bdbe_scnorm
OfficialEfficiently standardize single-cell sequencing data for accurate analysis.
Data & Analytics#bioinformatics#data normalization#expression matrix#single-cell sequencing#python processing
Authorcas-bigdatalab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill addresses the need for reliable and bias-free single-cell sequencing data, crucial for subsequent clustering and differential expression analysis.
Core Features & Use Cases
- Single-Cell Data Standardization: Eliminates technical biases in expression matrices, ensuring robust analysis foundations.
- File Uploads: Supports popular data formats like h5ad and csv, enabling flexible data submission.
- Automated Processing: Streamlines the process with automated standardization tasks, saving valuable time and resources.
Quick Start
To preprocess single-cell sequencing data, run the following command:
python scripts/bdbe_scnorm.py --input_file input.csv --species mouse
Dependency Matrix
Required Modules
requestsjson
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: bdbe_scnorm Download link: https://github.com/cas-bigdatalab/piflow/archive/main.zip#bdbe-scnorm Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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