.. epistasis documentation master file, created by sphinx-quickstart on Thu Jul 7 15:47:18 2016. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. ``epistasis`` ============= A Python API for modeling statistical, high-order epistasis in genotype-phenotype maps. You can use this library to: 1. Decompose genotype-phenotype maps into high-order epistatic interactions 2. Find nonlinear scales in the genotype-phenotype map 3. Calculate the contributions of different epistatic orders and 4. Estimate the uncertainty in the epistatic coefficients and For more information about the epistasis models in this library, see our Genetics paper: `Sailer, Z. R., & Harms, M. J. (2017). "Detecting High-Order Epistasis in Nonlinear Genotype-Phenotype Maps." Genetics, 205(3), 1079-1088.`_ .. _`Sailer, Z. R., & Harms, M. J. (2017). "Detecting High-Order Epistasis in Nonlinear Genotype-Phenotype Maps." Genetics, 205(3), 1079-1088.`: http://www.genetics.org/content/205/3/1079 This library is built on top of well known tools in the scientific Python stack. It uses packages like matplotlib, numpy, scipy, scikit-learn, and pandas. We strive to follow similar inferface designs present in this ecosytem. If you notice ways we can improve, please open an issue on Github! We'd love to hear your feedback. Currently, this package works only as an API. There is no command-line interface. Instead, we encourage you use this package inside `Jupyter notebooks`_ . Basic Example ------------- Fit an epistasis model to genotype-phenotype map data. .. code-block:: python # Import a model and the plotting module from gpmap import GenotypePhenotypeMap from epistasis.models import EpistasisLinearRegression from epistasis.pyplot import plot_coefs # Genotype-phenotype map data. wildtype = "AAA" genotypes = ["ATT", "AAT", "ATA", "TAA", "ATT", "TAT", "TTA", "TTT"] phenotypes = [0.1, 0.2, 0.4, 0.3, 0.3, 0.6, 0.8, 1.0] # Create genotype-phenotype map object. gpm = GenotypePhenotypeMap(wildtype=wildtype, genotypes=genotypes, phenotypes=phenotypes) # Initialize an epistasis model. model = EpistasisLinearRegression(order=3) # Add the genotype phenotype map. model.add_gpm(gpm) # Fit model to given genotype-phenotype map. model.fit() # Plot coefs. fig, axes = plot_coefs(model, figsize=(2,4)) .. image:: img/basic-example.png Documentation ------------- We are still working hard on the Docs! You may notice blank spots in various places. We appreciate your patience as we try to catch up on docs. .. toctree:: :maxdepth: 2 pages/quick_guide pages/models pages/pipeline pages/anatomy pages/simulate pages/visualize pages/advanced pages/io api/main .. ------------------------- Example Gallery ------------------------- Example Gallery --------------- ------------------------------ .. raw:: html
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.. ------------------------- Tables and search ------------------------- Indices and tables ------------------ * :ref:`genindex` * :ref:`modindex` * :ref:`search` .. _Jupyter notebooks: http://jupyter.org/