yamss
Tools for high-throughput metabolomics
Bioconductor version: 3.23 · Package version: 1.38.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Tools to analyze and visualize high-throughput metabolomics data aquired using chromatography-mass spectrometry. These tools preprocess data in a way that enables reliable and powerful differential analysis. At the core of these methods is a peak detection phase that pools information across all samples simultaneously. This is in contrast to other methods that detect peaks in a sample-by-sample basis.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("yamss")Details
| Maintainer | Leslie Myint <leslie.myint@gmail.com> |
| Author | Leslie Myint [cre, aut] (ORCID: <https://orcid.org/0000-0003-2478-0331>), Kasper Daniel Hansen [aut] |
| License | Artistic-2.0 |
| URL | https://github.com/hansenlab/yamss |
| Bug Reports | https://github.com/hansenlab/yamss/issues |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | MassSpectrometry, Metabolomics, PeakDetection, Software |
| Package Short Url | https://bioconductor.org/packages/yamss/ |
Citation
From within R, enter citation("yamss"):
Leslie Myint, Kasper Daniel Hansen. yamss: Tools for high-throughput metabolomics. doi:10.18129/B9.bioc.yamss, R package version 1.38.0, https://bioconductor.org/packages/yamss.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | yamss_1.38.0.tar.gz |
| Windows binary (x86_64) | yamss_1.38.0.zip |
| macOS binary (arm64) | yamss_1.38.0.tgz |
| macOS binary (x86_64) | yamss_1.38.0.tgz |
Dependencies
Depends: R (>= 4.3.0), methods, BiocGenerics (>= 0.15.3), SummarizedExperiment
Imports: IRanges, stats, S4Vectors, EBImage, Matrix, mzR, data.table, grDevices, limma
Suggests: BiocStyle, knitr, rmarkdown, digest, mtbls2, testthat