biological interpretation of metabolomics data - bigcat€¦ · biological interpretation of...

Biological Interpretation of

Metabolomics DataMartina Kutmon – Maastricht University

Biological Interpretation of Metabolomics Data – Copenhagen – Dec 7, 2011 2

Contents

• Background on pathway analysis

• WikiPathways – Building Research Communities on Biological Pathways

• Data Analysis with PathVisio

• Introduction to the hands on part


PATHWAY ANALYSIS


Biological Pathways

• a number of biochemical steps

• linked together with a start and an end

• leads to a certain product or a change in the cell


Why Pathway Analysis?

• Intuitive to biologists• puts data in biological context

• more intuitive way of looking at your data

• more efficient than looking up gene-by gene

• Computational analysis• overrepresentation analysis

• network analysis

• Experimental Design


Why Pathway Analysis?


Biological Context

• Statistical results:

– 1,300 genes are significantly regulated after treatment with X

• Biological Meaning:

– Is a certain biological process activated or deactivated?

– Which genes in a pathway are significantly changed?


Usage of Pathway Analysis

• Pathway as a working hypothesis

– Describe expected process as a pathway

– Find out if the data supports the hypothesis

• Find enriched pathways for a dataset

– Which pathways are changed in my experiment setting?


Pathway Creation

• PathVisio allows you to draw your own pathways

• Graphical description of the process how you think it works

• Use pathway analysis to see if the data supports your hypothesis


Pathway Collections

• Which pathways should I use?

– more than 325 biological pathway related resources

• WikiPathways www.wikipathways.org

• Reactome www.reactome.org

• HMDB www.hmdb.ca

• KEGG www.genome.jp/kegg/

PathGuide: a pathway resource list. Bader et al. PubMed: 16381921

http://www.wikipathways.org/

http://www.reactome.org/

http://www.hmdb.ca/

http://www.genome.jp/kegg/


Pathway Analysis Tools

• PathVisio

• BioRAG

• MetaCore (GeneGO)

• Pathway-Express

• GenMAPP / MAPPFinder


WIKIPATHWAYSwww.wikipathways.org


What is a wiki?

A wiki is a website that allows the creation and editing of any number of interlinked web pages via a web browser ...

[wikipedia.org, 2011]


What is a wiki?

• Simple formating rules

• Collection of knowledge

• Multiple contributors

• Curation of knowledge

Examples

Wikipedia, Wikiquote, Wikibooks, Wikiversity

Wikispecies, Proteopedia, Gene Wiki, WikiPathways

Fan-wikis: Jedipedia, Simpsons wiki


WikiPathways

• Wiki for biological pathways

• Free and open source resource

• Share, curate

and discuss!

WikiPathways : buiding research communities on biological pathways. Kelder et al. PubMed: 22096230


Why WikiPathways?

• Repository for biological pathway information

• Organize knowledge

• Graphical pathway editing tool

• Community contribution and curation

• Version history

• Downloadable for further analysis


Repository for biological pathway information

• 1,658 pathways

• 1,954 registered users


Organize Knowledge


Organize Knowledge

Pathway Page

• Authors

• Graphical representation

• Curation tags

• Description

• Comments

• Ontology Tags

• Bibliography

• Categories

• History

• External References


Graphical Pathway Editing Tool

• Java Script Pathway Viewer


Graphical Pathway Editing Tool


WikiPathways data model

• Pathway identifiers

– Unique & stable

– WP1, WP43, WP1373

• Curation tags provide quality annotations

• All other information is stored in GPML


GPML format

• XML format, platform independent


Working with annotations

• DataNodes are annotated with an Xref

• Which datasource to use is up to the user


Working with annotations

• WikiPathways provides functions where the identifiers have been mapped for you

• Use BridgeDB library for solving your own mapping problems

http://www.bridgedb.org

http://www.bridgedb.org/


Community Contribution and Curation

• Communication

– Watch list

– Discussion pages

– Curation tags


Version History


Diff Viewer


Further Analysis


Tutorial and Mailinglist

• If you want to create a pathways in WikiPathways, the tutorial is a good way to start

http://wikipathways.org/index.php/Help:Tutorial

• If you have questions or problems, please contact the mailinglist

[email protected]

http://wikipathways.org/index.php/Help:Tutorial

mailto:[email protected]




PATHVISIOwww.pathvisio.org

Presenting and exploring biological pathways within PathVisio. Van Iersel et al. PubMed: 18817533


PathVisio


Pathway Analysis Workflow

• Prepare your data

• Import data into PathVisio

• Find „enriched“ pathways

• Visualize data on pathways

• Export pathway images


Prepare your data

• All kind of quantitative data, like microarray, sequencing or qPCR data

• Identifier system needs to be supported• Probes:

– Affymetrix, Illumina, Agilent,...

