BATCHIE

Welcome to the documentation for the Python implementation of BATCHIE

If you use BATCHIE please cite our preprint:

A Bayesian active learning platform for scalable combination drug screens
Christopher Tosh, Mauricio Tec, Jessica White, Jeffrey F Quinn, Glorymar Ibanez Sanchez, Paul Calder, Andrew L Kung, Filemon S Dela Cruz, Wesley Tansey
bioRxiv 2023.12.18.572245; doi: https://doi.org/10.1101/2023.12.18.572245

Contents

• Installation
  • Prerequisites
  • Option 1: Install Using pip
  • Option 2: Using Docker
• Quickstart Demo
• BATCHIE Data Format
  • Example
  • Explanation of Terms
  • Explanation of Example
  • On-Disk Format
• BATCHIE Output Format
  • Glossary of Output Files
• Running BATCHIE
  • Prerequisites
  • Prospective
  • Retrospective
  • Computational Cost
• Configuring BATCHIE
  • Pipeline Wide Parameters
  • Process Specific Parameters
• Extending BATCHIE
  • Adding a new model
  • Other Extensible Classes
• Retrospective Experiments
  • Merck
  • NCI Almanac
  • GDSC^2
• Command Line Interface
  • train_model
  • evaluate_model
  • calculate_distance_matrix
  • calculate_scores
  • select_next_plate
  • reveal_plate
  • extract_screen_metadata
  • prepare_retrospective_simulation
• batchie package
  • Submodules
  • batchie.common module
  • batchie.core module
  • batchie.data module
  • batchie.distance_calculation module
  • batchie.fast_mvn module
  • batchie.introspection module
  • batchie.log_config module
  • batchie.retrospective module
  • batchie.sampling module
  • batchie.synergy module
  • batchie.distance.mse module
  • batchie.models.sparse_combo module
  • batchie.models.sparse_combo_interaction module
  • batchie.policies.k_per_sample module
  • batchie.scoring.gaussian_dbal module
  • batchie.scoring.main module
  • batchie.scoring.size module
  • batchie.scoring.rand module

Indices and tables

• Index

• Module Index

• Search Page