Analyses - #3
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NoWon1
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Please do review these too and lmk if anything else is to be uploaded. Thanks and regards. |
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Pull request overview
Adds exploratory analysis outputs (CSV exports) for multiple simulation conditions (population/MMP variants) and includes a few helper Python scripts intended to post-process CC3D outputs and generate plots/statistics.
Changes:
- Added multiple CSV exports (
cell_count,mutation_effect,collective_invasion) for several experimental conditions (Normal, MORE/LESS_POPULATION, Half/Extra/Double_MMP, etc.). - Added analysis scripts under
Analysis/LESS_POPULATION/for peak-finding (comp.py), CC3D batch processing, and violin-plot statistical analysis.
Reviewed changes
Copilot reviewed 27 out of 49 changed files in this pull request and generated 7 comments.
Show a summary per file
| File | Description |
|---|---|
| Analysis/Normal/mutation_effect.csv | Adds mutation-effect time series export for “Normal” condition. |
| Analysis/Normal/Half_MMP/mutation_effect.csv | Adds mutation-effect export for Normal/Half_MMP variant. |
| Analysis/Normal/Half_MMP/cell_count.csv | Adds cell-count export for Normal/Half_MMP variant. |
| Analysis/Normal/collective_invasion.csv | Adds collective-invasion area metrics export for “Normal” condition. |
| Analysis/Normal/cell_count.csv | Adds cell-count export for “Normal” condition. |
| Analysis/MORE_POPULATION/mutation_effect.csv | Adds mutation-effect export for MORE_POPULATION condition. |
| Analysis/MORE_POPULATION/collective_invasion.csv | Adds collective-invasion area metrics export for MORE_POPULATION condition. |
| Analysis/MORE_POPULATION/cell_count.csv | Adds cell-count export for MORE_POPULATION condition. |
| Analysis/LESS_POPULATION/process_cc3d_data.py | Adds a CC3D output processing template for extracting cluster metrics. |
| Analysis/LESS_POPULATION/mutation_effect.csv | Adds mutation-effect export for LESS_POPULATION condition. |
| Analysis/LESS_POPULATION/comp.py | Adds a plotting script correlating mutation-effect peaks with cell counts. |
| Analysis/LESS_POPULATION/collective_invasion.csv | Adds collective-invasion area metrics export for LESS_POPULATION condition. |
| Analysis/LESS_POPULATION/cell_count.csv | Adds cell-count export for LESS_POPULATION condition. |
| Analysis/LESS_POPULATION/cc3d_violin_analysis.py | Adds violin-plot + ANOVA/Tukey analysis script for adhesion-condition comparisons. |
| Analysis/Less pop and normal mmp/mutation_effect.csv | Adds mutation-effect export for “Less pop and normal mmp” condition. |
| Analysis/Less pop and normal mmp/collective_invasion.csv | Adds collective-invasion area metrics export for “Less pop and normal mmp” condition. |
| Analysis/Less pop and normal mmp/cell_count.csv | Adds cell-count export for “Less pop and normal mmp” condition. |
| Analysis/Half_MMP/mutation_effect.csv | Adds mutation-effect export for Half_MMP condition. |
| Analysis/Half_MMP/collective_invasion.csv | Adds collective-invasion area metrics export for Half_MMP condition. |
| Analysis/Half_MMP/cell_count.csv | Adds cell-count export for Half_MMP condition. |
| Analysis/EXTRA_MMP/mutation_effect.csv | Adds mutation-effect export for EXTRA_MMP condition. |
| Analysis/EXTRA_MMP/cell_count.csv | Adds cell-count export for EXTRA_MMP condition. |
| Analysis/Double_MMP/mutation_effect.csv | Adds mutation-effect export for Double_MMP condition. |
| Analysis/Double_MMP/collective_invasion.csv | Adds collective-invasion area metrics export for Double_MMP condition. |
| Analysis/Double_MMP/cell_count.csv | Adds cell-count export for Double_MMP condition. |
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| cell_count_df.columns = ['MCS', 'CoI', 'Laminin', 'Cancer1', 'Cancer2', | ||
| 'C_Lysed', 'L_Lysed', 'NCoI', 'Immune', 'Apoptotic'] | ||
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| import warnings | ||
| warnings.filterwarnings('ignore') |
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| def load_simulation_data(self, data_path=None, simulation_data=None): | ||
| """ | ||
| Load CC3D simulation results | ||
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| Parameters: | ||
| ----------- | ||
| data_path : str, optional | ||
| Path to CSV file containing simulation results | ||
| simulation_data : dict, optional | ||
| Dictionary containing simulation results | ||
| """ | ||
| if data_path: | ||
| self.data = pd.read_csv(data_path) | ||
| elif simulation_data: | ||
| self.data = pd.DataFrame(simulation_data) | ||
| else: | ||
| # Generate sample data for demonstration | ||
| self.data = self._generate_sample_data() | ||
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| # Load data (replace with your actual data loading) | ||
| analyzer.load_simulation_data() | ||
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| def create_violin_plot(self, adhesion_type, figsize=(12, 8)): | ||
| """ | ||
| Create violin plots for both metrics | ||
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| Parameters: | ||
| ----------- | ||
| adhesion_type : str | ||
| 'cell-cell' or 'cell-ECM' | ||
| figsize : tuple | ||
| Figure size | ||
| """ | ||
| # Filter data | ||
| plot_data = self.data[self.data['adhesion_type'] == adhesion_type].copy() | ||
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| # Create figure with subplots | ||
| fig, axes = plt.subplots(1, 2, figsize=figsize) |
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| def process_all_simulations(): | ||
| """ | ||
| Process all CC3D simulation results | ||
| """ | ||
| # Initialize processor | ||
| processor = CC3DDataProcessor("/path/to/your/cc3d/simulations") | ||
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| import pandas as pd | ||
| import matplotlib.pyplot as plt | ||
| from scipy.signal import find_peaks |
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the .CSVs for having conducted ExploratoryDataAnalysis and Data wrangling.