daehee hwang leroy hood institute for systems biology

Daehee HwangLeroy Hood

Institute for Systems Biology

2Why Prequips for Systems Biology with proteomic data?

• Need for visualization, analysis, and integration of multiple proteomic datasets: raw data level, peptide level, protein level, multi sample

analysis

• Need for an interface between proteomic data and systems biology analytical tools such as network/pathway analyses

3Integration of proteomic data at various levels

Raw Data(MS, MS/MS)

PeptideId + Quantiation

ProteinId + Quantitation

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Raw Data(MS, MS/MS)



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(MS, MS/MS)



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4Pep3d: Quality Assessment

Prequips

Multi Sample

Raw Data(MS, MS/MS)



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Pep3D

Properties

- quality assessment

- 2D gel-like visualizationGaggle

NetworkAnalysisCytoscape

InteractionDatabase

STRING

PathwayDatabase

KEGG

MicroarrayData Analysis

Mayday, TIGR

5Pep3d: Quality Assessment

Pep3D

Instance 1

Pep3D

Instance 2Communication

not possible!

6Interface to Systems Biology

Gaggle


InteractionDatabase

STRING

PathwayDatabase

KEGG


Mayday, TIGR

Raw Data(MS, MS/MS)



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7Prequips Overview

Prequips

Multi Sample

Gaggle


InteractionDatabase

STRING

PathwayDatabase

KEGG


Mayday, TIGR

- handles multiplesamples at all levels

Key Properties

- integrates high-levelanalysis tools

- is extensible

Raw Data(MS, MS/MS)



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8Integration of proteomic datasets at various levels

Database Search

raw data

Mass Spectrometer

peptide-level data

e.g. mzXML, mzData, ...

Validation

Peptide Quantification

Protein Inference

protein-level data

Protein Quantitation

e.g. pepXML,AnalysisXML,...

e.g. protXML, ...

Trans-Proteomic Pipeline

annotation

further analysis results

9

Raw Data

Data model

Peptide LevelProtein Level

Core Core CoreMeta Meta Meta

Single-Sample Analysis

Multi-Sample Analysis

Project

Data Providers

Data Structures

protein-level data source,e.g. protXML files

peptide-level datasource, e.g. pepXML,dta or AnalysisXML files

raw data level,e.g. mzXML or mzDatafiles

View

ers

Perspectives

10Case Study: Toponomic change in drug treated Mø

Calreticulin

BiP

Bcl2

ATPase

Lamp1

2 4 6 8 10 12 14 16 18 20

8% 28%

114 115 116 117

Fraction #:

Mock1 Mock2 Thapsigargin

11Visualization: Single exp.

CID spectrathat have been selected

detailed information about one of the level 2 spectra

projectmanager peak map for run 29

level 1 spectrum & corresponding CID spectra

level 1

level 2

level 2all scans of Mock 1 experiment

12Visualization: Multiple exps.

(polymer?) contamination in all 4 runs(this would be hard to see with Pep3D)

green = 0red = 1

13Visualization: assess, quntify, etc.Mock Up (software is under development):

m/z

min maxretention time

min max

map 1map 2map 3map 4map 5map 6

map 1 map 2

map 3 map 4X

XX

Doesn’t really match the remaining 3 maps!

14Prequips & the Gaggle

Gaggle Boss

Prequips

Mayday

R statistical environment

Cytoscape

Exchange of data structures such as name lists, lists of name-value pairs, matrices and networks.

KEGGDAVID

Browser

15Mayday

16Cytoscape

overall mouse protein/protein interaction map in Cytoscape

17Analysis: Feature extraction

Proteintable

Gaggle pluginfor interactionwith other tools

Filters

18Analysis: Feature extraction

Gaggle plugin: selection for broadcast

calreticulin

19Analysis: Feature selection

Mock1 Mock2 Thapsigargin

20Broadcast to Gaggle

21Prequips to Gaggle

Gaggle Boss

Prequips

Mayday


Cytoscape


KEGGDAVID

Browser

22Gaggle Boss

23Gaggle to Cytoscape

Gaggle Boss

Prequips

Mayday


Cytoscape


KEGGDAVID

Browser

24Integration: Network Analysis

proteasome complex

ribosome large subunit

chaperones

actin filamentregulation

Thapsigargin 114 iTRAQ ratio

25Cytoscape to Prequips

Gaggle Boss

Prequips

Mayday


Cytoscape


KEGGDAVID

Browser

26Analysis: Feature extraction- Module selection

the ids sentfrom Cytoscapethrough the Gaggle

proteasome proteins

27Prequips & the Gaggle

Gaggle Boss

Prequips

Mayday


Cytoscape


KEGGDAVID

Browser

28Analysis: Functional enrichmentthe proteasome complex enriched compared to a mouse genome background

29Prequips Summary

Prequips

Multi Sample

Gaggle


InteractionDatabase

STRING

PathwayDatabase

KEGG


Mayday, TIGR

- handles multiplesamples at all levels

Key Properties

- integrates high-levelanalysis tools

- is extensible

Raw Data(MS, MS/MS)



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30Conclusion

• general and extensible software for systems biology research with proteomics mass spectrometry data.

• Integration capability of data from various sources for visualization and analysis.

• An interactive environment that supports (visual) data exploration.

31Software details

• implemented in Java

• based on Eclipse Rich Client Platform

• extremely modular architecture

• multiple plugin interfaces– e.g. viewers, data providers, algorithms

• meta information framework– analysis results, sequence information, annotation, ...– data structures as plugins– requirement to support future analytical tools and data

sources

32Acknowledgements

• Special thanks to Nils Gehlenborg

• Hood Lab: Inyoul Lee

• Kay Nieselt

• Aebersold Lab: Nichole King, James Eddes,

Eric Deutsch, Ning Zhang, David

Shteynberg, Wei Yan, and Andrew Garbutt

• Paul Shannon for help with the Gaggle

33

Core

Mayday

Database Gaggle

R

Visualization

Excel

PostgreSQLdatabase

MySQLdatabase

R environmentBioconductor

SBEAMSSBEAMSinstallation

Machine

Learning

WEKA Library

anything else

Prequips

34Cytoscape

daehee hwang leroy hood institute for systems biology

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