Tutorial 2: Pathway Analysis -...

Tutorial 2: Pathway Analysis CSIRO Tutorial Series: Pathway and Network Analysis

CSIRO NUTRITION & FOOD

Martina Summer-Kutmon, PhD | Department of Bioinformatics, Maastricht University, The Netherlands 01 December 2015

Tutorial series

• Tutorial 1: Pathway creation • 24 November 2015, 2-4 PM

• Tutorial 2: Pathway analysis • 1 December 2015 , 2-4 PM

• Tutorial 3: Network analysis • 8 December 2015 , 2-4 PM

• Material (presentations and hands-on instructions) will be available on the website • http://projects.bigcat.unimaas.nl/adelaide-tutorials-2015/

CSIRO Tutorial Series: Pathway Creation | Martina Summer-Kutmon 2 |

http://projects.bigcat.unimaas.nl/adelaide-tutorials-2015/





Introduction

Data analysis


Quantitative measurements

Isolated data points

Slide adapted from Thomas Kelder

Data analysis


Comparative statistics

Isolated lists

Clustering

Isolated groups

Gene sets

Functional groups


Data analysis


Functional organisation

Pathways


FOCUS OF TODAY’S TUTORIAL

Data analysis


Systems organisation

Networks


Pathway analysis

Why pathway analysis?


Scanned microarrays

Raw intensities

Normalized intensities

Gene level statistics

Set of affected pathways

Set of overrepresentated

GO terms

Set of co-regulated genes

Biological Interpretation

Image analysis

QC Normalization

Statistical analysis

Pathway analysis

Clustering

GO analysis



Hmgcr

Dgat1

Ldlr

Mttp

Soat1

Lipc

Pltp

Lcat


“A picture is worth a thousand words.”

• Intuitive

• Puts data into biological context

• More efficient than looking up single gene information

11 CSIRO Tutorial Series: Pathway Creation | Martina Summer-Kutmon


• Involvement in pathways • Group genes, proteins and other biological molecules

• Reducing complexity

• Several hundred pathways instead of thousands of genes

• Analysis on functional level

• Identify active pathways that differ between two conditions • Higher explanatory power than a simple list of genes


Pathway analysis methods

• Overrepresentation analysis (ORA)

• Functional Class Scoring (FCS)

• Pathway Topology (PT) Based

13

Khatri, Purvesh, Marina Sirota, and Atul J. Butte. "Ten years of pathway analysis: current approaches and outstanding challenges.“ PLoS computational biology 8.2 (2012): e1002375.

CSIRO Tutorial Series: Pathway Creation | Martina Summer-Kutmon


• Overrepresentation analysis • Define input list through criteria

– Which genes are significantly up- or down-regulated

• Count genes in pathway for input and background list

• Perform statistical test for over- or under-representation (e.g. hypergeometric test)



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1. Total number of genes measured in experiment = N

2. Set criteria to define total number of “differential expressed genes” = R (p-value<0.05)

3. Total number of genes in pathway that are measured in experiment = n

4. Number of genes changed in the pathway = r

N = 35 genes

R = 9 genes

n = 12 genes

r = 6 genes

Z-Score = 2.34033

Pathway X



• What does the Z-Score tell you? • Z-Score > 1.96:

– Significantly more genes are changed in the pathway compared to the complete data set

• Z-Score = 0:

– Distribution of changed genes in the pathway is the same as in the complete data set

• Z-Score < -1.96

– Significantly less genes are changed in the pathway compared to the complete data set

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BUT ...



• Be aware!

• Overrepresentation analysis and functional class scoring DO NOT take

pathway topology into account!

• Always manually verify the pathways to make the right conclusions!


Pathway analysis in PathVisio

PathVisio 3.2.1

a tool to edit and analyze biological pathways

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www.pathvisio.org


http://www.pathvisio.org/

PathVisio 3.2.1

• What can you do with PathVisio? • Draw your pathways

• Visualize your data on pathways

• Find pathways regulated in your data set

• More functionality through plugins • Plugin repository with 16 plugins and more coming

• Many different plugin developers


PathVisio application

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Toolbar: drawing objects, layout, view, visualization

Sidepanel: Drawing, Editing, Backpage, Search, Legend

Status bar: Loaded databases, data sets

Pathway display area


PathVisio walkthrough

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Load identifier mapping databases

Create new pathway Load dataset

Create data visualization

Find regulated pathways

WikiPathways

Export pathway image with data

1

Select pathway collection

Draw pathways

Visualize data on pathway

2 Visualize data

3 Pathway statistics Share/Upload


Load identifier mapping databases

• Identifier mapping datbases from • Download bridge files from http://bridgedb.org/data/gene_database/

• Gene products (based on Ensembl)

• Metabolites (based on HMDB)

• Data -> Select Gene/Metabolite Database

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Check status bar!


http://bridgedb.org/data/gene_database/

Identifier mapping

• Annotation of data nodes and interactions

• Xref → identifier + database


Identifier mapping

How does it work in PathVisio?

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Annotation

ID Mapping


Data visualization

• Load dataset • Quantitative data

• Comma separated file (.csv or .txt)

• Identifier column

• System code (1-2 letter code) column → datasource (optional)


Data visualization

• Create visualization • Basic – one value (e.g. logFC)

• Advanced – multiple values (e.g. logFC + p.value)

• Gradient based visualization • logFC

• Rule based visualization • p.value


Data visualization

• Visualize data on pathway


Data visualization

• Export high quality pathway image with data for publications

• Plugins: • HTMLexport plugin

• BioPAX plugin


Pathway statistics

• Download pathway collection from WikiPathways

• http://www.wikipathways.org/index.php/Download_Pathways

• 20 different species

• Find regulated pathways

• Default method: Z-Score statistics


http://www.wikipathways.org/index.php/Download_Pathways

http://www.wikipathways.org/index.php/Download_Pathways

Use cases

Time series data

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JR Tisoncik et al. Microbiology and Molecular Biology Reviews (2012)

Acute-phase response during

H5N1 virus infection.


Tissue expression data

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DGJ Jennen et al. Drug Discovery Today (2010)

Comparison of expression in

different cell types.


Multi-omics data visualization

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I Rubio-Aliaga et al. Physiological Genomics (2011)

Visualization of transcriptomics and metabolomics data

together in the pathway.


Nutritional studies

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M Kutmon et al. Genes & Nutrition (2015)

Cell cycle down-regulation in

prostate cancer cells after vitamin

D treatment


Highlighting genes

• List of genes targeted by a set of microRNAs


Different color for each microRNA

Highlighting of target genes in pathways

Questions

CSIRO NUTRITION & FOOD

Email: [email protected]

Hands-on session

Dataset

• Publicly available gene expression datasets

• Vitamin B12

• Expression data collections: • Gene Expression Omnibus (GEO)

• Array Express

• 1 human dataset studying the effect of different vitamin B12 concentrations in human adipocytes

– http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43166

• Treatment with B12-50uM vs. No treatment (control)

• Data pre-processing is already performed


http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE43166

Dataset


Step-by-step instructions

• On the website Material for tutorial 2 Hands-on session material

• Questions to guide you through the tutorial • Answers will be provided

• Ask if you have any questions or problems!

• http://projects.bigcat.unimaas.nl/adelaide-tutorials-2015/







Data import

• Files generated:

• .pgex data file that can be loaded with “Select expression dataset”

• .pgex.xml visualization options are saved and loaded with the dataset

• .pgex.txt identifiers not recognized by identifier mapping database


Tutorial 2: Pathway Analysis -...

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