Code associated with the article "Mitochondrial Network State Scales mtDNA Genetic Dynamics". See https://doi.org/10.1534/genetics.119.302423
Clone the repository
$ git clone --recursive https://github.com/ImperialCollegeLondon/MitoNetworksGenetics.git
to make sure you get the mitonetworks repository too. Much of the python code depends on the mitonetworks
package which contains a set of helper functions and classes. To install this package, perform the following commands
$ cd mitonetworks
$ python setup.py sdist
$ pip install ./dist/mitonetworks-0.0.1.tar.gz
Param_sweeps
: Parameter sweeps for a set of replication/degradation rate functions, Figures S4B-I
Ablate_fusion_fission
: Figure S2BDeterministic_phase_portrait
: Figures 2A,B and Figure S2AQuality_control/sel_fus/Analysis
: Figure 4AQuality_control/QC_sweep
: Figure S7Quality_control/sel_deg/Analysis
: Figure 4BStochastic_analysis/delta_sweep/Post_processing/Analysis
: Figure 2GStochastic_analysis/Fast_turnover
: Figure S5Stochastic_analysis/kappa_sweep/Analysis
: Figure 2FStochastic_analysis/mu_sweep/Analysis
: Figure 2EStochastic_analysis/network_and_b_sweep/Post_processing/Analysis
: Figure S3B,C,D,E, Figure S4A, and Figure 2HStochastic_analysis/Nominal_parametrization/Analysis
: Figure 2C,D and Figure S3AStochastic_analysis/xi_sweep/Analysis
: Figure S3E
- Exploration of the infinite sites Moran model, Figure 3.
- Exploration of a biallelic Moran model, Figure S6
- Deterministic treatment of a simple network process, Figure S1
The following table summarizes the locations of the Mathematica proofs in the paper. LFC = linear feedback control.