Other packages > Find by keyword >

net4pg  

Handle Ambiguity of Protein Identifications from Shotgun Proteomics
View on CRAN: Click here


Download and install net4pg package within the R console
Install from CRAN:
install.packages("net4pg")

Install from Github:
library("remotes")
install_github("cran/net4pg")

Install by package version:
library("remotes")
install_version("net4pg", "0.1.1")



Attach the package and use:
library("net4pg")
Maintained by
Laura Fancello
[Scholar Profile | Author Map]
First Published: 2021-09-20
Latest Update: 2022-09-07
Description:
In shotgun proteomics, shared peptides (i.e., peptides that might originate from different proteins sharing homology, from different proteoforms due to alternative mRNA splicing, post-translational modifications, proteolytic cleavages, and/or allelic variants) represent a major source of ambiguity in protein identifications. The 'net4pg' package allows to assess and handle ambiguity of protein identifications. It implements methods for two main applications. First, it allows to represent and quantify ambiguity of protein identifications by means of graph connected components (CCs). In graph theory, CCs are defined as the largest subgraphs in which any two vertices are connected to each other by a path and not connected to any other of the vertices in the supergraph. Here, proteins sharing one or more peptides are thus gathered in the same CC (multi-protein CC), while unambiguous protein identifications constitute CCs with a single protein vertex (single-protein CCs). Therefore, the proportion of single-protein CCs and the size of multi-protein CCs can be used to measure the level of ambiguity of protein identifications. The package implements a strategy to efficiently calculate graph connected components on large datasets and allows to visually inspect them. Secondly, the 'net4pg' package allows to exploit the increasing availability of matched transcriptomic and proteomic datasets to reduce ambiguity of protein identifications. More precisely, it implement a transcriptome-based filtering strategy fundamentally consisting in the removal of those proteins whose corresponding transcript is not expressed in the sample-matched transcriptome. The underlying assumption is that, according to the central dogma of biology, there can be no proteins without the corresponding transcript. Most importantly, the package allows to visually inspect the effect of the filtering on protein identifications and quantify ambiguity before and after filtering by means of graph connected components. As such, it constitutes a reproducible and transparent method to exploit transcriptome information to enhance protein identifications. All methods implemented in the 'net4pg' package are fully described in Fancello and Burger (2022) .
How to cite:
Laura Fancello (2021). net4pg: Handle Ambiguity of Protein Identifications from Shotgun Proteomics. R package version 0.1.1, https://cran.r-project.org/web/packages/net4pg. Accessed 04 Apr. 2025.
Previous versions and publish date:
0.1.0 (2021-09-20 17:20)
Other packages that cited net4pg R package
View net4pg citation profile
Other R packages that net4pg depends, imports, suggests or enhances
Complete documentation for net4pg
Downloads during the last 30 days
03/0503/0603/0703/0803/0903/1003/1103/1203/1303/1403/1503/1603/1703/1803/1903/2003/2103/2203/2303/2403/2503/2603/2703/2803/2903/3003/3104/0104/02Downloads for net4pg024681012141618202224TrendBars

Today's Hot Picks in Authors and Packages

RMixpanel  
API for Mixpanel
Provides an interface to many endpoints of Mixpanel's Data Export, Engage and JQL API. The R functio ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
GeDS  
Geometrically Designed Spline Regression
Spline Regression, Generalized Additive Models, and Component-wise Gradient Boosting, utilizing Geo ...
Download / Learn more Package Citations See dependency  
perryExamples  
Examples for Integrating Prediction Error Estimation into Regression Models
Examples for integrating package 'perry' for prediction error estimation into regression models. ...
Download / Learn more Package Citations See dependency  
PakPMICS2014HH  
Multiple Indicator Cluster Survey (MICS) 2014 Household Questionnaire Data for Punjab, Pakistan
Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2014 Hous ...
Download / Learn more Package Citations See dependency  
metaprotr  
Metaproteomics Post-Processing Analysis
Set of tools for descriptive analysis of metaproteomics data generated from high-throughput mass ...
Download / Learn more Package Citations See dependency  

23,990

R Packages

207,311

Dependencies

64,809

Author Associations

23,991

Publication Badges

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