stable
Table of Contents
Installation Instructions
Modeling Tutorials
Tutorial 1: Built-in demonstration scripts
Evaluating a GE regression model
Visualizing an MPA regression model
Training a GE regression model
References
Tutorial 2: Protein DMS modeling using additive G-P maps
Training
Visualization
References
Tutorial 3: Splicing MPRA modeling using multiple built-in G-P maps
Training multiple models
Visualizing model performance
Visualizaing pairwie model parameters
References
Tutorial 4: Protein DMS modeling using a biophysical G-P map
Defining a custom G-P map
Training a model with a custom G-P map
Visualizing models with custom G-P maps
References
Tutorial 5: The sort-seq
E. Coli lac
promoter binding analysis using a custom biophysical G-P maps
Training
References
Built-In Datasets
Overview of built-in datasets
gb1 dataset
Summary
Preprocessing
nisthal dataset
Summary
Preprocessing
amyloid dataset
Summary
Preprocessing
tdp43 dataset
Summary
Preprocessing
mpsa datasets
Summary
Preprocessing
sortseq dataset
Summary
Preprocessing
Underlying Mathematics
Notation
Genotype-phenotype (G-P) maps
Additive G-P maps
Neighbor G-P maps
Pairwise G-P maps
Black box G-P maps
MPA measurement processes
GE nonlinearities
GE noise models
Gaussian nose models
Cauchy noise models
Skewed-t noise models
Gauge modes and diffemorphic modes
Fixing diffeomorphic modes
Fixing the gauge
Metrics
Loss function
Variational information
Predictive information
Uncertainties in kNN estimates
References
API Reference
Tests
Examples
Load
Visualization
Models
mavenn
Docs
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Index
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Index
B
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F
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G
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H
|
I
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L
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M
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P
|
R
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S
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X
|
Y
B
bootstrap() (mavenn.Model method)
F
fit() (mavenn.Model method)
G
get_nn() (mavenn.Model method)
get_theta() (mavenn.Model method)
H
heatmap() (in module mavenn)
heatmap_pairwise() (in module mavenn)
I
I_predictive() (mavenn.Model method)
I_variational() (mavenn.Model method)
L
list_tutorials() (in module mavenn)
load() (in module mavenn)
load_example_dataset() (in module mavenn)
load_example_model() (in module mavenn)
M
Model (class in mavenn)
P
p_of_y_given_phi() (mavenn.Model method)
p_of_y_given_x() (mavenn.Model method)
p_of_y_given_yhat() (mavenn.Model method)
phi_to_yhat() (mavenn.Model method)
R
run_demo() (in module mavenn)
run_tests() (in module mavenn)
S
save() (mavenn.Model method)
set_data() (mavenn.Model method)
simulate_dataset() (mavenn.Model method)
X
x_to_phi() (mavenn.Model method)
x_to_yhat() (mavenn.Model method)
Y
yhat_to_yq() (mavenn.Model method)
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