Introduction Biological Background Method Results Moving Forward

Modeling gene expression using five

histone modificationsFifth Annual Primes MIT Conference

Lalita Devadas

Mentor: Angela Yen

May 17, 2015

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Introduction Biological Background Method Results Moving Forward

Outline

1 Biological Background

2 Method

3 Results

4 Moving Forward

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Introduction Biological Background Method Results Moving Forward

Outline

1 Biological Background

2 Method

3 Results

4 Moving Forward

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Introduction Biological Background Method Results Moving Forward

Gene ExpressionCentral dogma of molecular biology

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Introduction Biological Background Method Results Moving Forward

Gene ExpressionRelevance

Important to understanding biological activity

Crucial to advances in medicine

Detection, prevention, and treatment of disease

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Introduction Biological Background Method Results Moving Forward

Gene ExpressionRegulation

Genetic

Sequences of nucleotides (ACTG)

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Introduction Biological Background Method Results Moving Forward

Gene ExpressionRegulation

Epigenetic

Changes to environment surrounding DNA

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Introduction Biological Background Method Results Moving Forward

EpigeneticsHistone modifications

Chemical changes to histone protein core or protrudingtail

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Introduction Biological Background Method Results Moving Forward

EpigenomesRoadmap Project

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Introduction Biological Background Method Results Moving Forward

Outline

1 Biological Background

2 Method

3 Results

4 Moving Forward

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Introduction Biological Background Method Results Moving Forward

Data PipelineObjective

Density of HistoneModifications

Level of GeneExpression

Prediction

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Introduction Biological Background Method Results Moving Forward

Data PipelineOverview

All Histone Data

Relevant Histone Data

“Off” genes (Unexpressed) “On” genes (Expressed)

Predicted Expression

Best-binning

Classification Classification

Predict at 0 Regression

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Introduction Biological Background Method Results Moving Forward

Data PipelineBest-bin approach

All Histone Data

Relevant Histone Data

“Off” genes (Unexpressed) “On” genes (Expressed)

Predicted Expression

Best-binning

Classification Classification

Predict at 0 Regression

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Introduction Biological Background Method Results Moving Forward

Best-bin approachDividing genes

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Introduction Biological Background Method Results Moving Forward

Best-bin approachChoosing best bin

strongest correlation

epigenome X, histone mark Y

p = best bin

bin 1 bin 2 bin 3 bin 4 . . bin p . . . bin 81 expression

gene a

gene b

gene c

.

.

.

.

.

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Introduction Biological Background Method Results Moving Forward

Data PipelineClassification

All Histone Data

Relevant Histone Data

“Off” genes (Unexpressed) “On” genes (Expressed)

Predicted Expression

Best-binning

Classification Classification

Predict at 0 Regression

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Introduction Biological Background Method Results Moving Forward

Types of ModelsRandom Forest

Random Forest model

Returns majority vote of classification determined by a groupof decision trees

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Introduction Biological Background Method Results Moving Forward

Types of ModelsRandom Forest

Random Forest model

Returns majority vote of classification determined by a groupof decision trees

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Introduction Biological Background Method Results Moving Forward

Data PipelineRegression

All Histone Data

Relevant Histone Data

“Off” genes (Unexpressed) “On” genes (Expressed)

Predicted Expression

Best-binning

Classification Classification

Predict at 0 Regression

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Introduction Biological Background Method Results Moving Forward

Types of ModelsLinear Model

Linear model

Finds a linear correlation between predictors and response

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Introduction Biological Background Method Results Moving Forward

Data PipelineOverview

All Histone Data

Relevant Histone Data

“Off” genes (Unexpressed) “On” genes (Expressed)

Predicted Expression

Best-binning

Classification Classification

Predict at 0 Regression

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Introduction Biological Background Method Results Moving Forward

Outline

1 Biological Background

2 Method

3 Results

4 Moving Forward

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Introduction Biological Background Method Results Moving Forward

EpigenomesRoadmap Project

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Introduction Biological Background Method Results Moving Forward

Data PipelineObjective

Density of HistoneModifications

Level of GeneExpression

H3K9me3

H3K4me3

H3K4me1

H3K36me3

H3K27me3

Prediction

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Introduction Biological Background Method Results Moving Forward

Results of PipelineConclusions

Models created for cultured epigenomes have a muchhigher predictive power than those created for tissuesamples

H3K36me3 is the most important histone mark used forprediction

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Introduction Biological Background Method Results Moving Forward

Results of PipelineGraph

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Introduction Biological Background Method Results Moving Forward

Specifics of Best ModelClassification Accuracy

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Introduction Biological Background Method Results Moving Forward

Specifics of Best ModelRegression Accuracy

every data pointrepresents one gene

r2 value: 0.640

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Introduction Biological Background Method Results Moving Forward

Outline

1 Biological Background

2 Method

3 Results

4 Moving Forward

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Introduction Biological Background Method Results Moving Forward

Next Steps

Improve predictive power

Broaden scope of predictors and response

Further analysis of current results

Apply procedure to different data

Release code as a tool for other researchers

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Introduction Biological Background Method Results Moving Forward

Acknowledgements

I would like to thank:

My mentor, Angela Yen

Prof. Manolis Kellis

Roadmap Project

PRIMES program

My family

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