The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Type: Package
Title: Calculates the Percentage CV for Mass Spectrometry-Based Proteomics Data
Version: 0.4.0
Maintainer: Alejandro Brenes <abrenes@ed.ac.uk>
Description: Calculates the percentage coefficient of variation (CV) for mass spectrometry-based proteomic data. The CV can be calculated with the traditional formula for raw (non log transformed) intensity data, or log transformed data.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2024-11-21 20:50:51 UTC; ajbrenesmurillo
Author: Alejandro Brenes ORCID iD [aut, cre]
Repository: CRAN
Date/Publication: 2024-11-21 21:10:02 UTC

protLogCV protCV

Description

Calculates the percentage CV for intensity based proteomic data.

Usage

protLogCV(logData, base)
protCV(data)

Arguments

data

input dataframe of the intensity values.

logData

input dataframe of the log transformed intensity values.

base

numerical base of the logarithm that was used to transform the data. Values that are accepted are 2 (for log2) and 10 (for log10)

Value

returns a list containing the percentage CVs

Author(s)

Alejandro J. Brenes

References

https://www.biorxiv.org/content/10.1101/2024.09.11.612398v1

Examples


library(proteomicsCV)
log_intensity_df<-data.frame(intensity1=c(16.93157,26.57542,19.90749,18.86056),
                         intensity2=c(17.16546,27.77706,19.45854,19.60721),
                         intensity3=c(17.04260,27.21697,19.70314,16.19530),
                         intensity4=c(17.08473,26.99766,17.93342,17.97693))

# log formula with the data already transformed to log2
cvs<-protLogCV(log_intensity_df, 2)
# log formula with the data not log transformed
not_log_intensity_df<-data.frame(intensity1=c(125000,100000000,983450,475987),
                         intensity2=c(147000,230000000,720450,798656),
                         intensity3=c(135000,156000000,853566,75036),
                         intensity4=c(139000,134000000,250321,257986))
# base formula with raw intensity (no log transformation)
raw_cvs<-protCV(not_log_intensity_df)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.