Metadata-Version: 2.1
Name: GenRisk
Version: 0.2.4
Summary: Comprehensive genetic risk assessment
Home-page: https://github.com/AldisiRana/genrisk
Author: Rana Aldisi
Author-email: aldisi.rana@gmail.com
License: MIT
Description: # GenRisk
        
        GenRisk is a package that implements different gene-based scoring schemes to analyze and find significant genes 
        within a phenotype in a population
        
        ## Citation
        Rana Aldisi, Emadeldin Hassanin, Sugirthan Sivalingam, Andreas Buness, Hannah Klinkhammer, Andreas Mayr, Holger Fröhlich, Peter Krawitz, Carlo Maj, GenRisk: a tool for comprehensive genetic risk modeling, Bioinformatics, Volume 38, Issue 9, 1 May 2022, Pages 2651–2653, https://doi.org/10.1093/bioinformatics/btac152
        
        ## Requirements
        * plink >= 1.9 https://www.cog-genomics.org/plink/
        * R version >= 3.6.3
        
        ## Installation
        Option 1: The latest release of ``GenRisk`` can be installed on python3+ with:
        
            $ pip install genrisk
        
        Option2: you can also install the package with the latest updates directly from `GitHub <https://github.com/AldisiRana/GenRisk>`_ with:
        
            $ pip install git+https://github.com/AldisiRana/GenRisk.git
        
        ## Usage
        
        ### Score genes
        This command calculate the gene-based scores for a given dataset.
        
        It requires plink binary files, and an annotations file that contains all information needed for the score computation.
        
            $ genrisk score-genes -a ../path/to/toy_vcf_data.tsv -o toy_genes_scores.tsv -t toy_vcf_scoring -v ID -f AF -g gene -l ALT -d RawScore
        
        * For further CLI options and parameters use --help
        
        ### Calculate p-values
        This function calculates the p-values across the genes between two given groups
            
            $ genrisk find-association -s toy_genes_scores.tsv -i info.pheno -t linear -c quan -a fdr_bh -v sex,age,bmi 
        
        * For further CLI options and parameters use --help
        
        ### Visualize
        Visualize manhatten plot and qqplot for the data.
        
            $ genrisk visualize -p logit_assoc_binary.tsv -i genes_info_ref.txt --genescol-1 genes
        
        * For further CLI options and parameters use --help
        
        ### Create model
        Create a prediction model (classifier or regressor) with given dataset
        
            $ genrisk create-model -d toy_dataset_feats.tsv -o quan_regression_model -n quan_regression_model --model-type regressor -l quan --normalize
        
        * For further CLI options and parameters use --help
        
        ### Test model
        Evaluate a prediction model with a given dataset.
        
            $ genrisk test-model --model-path regressor_model.pkl --input-file testing_dataset.tsv --model-type regressor 
            --labels-col target --samples-col IID
        * For further CLI options and parameters use --help
        
        ### Get PRS scores
        This command aquires a PGS file (provided by the user or downloaded from pgscatalog) then calculates the PRS scores for dataset.
        Note: This command is interactive.
        
            $ genrisk get-prs
        * For further CLI options and parameters use --help
        
        ### Get GBRS
        Calculate gene-based risk scores for individuals. 
        If users do not have weights for calculation, they can provide a file with the phenotype and weights will be calculated.
        
            $genrisk get-gbrs --scores-file scores_file.tsv --weights-file weights_file.tsv --weights-col zscore --sum
        * For further CLI options and parameters use --help
        
        ## Contact
        If you have any questions or problems with the tool or its installation please feel free to create an issue in the repository or contact me via email:
        aldisi.rana@gmail.com
Keywords: genetics,scoring,risk,comprehensive
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.7.5
Description-Content-Type: text/markdown
Provides-Extra: docs
