ProbMetab - Silva et al.

ProbMetab

The ProbMetab provides probability ranking to candidate compounds assigned to masses

with the prior assumption of connected sample and additional previous and spectral information modeled by the user.
Take a look at our study case to get a better understanding of our approach.

Download

ProbMetab

Find attached to this section all necessary files to install ProbMetab on your R environment. Please, remember to read carefully the Instalation instructions for a better understanding of all necessary steps.

Linux (Unix)

ProbMetab_1.0.tar.gz (Linux)

Windows

ProbMetab_1.0.zip (Windows)

MAC OS

ProbMetab_1.0.tgz (MAC OS - Mountain Lion).
Aditional Libraries (MAC OS only)

Manual

Download ProbMetab Manual as a PDF file.

API

View ProbMetab's API

How-to Install

Steps for installing ProbMetab on your computer.

There are some necessary steps one needs to follow to properly install ProbMetab into the R environment.

If you experience recurrent problems trying to install our package, please email: rsilvabioinfo@gmail.

Dependencies (All OS)

source("http://bioconductor.org/biocLite.R")
biocLite(c("CAMERA", "graph", "RCytoscape", "multtest"))
install.packages(c("RcppArmadillo", "hwriter", "GeneNet", "RCurl","XML", "rjson"))

External Libraries (Linux)

If you have problems installing the packages above, these are
external libraries usually required on linux (specifically Ubuntu 13.04)

sudo apt-get install libxml2-dev
sudo apt-get install libnetcdf-dev
sudo apt-get install libcurl4-openssl-dev

Recomended external libraries

Necessary packages to run the study case example

install.packages(c( "bootstrap", "leaps", "mgcv"))

External Sources

Recommended packages sources outside cran and Bioconductor

http://mzmatch.sourceforge.net/tutorial.mzmatch.r.advanced.php
http://diffcorr.sourceforge.net/

Aditional Steps - MAC OS (only)

Download additional libraries and copy it to two distinct and specific folders on Mac OS:
File libstdc++.6.dylib:
cp libstdc++.6.dylib /Library/Frameworks/R.framework/Versions/3.0/Resources/lib/
File libgcc_s.1.dylib:
cp libgcc_s.1.dylib /Library/Frameworks/R.framework/Resources/lib/

Journal

Our latest posts and releases/updates briefly described. Click on comment icon on google plus box below to see the last news.

ProbMetab v1.0

Nov 6, 2013 By Ricardo R. Silva

ProbMetab v1.0 publication is online. Here is the Advance online version.

We also refer to ProbMetab paper's supplemental material.

Study Cases

Find out the study cases to get a better understanding of ProbMetab approach.

In this section you will find study cases that illustrates the usage of R package ProbMetab in two real metabolomics datasets. The aim is to perform a complete analysis work-flow, from spectra preprocessing to network visualization, to show the package integration capabilities with upstream tools (CAMERA and mzmatch.R in this example) and with downstream tools (Cytoscape and DiffCor).

Study Case

Study Case Manual

Find here a document that explains, step-by-step, the study cases that uses ProbMetab.
Download 1

External Files

External files of analysis intermediary steps refereed in the text.
Download 2

Dataset

mzXML spectras from sugar cane plants cultivated under drought stress and standard irrigation.
Download 3

Example code and Linux image

Text file with commented example code and a Linux image with all ProbMetab dependencies installed.
Download 4

Output Examples

This section provides output examples for a better understanding of our approach.

Screencast

Web-Representation

Graph representation where: nodes are mass peaks and edges are drawn only if there is at least one biochemical reaction transforming an annotated compound into some annotated compound, and the mass peaks present a correlation above user's threshold. Clicking the nodes the user can see the probability ranking and additional information associated to a mass peak, helping the interpretation of network context.

Web-Representation example.

Tabular-Representation

ProbMetab’s tabular output showing how the probability ranking is associated to spectra and database weblinks. Aditionally to prababilities and web links the table presents the fields entropy of probability distribution among the candidates (entropy – from information theory) and ion annotation in the format: original mass# original retention time# isotopic pattern, if present# adduct pattern, if present.

Tabular-Representation example.

The ProbMetab provides probability ranking to candidate compounds assigned to masses

Take a look at our study case to get a better understanding of our approach.