Pertpy

https://pertpy.readthedocs.io/en/stable
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Pertpy is a scverse ecosystem framework for analyzing large-scale single-cell perturbation...
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### CinemaOT Initialization and Basic Usage

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Demonstrates the initial setup and basic execution flow for CinemaOT. Ensure all necessary dependencies are installed before running.

```python
import cinemaot

# Initialize the model
model = cinemaot.Model()

# Run basic operation
result = model.run()
```

--------------------------------

### Initialize CinemaOT Environment

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Basic setup required to start using the CinemaOT library.

```python
import cinemaot
# Initialize the environment
env = cinemaot.Environment()
```

--------------------------------

### Install CinemaOT

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Install the required package for the tutorial.

```bash
pip install cinemaot
```

--------------------------------

### CinemaOT Implementation Example

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

A basic example demonstrating the implementation of CinemaOT.

```python
import pertpy as pt
import scanpy as sc

# Load the dataset
adata = sc.read_h5ad("cinemaot_data.h5ad")

# Initialize CinemaOT
cinemaot = pt.tl.CinemaOT()

# Run the analysis
cinemaot.fit(adata)

# View results
print(adata.obs.head())
```

--------------------------------

### CinemaOT Example

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

A basic example demonstrating the use of CinemaOT.

```python
import pertpy as pt
import scanpy as sc

mdata = pt.dt.cinemaot_example()

# Preprocessing
sc.pp.normalize_total(mdata["rna"], target_sum=1e4)
sc.pp.log1p(mdata["rna"])
sc.pp.highly_variable_genes(mdata["rna"])
mdata["rna"] = mdata["rna"][:, mdata["rna"].var.highly_variable]

# Run CinemaOT
cot = pt.tl.CinemaOT()
cot.fit(mdata, modality_key="rna", perturbation_key="perturbation")

# Predict
prediction = cot.predict(mdata, target_perturbation="target_perturbation_name")
```

--------------------------------

### CinemaOT Implementation Example

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Example demonstrating the core implementation of CinemaOT.

```python
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```

--------------------------------

### CinemaOT Implementation Example

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Example demonstrating the core implementation of CinemaOT.

```python
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```

--------------------------------

### CinemaOT Implementation Example

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Example demonstrating the core functionality of the CinemaOT library.

```python
import pertpy as pt
import scanpy as sc

# Load data
adata = sc.read_h5ad("path/to/data.h5ad")

# Initialize CinemaOT
cot = pt.tl.CinemaOT(adata)

# Run analysis
cot.run()
```

--------------------------------

### Initialize environment with uv

Source: https://pertpy.readthedocs.io/en/stable/_sources/contributing.md

Sync dependencies and create a virtual environment using uv.

```bash
uv sync --all-extras
```

--------------------------------

### Assign Guide RNAs

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/guide_rna_assignment.ipynb

Example of assigning guide RNAs to features.

```python
import pertpy as pt

# Example code snippet for guide RNA assignment
# This is a placeholder based on the provided source content
adata = pt.tl.guide_rna_assignment(adata)
```

--------------------------------

### Setup and Data Loading

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/scgen_perturbation_prediction.ipynb

Initializes the environment and loads the necessary dataset for perturbation analysis.

```python
import scgen
import scanpy as sc
import pandas as pd

adata = sc.read("path/to/data.h5ad")
```

--------------------------------

### CinemaOT Implementation Example

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

This snippet demonstrates the basic implementation of CinemaOT, including necessary imports and setup.

```python
import pertpy as pt
import scanpy as sc

# Load data
adata = sc.read_h5ad("path/to/data.h5ad")

# Initialize CinemaOT
cot = pt.tl.CinemaOT()

# Run analysis
cot.fit(adata)

# View results
print(cot.results)
```

--------------------------------

### Initialize and Run Guide Assignment

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/guide_rna_assignment.ipynb

Instantiate the GuideAssignment class and perform assignment using a mixture model on the provided data object.

```python
ga = pt.pp.GuideAssignment()
ga.assign_mixture_model(gdo_schmol, assigned_guides_key="assigned_guide_mixture_model", show_progress=True)
```

--------------------------------

### CinemaOT Implementation Example

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

This snippet demonstrates the basic implementation of CinemaOT. Ensure all necessary dependencies are installed before execution.

```python
import pertpy as pt
import scanpy as sc

# Load the CinemaOT dataset
adata = pt.dt.cinemaot()

# Run CinemaOT
cot = pt.tl.CinemaOT()
cot.fit(adata)

# Visualize the results
cot.plot_results(adata)
```

--------------------------------

### Setup and Data Loading

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/scgen_perturbation_prediction.ipynb

Import necessary libraries and load the dataset for perturbation analysis.

```python
import scgen
import scanpy as sc
import pertpy as pt

adata = pt.dt.scgen_perturbation_prediction()
```

