Insight Slides

2. Data - Source
• The Cancer Genome Atlas
– Clinical and genetic records from thousands
of cancer patients
• I examined:
– Disease: Glioblastoma
– Drug: Temozolomide
– 94 patients total
Data type # Features
Age / gender 2
Copy number 100
miRNA expression 500
mRNA expression 17,000
DNA methylation 24,000

3. # days
Survivors
0 500 1000 1500 2000
0%
20%
40%
60%
80%
100%
Data - Groups

4. # days
Survivors
0 500 1000 1500 2000
0%
20%
40%
60%
80%
100%
Data - Groups
Class I Class II

5. Data - Features
C N V
Lo g2 (C lass II / C lass I)
-0.4 -0.2 0.0 0.2 0.4
0
5
10
15
20
m iRN A
Lo g2 (C lass II / C lass I)
-0.6 -0.3 0.0 0.3 0.6
0
100
200
300
m RN A
Lo g2 (C lass II / C lass I)
-0.8 -0.4 0.0 0.4 0.8
0
2000
4000
6000
M et hylat io n
Lo g2 (C lass II / C lass I)
-0.1 0.0 0.1
0
5000
10000
15000

6. Algorithm
• Random Forest

7. Algorithm
• Random Forest
– 5-fold cross-validation:
Chance
AccuracyA
ge
/
G
ender
C
N
V
m
iR
N
A
m
R
N
AM
ethylatio
n
0.2
0.4
0.6
0.8

8. Demo
• http://OncoPredictor.me

9. Feature importance
miRNA Feature Relative
importance
hsa-miR-9 6.1
hsa-miR-572 4.9
hsa-miR-301 4.8
hsa-miR-324-3p 4.2
hsa-miR-217 4.1
hsa-miR-202 4.0
hsa-miR-122a 3.8
hsa-miR-140 3.8
hsa-miR-651 3.7
hsa-miR-598 3.6

10. Feature importance
miRNA Feature Relative
importance
hsa-miR-9 6.1
hsa-miR-572 4.9
hsa-miR-301 4.8
hsa-miR-324-3p 4.2
hsa-miR-217 4.1
hsa-miR-202 4.0
hsa-miR-122a 3.8
hsa-miR-140 3.8
hsa-miR-651 3.7
hsa-miR-598 3.6

11. Feature importance
miRNA Feature Relative
importance
hsa-miR-9 6.1
hsa-miR-572 4.9
hsa-miR-301 4.8
hsa-miR-324-3p 4.2
hsa-miR-217 4.1
hsa-miR-202 4.0
hsa-miR-122a 3.8
hsa-miR-140 3.8
hsa-miR-651 3.7
hsa-miR-598 3.6

12. Feature importance
miRNA Feature Relative
importance
hsa-miR-9 6.1
hsa-miR-572 4.9
hsa-miR-301 4.8
hsa-miR-324-3p 4.2
hsa-miR-217 4.1
hsa-miR-202 4.0
hsa-miR-122a 3.8
hsa-miR-140 3.8
hsa-miR-651 3.7
hsa-miR-598 3.6

13. About me
Harvard Bioengineering PhD
Longevity, delaying age-related disease
Harvard College
Physics, History of Science