Metadata-Version: 2.1
Name: singlecelldata
Version: 1.0.1
Summary: A python package for managing single-cell RNA-seq datasets.
Home-page: https://edwinv87.github.io/singlecelldata
Author: Edwin Vans
Author-email: vans.edw@gmail.com
License: UNKNOWN
Description: # SingleCell
        
        SingleCell is a python class available in the singlecelldata package for managing single-cell RNA-seq data. It contains three pandas dataframes; `data` for holding gene expression values (counts/normalized counts), `genedata` for holding more information about the genes e.g., gene names, and `celldata` which contains more information about cells such as cell types, labels etc.
        
        ## Installation
        
        The singlecelldata package can be easily installed using the following command:
        
        `pip install singlecelldata`
        
        ## Documentation
        
        The SingleCell class reference manual can be found [here](https://singlecelldata.readthedocs.io/en/latest/index.html)
        
        ## Using the SingleCell class
        
        ### Basic Example
        
        The SingleCell class can be used to create an object which stores single-cell gene expression data and additional data about genes and cells in their respective dataframes. To create a SingleCell object sc, the following python code can be used:
        
        ```python
        import pandas as pd
        from singlecelldata import SingleCell
        
        dataset = 'biase'
        
        data_path = "data/" + dataset + '/' + dataset + "_data.csv"
        celldata_path = "data/" + dataset + '/' + dataset + "_celldata.csv"
        genedata_path = "data/" + dataset + '/' + dataset + "_genedata.csv"
        
        # Create pandas dataframes by reading data from files
        data = pd.read_csv(data_path, index_col=0)
        celldata = pd.read_csv(celldata_path, index_col=0)
        genedata = pd.read_csv(genedata_path, index_col = 0)
        
        # Create a single cell object
        sc = SingleCell(dataset, data, celldata, genedata)
        ```
        
        In the above example, a SingleCell object, sc, was ceated by passing the dataset name and the main data, the cell data and gene data as Pandas dataframes. [Pandas](https://pandas.pydata.org/) is a powerpul python library for creating data structures from a variety of sources. Pandas can open and read data from numerous differernt file types such as csv files and creating dataframes from it. This enables the user to create SingleCell objects from a variety of different data file types.
        
        ### Detailed Example
        
        More detailed example can be found [here](https://edwinv87.github.io/singlecelldata/docs/SingleCell-Example.html)
        
        ## Contact
        
        Contact the author on <vans.edw@gmail.com> to give feedback/suggestions for further improvements and to report issues.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
