Last pca process

[birsenyrtds]

Single-Cell PCA Toolkit
🔬 A Python toolkit for PCA analysis of single-cell RNA-seq data using Scanpy. Streamlines preprocessing, dimensionality reduction, and visualization for AnnData objects.

Key Features
🛠️ Automated PCA Pipeline: Normalization → Log Transformation → Scaling → PCA

📊 Visualization Tools: PCA scatter plots (with custom coloring) + explained variance plots

💾 HDF5 Integration: Save/load results in .h5ad format (AnnData native)

⚙️ Configurable: Adjust components (n_comps), solvers (svd_solver='arpack'), and plotting styles

Tech Stack
scanpy (single-cell analysis)

matplotlib (visualization)

anndata (data structure)

Quick Start
python
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import scanpy as sc
from pca_toolkit import run_pca, plot_pca, plot_variance

adata = sc.read("your_data.h5ad") # Load dataset
run_pca(adata, n_comps=50) # Run PCA
plot_pca(adata, color="louvain") # Plot by cluster
plot_variance(adata) # Variance ratios
📌 Ideal for:

Exploratory single-cell analysis

Batch effect visualization

Dimensionality reduction benchmarks

📜 License: MIT (or specify your license)

Demo results: