www.cmmt.ubc.ca

MOTIF ENRICHMENT ANALYSIS IN CO-EXPRESSED GENE SETS AND HIGH-

THROUGHPUT SEQUENCE SETS

Wyeth WassermanJan. 18, 2012

opossum.cisreg.ca/oPOSSUM3

Welcome

• If you encounter any technical difficulties during the webinar– Type a report using the chat option

• Slide presentation ~20 min• Compile Questions as they are submitted

and answer them during the final Q&A/discussion period

• During the discussion session, we’ll allow audience speaking

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Webinar Format

• Introduction• Walk-Through• Summary• Q&A

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INTRODUCTION

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Overview

• Given co-expressed gene sets, what are the key mediators of co-expression?– Focus on TFs

• Web-based software system for motif enrichment analysis– Co-expressed genes or sequences– Multiple sets of analysis methods– Available for human, mouse, fly, worm, yeast

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Motif Enrichment Analysis

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Background Target

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0.2

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TFBS1 TFBS2 TFBS3

Prop

ortio

n of

gen

es c

onta

inin

g TF

BS

BackgroundTarget

p=0.04 p=0.55 p=0.66

Finds over-represented TFBS in co-expressed gene sets

What do we need?

• Region selection– Where to look for enriched binding sites– Use conservation filter to restrict search

space• TFBS profiles to search for

– Need a pool of validated profiles• Scoring metrics for enrichment

– How to measure motif over-representation

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GeneCR1 CR2 CR4CR3

Threshold

Genomic Position

phastConsScore

Conserved Region Selection

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TFBS Profiles• JASPAR 2010: Portales-Casamar et al. Nucleic

Acids Research 2009.• Expanded collection of TFBS profiles

– 130 vertebrate profiles– 105 insect profiles– 5 nematode profiles– 177 yeast profiles– PBM (104), PBM_HOMEO (176), PBM_BHLH (19)

• Standardized 2-level TF classification (class, family)

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Scoring Metrics

• Z scores– Based on the number of occurrences of the TFBS

relative to background– Normalized for sequence length– Simple binomial distribution model

• Fisher scores– Fisher exact probability test

• Fisher score = -log(Fisher p-value)– Based on the number of genes containing the TFBS

relative to background

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Additional Metric for Seq-Based• KS scores

– Kolmogorov-Smirnoff test– Compares the empirical

distribution of the distances of the binding sites from the maximum point of confidence (MPC) to the background

– Expect real binding sites to be centered around the MPC

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MPC

Foreground

Background

KS score = -log(KS test p-value)

Analysis Methods

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WALK-THROUGH

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http://opossum.cisreg.ca/oPOSSUM3

Human SSA - Input

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Human SSA - Results

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TF HNF1A

JASPAR ID MA0046.1

Class Helix-Turn-Helix

Family Homeo

Tax Group Vertebrates

IC 15.548

GC Content 0.259

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Target Gene Hits 19

Target Gene Non-Hits 36

Background Gene Hits 1113

Background Gene Non-Hits 3887

Target TFBS Hits 41

Target TFBS Nucleotide Rate 0.0269

Background TFBS Hits 2127

Background TFBS Nucleotide Rate 0.009

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Z-score 15.134

Fisher score 3.646

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oPOSSUM methods

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Human aCSA - Input

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Human aCSA - Input

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Human aCSA - Input

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Human aCSA - Results

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TFBS Cluster Analysis

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TFBS ProfileCluster

GeneCR1 CR2 CR4CR3

TFBSs

TFBS Cluster Hits

Merge

Overrepresentation Analysisbased on merged TFBS cluster hits

TFBS Cluster Analysis (TCA)

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Human TCA – TFBS cluster selection

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Human TCA - Results

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TFCluster Info Page

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Seq SSA - Input

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Seq SSA - Input

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Seq SSA - Results

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KS score

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Seq TCA - Input

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SUMMARY

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oPOSSUM-3

• Web-based system for motif enrichment analysis in co-expressed gene sets and sequences from high-throughput experiments

• Important functionalities– Gene-based vs. Sequence-based– Single site vs. Anchored combination site– Individual vs. clusters of TFBS profiles– Human, mouse, fly, worm and yeast

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Development Team

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Version 1 CSA Version 2 Version 3• Ho Sui, SJ• Mortimer, JR• Arenillas, DJ• Brumm, J• Walsh, CJ• Kennedy, BP• Wasserman,

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• Huang, S• Fulton, DL• Arenillas, DJ• Perco, P• Ho Sui, SJ• Mortimer, JR• Wasserman,

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• Ho Sui, SJ• Fulton, DL• Arenillas, DJ• Kwon, AT• Wasserman,

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• Kwon, AT• Arenillas, DJ• Worsely

Hunt, R• Wasserman,

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QUESTIONS & ANSWERS

Please take a moment to type questions/comments into the chat box.The questions will be answered shortly.

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