Metadata-Version: 2.1
Name: rtg_score
Version: 0.1.0
Summary: Analysis of confounders by Rank-to-Group scores
Home-page: UNKNOWN
Author: Alex Rogozhnikov, System1 Biosciences
License: UNKNOWN
Description: # Rank-To-Group (RTG) score evaluates contribution of confounders
        
        <img src="example/confounder_contribution.png" width="400" />
        
        Batch, cell line, donor, plate, reprogramming, protocol — these and other confounding factors influence cell cultures *in vitro*.
        
        RTG score tracks contribution of different factors to variability by estimating how **R**ank maps **T**o **G**roup. 
        Scoring relies on ranking by similarity, so there are no explicit or implicit assumptions of linearity.
        
        RTG perfectly works with both well-interpretable data (gene expressions, cell types) 
        and embeddings provided by deep learning.
        
        ## Usage 
        
        `rtg_score` is python package. Installation:
        ```bash
        pip install rtg_score
        ```
        
        RTG score requires two DataFrames: one with confounds and ane with embeddings (or other features, e.g. gene expressions)
        ```python
        from rtg_score import compute_RTG_score
        # following code corresponds to computing element of the figure above
        # 
        score = compute_RTG_score(
            metadata=confounders_metadata,
            include_confounders=['batch', 'donor'],
            exclude_confounders=['organoid_id'],
            embeddings=qpcr_delta_ct, 
        )
        ```
        
        An example of code to compute and plot table above is available in [`example`](https://github.com/System1Bio/rtg_score/blob/master/example/Example_qPCR.ipynb) subfolder.
        
        
        
        
              
Keywords: variability analysis,variability decomposition,contributing factors
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3 
Description-Content-Type: text/markdown
