Bioconductor version: Release (3.14)
Methods and tools for (pre-)processing of metabolomics datasets (i.e. peak matrices), including filtering, normalisation, missing value imputation, scaling, and signal drift and batch effect correction methods. Filtering methods are based on: the fraction of missing values (across samples or features); Relative Standard Deviation (RSD) calculated from the Quality Control (QC) samples; the blank samples. Normalisation methods include Probabilistic Quotient Normalisation (PQN) and normalisation to total signal intensity. A unified user interface for several commonly used missing value imputation algorithms is also provided. Supported methods are: k-nearest neighbours (knn), random forests (rf), Bayesian PCA missing value estimator (bpca), mean or median value of the given feature and a constant small value. The generalised logarithm (glog) transformation algorithm is available to stabilise the variance across low and high intensity mass spectral features. Finally, this package provides an implementation of the Quality Control-Robust Spline Correction (QCRSC) algorithm for signal drift and batch effect correction of mass spectrometry-based datasets.
Author: Andris Jankevics [aut], Gavin Rhys Lloyd [aut, cre], Ralf Johannes Maria Weber [aut]
Maintainer: Gavin Rhys Lloyd <g.r.lloyd at bham.ac.uk>
Citation (from within R,
enter citation("pmp")
):
To install this package, start R (version "4.1") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("pmp")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pmp")
HTML | R Script | Peak Matrix Processing for metabolomics datasets |
HTML | R Script | Signal drift and batch effect correction and mass spectral quality assessment |
HTML | R Script | Signal drift and batch effect correction for mass spectrometry |
Reference Manual | ||
Text | NEWS |
biocViews | BatchEffect, MassSpectrometry, Metabolomics, QualityControl, Software |
Version | 1.6.0 |
In Bioconductor since | BioC 3.11 (R-4.0) (2 years) |
License | GPL-3 |
Depends | R (>= 4.0) |
Imports | stats, impute, pcaMethods, missForest, ggplot2, methods, SummarizedExperiment, S4Vectors, matrixStats, grDevices, reshape2, utils |
LinkingTo | |
Suggests | testthat, covr, knitr, rmarkdown, BiocStyle, gridExtra, magick |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | metabolomicsWorkbenchR, structToolbox |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | pmp_1.6.0.tar.gz |
Windows Binary | pmp_1.6.0.zip |
macOS 10.13 (High Sierra) | pmp_1.6.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/pmp |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/pmp |
Package Short Url | https://bioconductor.org/packages/pmp/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.14 | Source Archive |
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