Other packages > Find by keyword >

MetProc  

Separate Metabolites into Likely Measurement Artifacts and True Metabolites
View on CRAN: Click here


Download and install MetProc package within the R console
Install from CRAN:
install.packages("MetProc")

Install from Github:
library("remotes")
install_github("cran/MetProc")

Install by package version:
library("remotes")
install_version("MetProc", "1.0.1")



Attach the package and use:
library("MetProc")
Maintained by
Mark Chaffin
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-05-19
Latest Update: 2016-05-19
Description:
Split an untargeted metabolomics data set into a set of likely true metabolites and a set of likely measurement artifacts. This process involves comparing missing rates of pooled plasma samples and biological samples. The functions assume a fixed injection order of samples where biological samples are randomized and processed between intermittent pooled plasma samples. By comparing patterns of missing data across injection order, metabolites that appear in blocks and are likely artifacts can be separated from metabolites that seem to have random dispersion of missing data. The two main metrics used are: 1. the number of consecutive blocks of samples with present data and 2. the correlation of missing rates between biological samples and flanking pooled plasma samples.
How to cite:
Mark Chaffin (2016). MetProc: Separate Metabolites into Likely Measurement Artifacts and True Metabolites. R package version 1.0.1, https://cran.r-project.org/web/packages/MetProc. Accessed 12 Oct. 2026.
Previous versions and publish date:
1.0.1 (2016-05-19 05:46), (2026-07-09 08:10)
Other packages that cited MetProc R package
View MetProc citation profile
Other R packages that MetProc depends, imports, suggests or enhances
Complete documentation for MetProc
Functions, R codes and Examples using the MetProc R package
Some associated functions: MetProc-package . corr_metric . get_group . get_missing . heatmap_res . met_proc . plot_metric . plot_pp_sample_missing . read.met . run_metric . sampledata . subset_met . write.met . 
Some associated R codes: functions_cleane.R .  Full MetProc package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

gwavr  
Get Water Attributes Visually in R
Provides methods to Get Water Attributes Visually in R ('gwavr'). This allows the user to point and ...
Download / Learn more Package Citations See dependency  
cglasso  
Conditional Graphical LASSO for Gaussian Graphical Models with Censored and Missing Values
Conditional graphical lasso estimator is an extension of the graphical lasso proposed to estimate th ...
Download / Learn more Package Citations See dependency  
ggparliament  
Parliament Plots
Simple parliament plots using 'ggplot2'. Visualize election results as points in the architectural l ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
SLEMI  
Statistical Learning Based Estimation of Mutual Information
The implementation of the algorithm for estimation of mutual information and channel capacity from e ...
Download / Learn more Package Citations See dependency  

29,000

R Packages

247,686

Dependencies

76,729

Author Associations

29,001

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA