Welcome to Proteomics Data Analysis with CloudBioLinux’s documentation!¶
Contents:
Starting a CloudBioLinux/CloudMan Instance¶
This screencast demonstrates how to use BioCloudCentral to launch CloudBioLinux/CloudMan. These instructions mostly apply except for proteomic data analysis, we recommend using our BioCloudCentral instance that is configured to point at images for proteomic data analysis.
GUI Tools¶
Linux may be known for opaque command-line tools, but there are actually many powerful easy-to-use graphical Desktop tools for proteomic data analysis. The following section outlines some of those available in the CloudBioLinux environment for proteomics.
MZmine¶
PeptideShaker¶
Pride Converter¶
Pride Inspector¶
TOPPAS¶
Programming Environments¶
The image is an ideal environment for mass spec data analysis and tool development. It comes preconfigured with libraries for R, Python, and Ruby.
R Libraries¶
The proteomics image provides immediate access to dozens of potentially useful R libraries. For high-level information about R and proteomics checkout the blog post Why R for Mass Spectrometrist and Computational Proteomics.
To start R, simply open a terminal and type R followed by enter.
ubuntu@hostname:~$ R
>
You will then be staring at the R prompt. The interesting libraries to explore include:
XCMS:
> library(xcms)
mzR:
> library(mzR)
> library(FactoMineR)
`caret <http://caret.r-forge.r-project.org/>_:
> library(caret)
ggplot2 and VennDiagram:
> library(ggplot2)
> library(VennDiagram)
Ruby¶
mspire comes pre-installed. mspire is a ruby library for working with mass spectrometry data.
$ irb # Launch interactive ruby interpreter. irb(main):001:0> require ‘mspire/mzml’ => true irb(main):002:0>
Visit the mspire homepage <https://github.com/princelab/mspire> for more information on using mspire.
Python¶
pyteomics
ubuntu@hostname:~$ python Python 2.7.3 (default, Aug 1 2012, 05:14:39) [GCC 4.6.3] on linux2 Type “help”, “copyright”, “credits” or “license” for more information. >>> from pyteomics.mass import Composition
Visit the Pyteomics Documentation for more information on using pyteomics.