Metadata-Version: 2.1
Name: cellregmap
Version: 0.0.3
Summary: A linear mixed model framework to map multivariate context-specific eQTL using single-cell RNA-seq data.
Home-page: https://github.com/limix/CellRegMap
Author: Anna Cuomo, Danilo Horta
Author-email: acuomo@ebi.ac.uk
Maintainer: Danilo Horta
Maintainer-email: horta@ebi.ac.uk
License: MIT
Download-URL: https://github.com/limix/CellRegMap
Description: # CellRegMap
        
        Cellular Regulatory Map (CellRegMap) is a linear mixed model approach to perform multi-context eQTL mapping by leveraging single cell RNA sequencing (scRNA-seq) data.
        It is related to the previously proposed [StructLMM](https://www.nature.com/articles/s41588-018-0271-0) but importantly it can account for sample structure, including population structure and repeated observations for the same samples, e.g., multiple cells for the same donor.
        
        The CellRegMap model and its applications to both real and simulated data are described in the [CellRegMap manuscript](https://www.biorxiv.org/content/10.1101/2021.09.01.458524v1).
        
        We are working on more instructions and tutorials to facilitate usage of the package at [this link](https://limix.github.io/CellRegMap/)!
        
        ## Install
        
        From your command line, enter
        
            python3 -m pip install cellregmap
        
        in your command line.
        
        ## Development
        
        To install it in development mode, enter
        
            git clone https://github.com/limix/CellRegMap.git
            cd CellRegMap
            python3 -m pip install -e .
        
        in your command line.
        
        ## Running tests
        
        From your command line, enter
        
            python3 setup.py test
        <!-- 
        ## Project layout
        
            ├─ old_files/       old scripts
            ├─ references/      documents on the mathematical concepts
            └─ CellRegMap/      package implementation
               └─ test/         test file
        
        ## References
        
        - [Exploring Multivariate Gene-Environment Interactions: Models And Applications](https://www.repository.cam.ac.uk/handle/1810/290971)
        - [Optimal tests for rare variant effects in sequencing association studies](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3440237/) [Supplementary material](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3440237/bin/supp_kxs014_kxs014supp.pdf) -->
        
Keywords: scRNA-seq,eQTL,context-specific regulation
Platform: Windows
Platform: MacOS
Platform: Linux
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Requires-Python: >=3.6
Description-Content-Type: text/markdown