• Genes and Proteins:

– Entrez Gene, Ensembl, UniProt, HUGO,...

• Metabolites:

– ChEBI, HMDB, PubChem,...


Prepare your data

• File format:

– PathVisio accepts delimited text files

– Prepare and export from Excel


Prepare your data

• Export from R

write.table(myTable, file=txtFile,

col.names = NA, sep = “\t“, quote =

FALSE, na = “NaN“)


Import your data


Import your data

• Gene databases for identifier mapping

• Download from www.pathvisio.org/wiki/PathVisioDownload

• 32 species supported

http://www.pathvisio.org/wiki/PathVisioDownload


Challenge – Identifier Mapping

• Microarrays typically use internal ids• Affymetrix 205749_at

• Agilent A_14_P106416

• Illumina ILMN_4380

• Pathways typically use gene/protein ids• Entrez Gene 1543

• Ensembl ENSG00000140465

• UniProt P04637



• 2 solutions

1. Software will take care of it– e.g. PathVisio uses synonym databases (BridgeDb

mapping databases)

2. Manual conversion of ids– DAVID http://david.abcc.ncifcrf.gov

– BioMART http://www.biomart.org

– NetAffx http://www.affymetrix.com

BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services. Van Iersel et al. PubMed:20047655

http://david.abcc.ncifcrf.gov/

http://www.biomart.org/

http://www.affymetrix.com/



• Gene/metabolite databases in PathVisio?

1. User specifies one identifier for the element, e.g. 5951 in PubChem for L-Serine

2. Gene/metabolite database in PathVisio knows the identifier for this object in other databases, e.g. L-Serine has id 17115 in ChEBI

3. PathVisio shows all cross references in the backpage

4. The element is represented by any of the identifiers in the backpage


Import your data

• Identifier and System Code


Import your data

• Exception file


Import your data

• Imported data is stored in a .pgex file

• Load an existing dataset


Find „enriched“ pathways

• Statistics

– Does the pathway contain a higher percentage of changed genes than the complete dataset?



• Calculate Z-Scores

– The Z-score can be used as a measure for how much a subset of genes is different from the rest

• r = changed genes in Pathway

• n = total genes in Pathway

• R = changed genes

• N = total genes

Other enrichment calculation methods:

Ackermann M et al., A general modular framework for gene set enrichment analysis,

BMC bioinformatics, 2009

)N

n)(

N

R(

N

Rn

)N

Rn(r

=zscore

1

111



• Z-Score is a method to rank pathways

– High Z-Score: Selection is very different from the rest of the dataset

– Z-Score = 0:Selection is not different at all

– Z-Score < 0:Selection is more stable than the rest



• Define a criterion and select a pathway collection

criterion

collection



• Results


Visualize your data

• Create a visualization

Activate visualization options

Add/Remove Visualizations


Visualize your data

• Expression as color


Visualize your data

Color set

based on criterion

Rule based:

- significant genes

(p-value)


Visualize your data


Visualize your data

Color set

based on gradient

Gradient based:

- fold change


Visualize your data


Export your pathways

• PathVisio supports several image formats which can be used in publications

PNG


Export your pathways


Acknowledgements

Martijn van IerselEBI, UK

Thomas KelderTNO, Zeist, NL

Bruce CollinsGladstone InstitutesSF, USA

Alex PicoGladstone InstitutesSF, USA

Kristina HanspersGladstone InstitutesSF, USA

Chris EveloMaastricht University, NL

… and many contributors around the world


Questions?


HANDS ON


Dataset Description

• Liver samples from C57BL/6J mice

– 12 weeks of low- and high-fat feeding

– Samples from two intervention studies within NUGO

• Transcriptomics, proteomics and metabolomics technologies

• Goal: characterization of molecular changes that promote hepatic steatosis


Dataset Description

• Columns:

– ID

– System code

– log2FC

– type

• met = metabolite

• prot = protein

• trans-PPS2 = transcripts from the PPS2 study

• trans-PPS3 = transcripts from the PPS3 study


Hands-on Session

• Instructions

– Printed out– www.bigcat.unimaas.nl/wiki/index.php/Metabolomics_Course_2011

http://www.bigcat.unimaas.nl/wiki/index.php/Metabolomics_Course_2011


Contact Details

• Questions?

1. Subscribe to the mailing listwww.pathvisio.org/wiki/MailingLists

2. Contact me [email protected]

http://www.pathvisio.org/wiki/MailingLists


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