BamScale
Bioconductor-Friendly Multithreaded BAM Processing
Bioconductor version: 3.24 · Package version: 0.99.14
Multithreaded sequential BAM processing built on top of the ompBAM C++ engine. BamScale provides user-friendly BAM read and scan interfaces designed for compatibility with existing Bioconductor workflows.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("BamScale")Details
| Maintainer | Chirag Parsania <chirag.parsania@gmail.com> |
| Author | Chirag Parsania [aut, cre] |
| License | MIT + file LICENSE |
| URL | https://cparsania.github.io/BamScale/ |
| Bug Reports | https://github.com/cparsania/BamScale/issues |
| System Requirements | C++17, OpenMP |
| Downloads rank | 60 |
| Source branch | devel |
| biocViews | Alignment, Coverage, DataImport, QualityControl, Sequencing, Software |
Documentation
- Benchmarking BamScale: reader throughput and end-to-end workflow impact
- Getting started with BamScale
Download
Follow the installation instructions to use this package in your R session.
| Source package | BamScale_0.99.14.tar.gz |
| Windows binary (x86_64) | BamScale_0.99.14.zip |
| macOS binary (arm64) | BamScale_0.99.14.tgz |
| macOS binary (x86_64) | BamScale_0.99.14.tgz |
Dependencies
Imports: BiocGenerics, BiocParallel, Biostrings, GenomeInfoDb, GenomicAlignments, GenomicRanges, IRanges, methods, ompBAM, Rcpp, Rsamtools, S4Vectors
LinkingTo: Rcpp, ompBAM, S4Vectors, IRanges, XVector
Suggests: BiocStyle, chipseqDBData, dplyr, ExperimentHub, ggplot2, knitr, readr, rmarkdown, rtracklayer, scales, tibble, testthat (>= 3.0.0), tidyr