Metadata-Version: 2.1
Name: MiScan
Version: 1.0.0
Summary: Maxout-inferred SNV-based cancer prediction model
Home-page: UNKNOWN
Author: Qulab USTC
Author-email: jeffery_cpu@163.com
License: UNKNOWN
Project-URL: MiScan website, http://galaxy.ustc.edu.cn
Description: # MiScan
        
        Maxout-inferred SNV-based cancer prediction model | Apache Software License
        
        
        
        # Tutorial
        
        ### Dependency data download
        
        &emsp;&emsp;To predict breast cancer risk with MiScan, Users firstly needs to do:
        
        - VCF Files
        
          We recommend using whole exon sequencing data to obtain individual variation
          information, but the results of whole genome sequencing and full-length RNA-seq
          data are also compatible with the model. Please download test VCF files from [FTP](http://galaxy.ustc.edu.cn:30803/liunianping/miscan/miscan_test_data/)
        
        - Maxout model weight
        
          Users also need a MiScan model weight to perform prediction, well-trained model weight can be downloaded from [here](http://galaxy.ustc.edu.cn:30803/liunianping/miscan/miscan_model/) 
        
        ### installation
        
        - install through `pip`
        
          for linux or Mac OS user, MiScan can be installed easily using `pip`
        
        ```bash
        pip install MiScan -i https://pypi.python.org/pypi
        ```
        
        - install through docker
        
          for windows user, we provide a Docker version for convenient.
        
        ```bash
        docker pull jefferyustc/miscan_command_line:v0.2.1
        docker run --name miscan_cli_test -it -v /path/to/data:/path/in/docker 9fd
        ```
        
        &emsp;&emsp;More over, `Docker File`is available in the project directory, build it youself if you'd like to.
        
        ### usage-commandline
        
        Suppose your VCF file and weight are placed in the `$dir` directory.
        
        ```bash
        MiScan --vcf $dir/SRR5447191.combined.filtered.vcf -o outputs --weight $dir/_MiScan_weights.hdf5
        ```
        
        or with below command:
        
        ```bash
        python -m MiScan --vcf $dir/SRR5447191.combined.filtered.vcf -o outputs --weight $dir/_MiScan_weights.hdf5
        ```
        
        if with docker, the path of VCF file or weight path shoule be path in Docker environment:
        
        ```bash
        MiScan -o test_outputs --vcf $dir_in_docker/SRR5447191.combined.filtered.vcf --weight $dir_in_docker/_MiScan_weights.hdf5
        ```
        
        
        
        ### usage-script
        
        ```python
        from MiScan import miscan_main
        
        miscan_main(
            outDir='./outputs',
            inVcf='/Users/jeffery/Downloads/SRR5447191.combined.filtered.vcf',
            model_weight='/Users/jeffery/workspace/projects/outputs/_MiScan_weights.hdf5'
        )
        ```
        
        
Keywords: deep learning SNV breast cancer prediction
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Natural Language :: English
Requires-Python: >=3.4
Description-Content-Type: text/markdown