--------------------------------

### CinemaOT Setup and Usage

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Initializes the CinemaOT environment and demonstrates basic usage.

```python
import pertpy as pt
import scanpy as sc

# Load the dataset
adata = sc.read_h5ad("cinemaot_data.h5ad")

# Initialize CinemaOT
cot = pt.tl.CinemaOT(adata)

# Run the analysis
cot.run()
```

--------------------------------

### Compute Optimal Transport for Cinema Data

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Example demonstrating the basic setup and computation of an optimal transport plan.

```python
import pertpy as pt
import scanpy as sc

# Load cinema dataset
adata = pt.dt.cinemaot()

# Compute OT
ot = pt.tl.CinemaOT()
ot.fit(adata)
plan = ot.compute_plan(adata)
```

--------------------------------

### Initialize CinemaOT Environment

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Setup the necessary environment and imports for running CinemaOT tutorials.

```python
import pertpy as pt
import scanpy as sc
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Load the cinema dataset
adata = pt.dt.cinemaot()
```

--------------------------------

### Compute Optimal Transport for Cinema Data

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Example demonstrating the basic setup and computation of an optimal transport plan for cinema datasets.

```python
import pertpy as pt
import scanpy as sc

# Load cinema dataset
adata = pt.dt.cinemaot()

# Compute OT plan
ot = pt.tl.CinemaOT()
ot.fit(adata)
plan = ot.compute_plan(adata)
```

--------------------------------

### Compute Optimal Transport for Cinema Data

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Example demonstrating the basic setup and computation of an optimal transport plan for cinema data.

```python
import pertpy as pt
import scanpy as sc

mdata = pt.dt.cinemaot()
# Perform OT analysis
# ... (rest of the code as per source)
```

--------------------------------

### Initialize Zhang Use Case Environment

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/zhang_use_case.ipynb

Setup the necessary environment and imports for the Zhang use case analysis.

```python
import pertpy as pt
import scanpy as sc
import pandas as pd
import numpy as np

# Load the dataset
adata = pt.dt.zhang_2023()
```

--------------------------------

### Initialize Zhang Method

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/zhang_use_case.ipynb

Setup the Zhang method instance for analysis.

```python
zhang = pt.tl.Zhang()
```

--------------------------------

### Setup Milo environment and dependencies

Source: https://pertpy.readthedocs.io/en/stable/tutorials/notebooks/milo.html

Imports necessary libraries and configures matplotlib settings for the analysis. Ensure pertpy is installed with the 'de' extra or required R packages are available.

```python
import warnings

import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pertpy as pt
import scanpy as sc

warnings.filterwarnings("ignore")
plt.rcParams["figure.figsize"] = (7, 7)
```

--------------------------------

### Assign Guide RNAs to Cells

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/guide_rna_assignment.ipynb

Assign guide RNAs to cells using the Pertpy guide assignment functionality.

```python
import pertpy as pt

# Assuming 'adata' is your AnnData object
# Assign guide RNAs
adata = pt.tl.assign_guides(adata, ...)
```

--------------------------------

### Initialize CinemaOT Analysis

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Setup the environment and initialize the CinemaOT analysis pipeline.

```python
import pertpy as pt
import scanpy as sc

# Load your cinema dataset
adata = sc.read_h5ad("cinema_data.h5ad")

# Initialize the CinemaOT model
cot = pt.tl.CinemaOT(adata)

# Run the analysis
cot.fit()
```

--------------------------------

### Verify Guide Assignment Matching

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/guide_rna_assignment.ipynb

Compares the assigned guide column with the original guide ID column to check for discrepancies.

```python
sum(gdo.obs["assigned_guide"] != gdo.obs["guide_ID"])
```

--------------------------------

### Setup and Data Loading

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/scgen_perturbation_prediction.ipynb

Import necessary libraries and load the dataset for perturbation prediction.

```python
import pertpy as pt
import scanpy as sc
import scgen

adata = pt.dt.scgen_perturbation_prediction()
```

--------------------------------

### Assign Guide RNAs to Target Sequences

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/guide_rna_assignment.ipynb

Use the guide RNA assignment functionality to map guides to their respective targets.

```python
import pertpy as pt

# Example of guide RNA assignment
# Assuming a loaded AnnData object 'adata'
# Replace 'guide_column' and 'target_column' with your actual column names
adata = pt.tl.assign_guides(adata, guide_column="guide", target_column="target")
```

--------------------------------

### CinemaOT Setup and Usage

Source: https://pertpy.readthedocs.io/en/stable/_sources/tutorials/notebooks/cinemaot.ipynb

Initial setup and basic usage of the CinemaOT library.

```python
import pertpy as pt
import scanpy as sc

# Load the data
adata = sc.read_h5ad("cinemaot_data.h5ad")

# Run CinemaOT
cinemaot = pt.tl.CinemaOT()
cinemaot.fit(adata)

# Visualize results
cinemaot.plot_results(adata)
```
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