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OncoPredictor Insight Presentation - PowerPoint PPT Presentation
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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
# days
Surv
ivor
s
0 500 1000 1500 20000%
20%
40%
60%
80%
100%
Data - Groups
# days
Surv
ivor
s
0 500 1000 1500 20000%
20%
40%
60%
80%
100%
Data - GroupsClass I
Class II
Data - FeaturesFr
eq
uency
Freq
uency
Freq
uency
Freq
uency
CNV
Log2 (Class II / Class I)-0.4 -0.2 0.0 0.2 0.40
5
10
15
20
miRNA
Log2 (Class II / Class I)-0.6 -0.3 0.0 0.3 0.60
100
200
300
mRNA
Log2 (Class II / Class I)-0.8 -0.4 0.0 0.4 0.80
2000
4000
6000
Methylation
Log2 (Class II / Class I)-0.1 0.0 0.1
0
5000
10000
15000
Algorithm
• Random Forest
Algorithm
• Random Forest– 5-fold cross-validation:
Chance
Acc
urac
y
Age /
Gen
der
CNV
miRNA
mRNA
Methyla
tion
0.2
0.4
0.6
0.8
Feature importance
miRNA Feature Relative importanc
e
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
Feature importance
miRNA Feature Relative importanc
e
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
Feature importance
miRNA Feature Relative importanc
e
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
Feature importance
miRNA Feature Relative importanc
e
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
About me
Harvard Bioengineering PhDLongevity, delaying age-related disease
Harvard CollegePhysics, History of Science
