63 scripts 6 dependents
glenndavis52
colorSpec:Color Calculations with Emphasis on Spectral Data
Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners. Build complex systems from simpler parts using a spectral product algebra. For light sources, compute CCT, CRI, SSI, and IES TM-30 reports. For object colors, compute optimal colors and Logvinenko coordinates. Work with the standard CIE illuminants and color matching functions, and read spectra from text files, including CGATS files. Estimate a spectrum from its response. A user guide and 9 vignettes are included.
Maintained by Glenn Davis. Last updated 2 months ago.
2 stars 6.34 score 73 scripts 5 dependentsbioc
qcmetrics:A Framework for Quality Control
The package provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.
Maintained by Laurent Gatto. Last updated 5 months ago.
immunooncologysoftwarequalitycontrolproteomicsmicroarraymassspectrometryvisualizationreportwriting
2 stars 6.03 score 2 dependentsbioc
plyxp:Data masks for SummarizedExperiment enabling dplyr-like manipulation
The package provides `rlang` data masks for the SummarizedExperiment class. The enables the evaluation of unquoted expression in different contexts of the SummarizedExperiment object with optional access to other contexts. The goal for `plyxp` is for evaluation to feel like a data.frame object without ever needing to unwind to a rectangular data.frame.
Maintained by Justin Landis. Last updated 12 days ago.
annotationgenomeannotationtranscriptomics
4 stars 5.88 score 6 scriptsbioc
TVTB:TVTB: The VCF Tool Box
The package provides S4 classes and methods to filter, summarise and visualise genetic variation data stored in VCF files. In particular, the package extends the FilterRules class (S4Vectors package) to define news classes of filter rules applicable to the various slots of VCF objects. Functionalities are integrated and demonstrated in a Shiny web-application, the Shiny Variant Explorer (tSVE).
Maintained by Kevin Rue-Albrecht. Last updated 5 months ago.
softwaregeneticsgeneticvariabilitygenomicvariationdatarepresentationguidnaseqwholegenomevisualizationmultiplecomparisondataimportvariantannotationsequencingcoveragealignmentsequencematching
2 stars 5.76 score 16 scriptsbioc
heatmaps:Flexible Heatmaps for Functional Genomics and Sequence Features
This package provides functions for plotting heatmaps of genome-wide data across genomic intervals, such as ChIP-seq signals at peaks or across promoters. Many functions are also provided for investigating sequence features.
Maintained by Malcolm Perry. Last updated 5 months ago.
visualizationsequencematchingfunctionalgenomics
5.23 score 19 scripts 1 dependentsbioc
AnnotationHubData:Transform public data resources into Bioconductor Data Structures
These recipes convert a wide variety and a growing number of public bioinformatic data sets into easily-used standard Bioconductor data structures.
Maintained by Bioconductor Package Maintainer. Last updated 9 days ago.
5.12 score 22 scripts 4 dependentsbioc
BiocSet:Representing Different Biological Sets
BiocSet displays different biological sets in a triple tibble format. These three tibbles are `element`, `set`, and `elementset`. The user has the abilty to activate one of these three tibbles to perform common functions from the dplyr package. Mapping functionality and accessing web references for elements/sets are also available in BiocSet.
Maintained by Kayla Morrell. Last updated 5 months ago.
4.58 score 32 scripts 2 dependentsbioc
OSAT:OSAT: Optimal Sample Assignment Tool
A sizable genomics study such as microarray often involves the use of multiple batches (groups) of experiment due to practical complication. To minimize batch effects, a careful experiment design should ensure the even distribution of biological groups and confounding factors across batches. OSAT (Optimal Sample Assignment Tool) is developed to facilitate the allocation of collected samples to different batches. With minimum steps, it produces setup that optimizes the even distribution of samples in groups of biological interest into different batches, reducing the confounding or correlation between batches and the biological variables of interest. It can also optimize the even distribution of confounding factors across batches. Our tool can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideal balanced RCBD. OSAT provides a number of predefined layout for some of the most commonly used genomics platform. Related paper can be find at http://www.biomedcentral.com/1471-2164/13/689 .
Maintained by Li Yan. Last updated 5 months ago.
datarepresentationvisualizationexperimentaldesignqualitycontrol
4.30 score 3 scripts
mikemahoney218
mvdf:A Minimum Viable Data Format for 3D Rendering via Blender
A small, self-contained, minimum viable data format providing a standard interface for using R as a front-end for the Blender 3D rendering program. The core approach centers around an S4 class, 'mvdf', with getter, setter, and validation methods designed to be extended for more specific rendering approaches.
Maintained by Michael Mahoney. Last updated 4 years ago.
16 stars 4.20 score 5 scriptsglenndavis52
spacesRGB:Standard and User-Defined RGB Color Spaces, with Conversion Between RGB and CIE XYZ and Lab
Standard RGB spaces included are sRGB, 'Adobe' RGB, 'ProPhoto' RGB, BT.709, and others. User-defined RGB spaces are also possible. There is partial support for ACES Color workflows.
Maintained by Glenn Davis. Last updated 2 months ago.
3.30 score 11 scripts 3 dependents
rogiersbart
ra:A minimal TileDB-backed lazy multi-dimensional array implementation with metadata
The {ra} package provides a wrapper around the low-level {tiledb} API and {jsonlite}, to implement a minimal lazy multi-dimensional array with arbitrary metadata support.
Maintained by Bart Rogiers. Last updated 9 months ago.
1.70 score