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TRANSCRIPTOMIC CHARACTERIZATION OF INDUCED NEURONS TRANSCRIPTOMIC CHARACTERIZATION OF INDUCED NEURONS

TRANSCRIPTOMIC CHARACTERIZATION OF INDUCED NEURONS - PowerPoint Presentation

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Uploaded On 2020-06-17

TRANSCRIPTOMIC CHARACTERIZATION OF INDUCED NEURONS - PPT Presentation

CHEN MORDECHAY 203215454 Supervisors Professor Eitan Bachmat Doctor Alal Eran Traditional brain research is biased Psychiatric drugs are being tested on humans We wish to test drugs in a safe lab environment ID: 780099

research results induced characterization results research characterization induced treatment control brain framework feature selection samples expression transcriptomic response drugs

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Slide1

TRANSCRIPTOMIC CHARACTERIZATION OF INDUCED NEURONS

CHEN MORDECHAY203215454Supervisors:Professor Eitan BachmatDoctor Alal Eran

Slide2

Traditional brain research is biased

Psychiatric drugs are being tested on humans – We wish to test drugs in a safe lab environmentWe wish to examine the use of Induced Pluripotent Stem Cells in researching brain diseasesTHE PROBLEM

Slide3

50,000 continuous features for each sample

Each feature represents a different geneWe measure the expression levels of each gene in each individualTranscriptomic Characterization

Slide4

THE COMPLETE RNAseq PIPELINE

Slide5

ANALYTIC FRAMEWORK

DATA PREPROCESSINGGather expression matrices

Gather annotations for our samples

2) FEATURE SELECTION

PCA

T-SNE

Differentially expressed genes selection

3) CLASSIFICATION SCHEMES

K-Means

Hierarchical Clustering

Linear Model

4) RESULTS GENERATION

Visualizations

Reports

Slide6

INTERACTIVE RESEARCH INTERFACE

Written in R using Shiny, Hosted on the cloudProcessing of datasets is accomplished using BGU HPC

Slide7

RESULTS

What we have discovered…

Slide8

Positive Control

Dataset source: GTEx - Publicly available250 Samples10 tissues25 samples of each tissueTissues

Adipose Tissue

Blood

Brain

Breast

Colon

Heart

Muscle

Ovary

Pancreas

Testis

Slide9

Results - Positive Control

Slide10

Treatment Response

Private Dataset from a drug discovery company30 samplesDisease: Rett SyndromeGenome editedPharmacologically treated

Treatment control

Slide11

Results – Treatment Response

Slide12

Summary: What we’ve accomplished

Distributed RNAseq processing pipelineSemi-Supervised flexible classification framework developmentImplementation via a cloud based research platform

Slide13

Special thanks is given to Einat Shusterman and Ido Shalev for their invaluable contribution to the project!

Slide14

TRANSCRIPTOMIC CHARACTERIZATION OF INDUCED NEURONS

CHEN MORDECHAY

203215454

Supervisors:

Professor Eitan

Bachmat

Doctor

Alal

Eran