Metadata-Version: 2.1
Name: promid
Version: 1.1
Summary: PromID: A deep learning-based tool to identify promoters
Home-page: https://github.com/PromStudy/PromID
Author: Ramzan Umarov
Author-email: umarov256@gmail.com
License: MIT
Download-URL: https://github.com/PromStudy/PromID/archive/v1.01.tar.gz
Description: # PromID: A deep learning-based tool to identify promoters
        
        ## Installation
        PromID can be installed from the [github repository](https://github.com/PromStudy/PromID.git):
        ```sh
        git clone https://github.com/PromStudy/PromID.git
        cd PromID
        pip install .
        ```
        PromID requires ```tensorflow>=1.7.0```, the GPU version is highly recommended.
        
        ## Usage
        PromID can be run from the command line:
        ```sh
        promid -I hg19.fa -O hg19_promoters.bed
        ```
        Required parameters:
         - ```-I```: Input fasta file.
         - ```-O```: Output bed file.
        
        Optional parameters:
         - ```-D```: Minimum soft distance between the predicted TSS, defaults to 1000.
         - ```-C```: Comma separated list of chromosomes to use for promoter prediction, defaults to all.
         - ```-T1```: Decision threshold for the scan model, defaults to 0.2.
         - ```-T2```: Decision threshold for the prediction model, defaults to 0.5.
Platform: UNKNOWN
Description-Content-Type: text/markdown
Provides-Extra: gpu
Provides-Extra: cpu
