Behavioral phenotyping project

Behavioral data embeddings for the stratification of individuals with neurodevelopmental conditions.

Designed for observational measurements of cognition and behavior of individuals with Autism Spectrum Conditions (ASCs).

TODO: Abstract

Technical Requirements

Python 3.6+

R 3.4+

The full list of required Python Packages is available in requrirements.txt file. It is possible to install all the dependency by:

$ pip install -r requirements.txt 

Behavioural Phenotyping Pipeline (TLDR ;))

A complete example of the Behavioural Phenotype Stratification is available as Jupyter notebook:

jupyter notebook behavioral_phenotyping_pipeline.ipynb

Documentation (at a glance)

The code is structured into multiple modules (.py files), including algorithms and methods for the multiple steps of the pipeline:

• dataset.py: Connects to the database and dump data
• features.py: Returns vocabulary and dictionary of behavioral EHRs for each of the 4 possible depth levels. It also returns a dataset with quantitative scores for level 4 features
• pt_embedding.py: Performs TFIDF for patient embeddings; Glove embeddings on words and average them out for subject embeddings; Word2vec embeddings on words, that are then averaged to output individual representations
• clustering.py: Performs Hierarchical Clustering/k-means on embeddings, and quantitative 4th level features
• visualization.py: Visualizes results (e.g. scatterplot & dendrogram)for sub-cluster visualization; Heatmap for inspection of quantitative scores between sub-clusters
• basic_statistics.py: Returns basic demographic statistics for dataset description
• test-demog-cl.R: Runs multiple pairwise comparisons between subgroups to check for confounders and support clinical validation

TODO: Paper, Poster, Conference Reference

TODO: Credits and Acknowledgements