Registration Open for Bioc2024
Early registration discount pricing ends May 31!

pmp

This is the development version of pmp; for the stable release version, see pmp.

Peak Matrix Processing and signal batch correction for metabolomics datasets


Bioconductor version: Development (3.20)

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")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("pmp")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("pmp")
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 HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews BatchEffect, MassSpectrometry, Metabolomics, QualityControl, Software
Version 1.17.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License GPL-3
Depends R (>= 4.0)
Imports stats, impute, pcaMethods, missForest, ggplot2, methods, SummarizedExperiment, S4Vectors, matrixStats, grDevices, reshape2, utils
System Requirements
URL
See More
Suggests testthat, covr, knitr, rmarkdown, BiocStyle, gridExtra, magick
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me metabolomicsWorkbenchR, structToolbox
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package pmp_1.17.0.tar.gz
Windows Binary pmp_1.17.0.zip (64-bit only)
macOS Binary (x86_64) pmp_1.17.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/pmp
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/pmp
Bioc Package Browser https://code.bioconductor.org/browse/pmp/
Package Short Url https://bioconductor.org/packages/pmp/
Package Downloads Report Download Stats