Package: clep
CLEP: A Hybrid Data- and Knowledge- Driven Framework for Generating Patient RepresentationsTable of ContentsGeneral InfoInstallationDocumentationInput DataUsageIssuesAcknowledgementsCitationDisclaimerGeneral InfoCLEP is a framework that contains novel methods for generating patient representations from any patient level data and its corresponding prior knowledge encoded in a knowledge graph. The framework is depicted in the graphic belowInstallationThe code can be installed fromPyPIwith:$pipinstallclepThe most recent code can be installed from the source onGitHubwith:$pipinstallgit+https://github.com/hybrid-kg/clep.gitFor developers, the repository can be cloned fromGitHuband installed in editable mode with:$gitclonehttps://github.com/hybrid-kg/clep.git
$cdclep
$pipinstall-e.DocumentationRead theofficial docsfor more information.Input Data FormatsDataSymbolSample_1Sample_2Sample_3HGNC_ID_10.3542.5681.564HGNC_ID_21.2551.2320.26452HGNC_ID_33.2561.51.5462Note:The data must be in a tab separated file format.DesignFileNameTargetSample_1AbnormalSample_2AbnormalSample_3ControlNote:The data must be in a tab separated file format.Knowledge GraphThe graph format CLEP can handle is a modified version of the Edge List Format. Which looks as follows:SourceRelationTargetHGNC_ID_1associationHGNC_ID_2HGNC_ID_2decreasesHGNC_ID_3HGNC_ID_3increasesHGNC_ID_1Note:The data must be in a tab separated file format & if your knowledge graph does not have relations between the source and the target, just populate the relation column with "No Relation".UsageNote:These are very basic commands for clep, and the detailed options for each command can be found in thedocumentationRadical SearchingThe following command finds the extreme samples with extreme feature values based on the control population.$clepsample-scoringradical-search--data<DATA_FILE>--design<DESIGN_FILE>--controlControl--threshold2.5--control_based--ret_summary--out<OUTPUT_DIR>Graph GenerationThe following command generates the patient-gene network based on the method chosen (Interaction_network).$clepembeddinggenerate-network--data<SCORED_DATA_FILE>--methodinteraction_network--ret_summary--out<OUTPUT_DIR>Knowledge Graph EmbeddingThe following command generates the embedding of the network passed to it.$clepembeddingkge--data<NETWORK_FILE>--design<DESIGN_FILE>--model_config<MODEL_CONFIG.json>--train_size0.8--validation_size0.1--out<OUTPUT_DIR>ClassificationThe following command carries out classification on the given data file for a chosen model (Elastic Net) using a chosen optimizer (Grid Search).$clepclassify--data<EMBEDDING_FILE>--modelelastic_net--optimizergrid_search--out<OUTPUT_DIR>IssuesIf you have difficulties using CLEP, please open an issue at ourGitHubrepository.AcknowledgementsCitationIf you have found CLEP useful in your work, please consider citing:CLEP: A Hybrid Data- and Knowledge- Driven Framework for Generating Patient Representations.Bharadhwaj, V. S., Ali, M., Birkenbihl, C., Mubeen, S., Lehmann, J., Hofmann-Apitius, M., Hoyt, C. T., & Domingo-Fernandez, D. (2020).bioRxiv, 2020.08.20.259226.GraphicsThe CLEP logo and framework graphic was designed by Carina Steinborn.DisclaimerCLEP is a scientific software that has been developed in an academic capacity, and thus comes with no warranty or guarantee of maintenance, support, or back-up of data.