Analyzing Shotgun Proteomic Data with PatternLab for Proteomics

Paulo C. Carvalho1, John R. Yates III1, Valmir C. Barbosa2

1 The Scripps Research Institute, La Jolla, California, 2 Systems Engineering and Computer Science Program, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Publication Name:  Current Protocols in Bioinformatics
Unit Number:  Unit 13.13
DOI:  10.1002/0471250953.bi1313s30
Online Posting Date:  June, 2010
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Abstract

PatternLab for proteomics is a one‐stop shop computational environment for analyzing shotgun proteomic data. Its modules provide means to pinpoint proteins/peptides that are differentially expressed and those that are unique to a state. It can also cluster the ones that share similar expression profiles in time‐course experiments, as well as help in interpreting results according to Gene Ontology. PatternLab is user‐friendly, simple, and provides a graphical user interface. Curr. Protoc. Bioinform. 30:13.13.1‐13.13.15. © 2010 by John Wiley & Sons, Inc.

Keywords: shotgun proteomics; label‐free proteomic analysis; label‐based proteomic analysis

     
 
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Table of Contents

  • Introduction
  • Basic Protocol 1: Parsing Experimental Data into PatternLab's Data Format
  • Basic Protocol 2: TFold and ACFold—Pinpointing Differentially Expressed Proteins
  • Alternate Protocol 1: Performing a Multi‐Class Comparison (a sparseMatrix.txt File with Three or More Classes)
  • Basic Protocol 3: Pinpointing Proteins Unique to a State with the Approximately Area‐Proportional Venn Diagram Module
  • Basic Protocol 4: TrendQuest: Clustering Proteins with Similar Expression Profiles
  • Basic Protocol 5: Compiling the Latest Gene Ontology and Gene Ontology Annotation (GOA) into GOEx's Precomputed Format
  • Guidelines for Understanding Results
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
 
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Materials

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Figures

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Literature Cited

Literature Cited
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