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.

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.

# 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))

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.

• Quick Guide
  • Introduction
  • Simple Example
  • Install and dependencies
  • Running tests
• Detailed list of models
  • EpistasisLinearRegression
  • EpistasisRidge
  • EpistasisLasso
  • EpistasisElasticNet
  • EpistasisNonlinearRegression
  • EpistasisSpline
  • EpistasisPowerTransform
  • EpistasisLogisticRegression
  • EpistasisEnsembleRegression
• Building an epistasis pipeline
  • Simple Example
• Anatomy of an epistasis model
  • The X matrix
  • Methods in every epistasis model
  • Methods in nonlinear models
• Simulating epistatic genotype-phenotype maps
  • LinearSimulation
  • NonlinearSimulation
• Plotting in the epistasis package
  • Plot epistatic coefficients
  • Plot nonlinear scale
• Advanced topics
  • Building your own X matrix
  • Write your own linear model
  • Setting bounds on nonlinear fits
  • Large genotype-phenotype maps
  • Estimating model uncertainty
• Saving an epistasis model
  • Pickle
  • Excel Spreadsheet
  • CSV File
• API documentation
  • epistasis.models package
  • epistasis.pyplot package
  • epistasis.sampling package
  • epistasis.simulate package
  • epistasis.mapping module
  • epistasis.matrix module
  • epistasis.stats module

Example Gallery

---

Fitting nonlinear genotype-phenotype maps

High-order epistasis model

Handling dead phenotypes

Indices and tables

• Index

• Module Index

• Search Page