1. gene
EXTRAPOLATION
models for
TOXICOGENOMIC
data
daniel gusenleitner
nacho caballero

2. Testing for carcinogenicity
is costly

3. Genes show
clustered
responses
Expression
correlates
between
platforms

4. We want to extrapolate the
expression of regular genes
11000 Genes
2K Arrays
10K 1K
Regular Landmark
Genes Genes

5. We fit a linear
model to each
2K Arrays
1K
regular gene X Landmark
Genes
Predicted Expression = Xβ
Expression Gene 1 = X1β1 +X2β2 +…+X2Kβ2K
Expression Gene 2 = X1β1 +X2β2 +…+X2Kβ2K
…
Expression Gene 10K = X1β1 +X2β2 +…+X2Kβ2K

6. Elastic
Net
mean error
number of variables
glmnet: Lasso and elastic-
net regularized
generalized linear models
http://cran.r-project.org/web/
packages/glmnet/index.html

7. Neural
Networks
regular
genes
hidden
layer
nnet: Feed-forward
Neural Networks and
Multinomial Log-
Linear Models landmark
http://cran.r-project.org/ genes
web/packages/nnet/index.html

8. mean fluorescent intensity
signal
ratio
Intensity variation
-to-
noise
intensity standard deviation
SNR = extrapolation mean error

9. Building 10451 models
takes a long time…
runtime single
total
per CPU
runtime
model runtime
linear
120 x 3 h 2 min 360 h
regression
elastic
120 x 16 h 11 min 1920 h
net
neural 50 x 0.75 7800 h
45 min
network h ?

10. Signal-to-Noise Comparison
E-net LM NN
ENSRNOG00000013133 135.58 19.62 13.21
ENSRNOG00000011861 209.82 28.82 12.08
ENSRNOG00000033466 190.81 26.58 11.86
ENSRNOG00000036816 197.82 23.09 9.93
ENSRNOG00000003515 273.62 29.35 8.68
ENSRNOG00000002254 53.43 8.83 7.21
ENSRNOG00000031266 76.19 8.19 6.70
ENSRNOG00000005963 145.06 6.99 6.49
ENSRNOG00000008613 38.86 3.97 6.07
ENSRNOG00000023095 13.57 2.70 5.98
ENSRNOG00000020947 17.27 2.41 5.04
ENSRNOG00000007258 103.77 13.71 4.91
ENSRNOG00000019813 16.53 3.01 4.68
ENSRNOG00000014232 61.69 9.17 4.05
ENSRNOG00000002454 50.71 5.58 3.80
ENSRNOG00000018201 5.04 1.64 3.39

11. The elastic net
outperforms
standard linear regression
Signal-to-noise ratio
Elastic Linear
Net Regression

12. Additional feature selection
Performance of extrapolation models
on carcinogenicity classifiers
Correlation between Luminex and
Affymetrix chips