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bioc
GenomicRanges:Representation and manipulation of genomic intervals
The ability to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome. More specialized containers for representing and manipulating short alignments against a reference genome, or a matrix-like summarization of an experiment, are defined in the GenomicAlignments and SummarizedExperiment packages, respectively. Both packages build on top of the GenomicRanges infrastructure.
Maintained by Hervé Pagès. Last updated 5 months ago.
geneticsinfrastructuredatarepresentationsequencingannotationgenomeannotationcoveragebioconductor-packagecore-package
44 stars 17.68 score 13k scripts 1.3k dependentsbioc
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
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 dependents
stuart-lab
Signac:Analysis of Single-Cell Chromatin Data
A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2021) <doi:10.1038/s41592-021-01282-5>.
Maintained by Tim Stuart. Last updated 8 months ago.
atacbioinformaticssingle-cellzlibcpp
355 stars 12.18 score 3.7k scripts 1 dependents