plot_adverse_events(): Lollipop chart of adverse events ranked by log-likelihood ratio.plot_interactions(): Circular network graph of protein interaction partners.plot_l2g(): Horizontal bar chart of locus-to-gene prediction scores.plot_colocalisation(): Scatter plot of H4 posterior vs colocalising variant count.plot_indications(): Bar chart of drug indications colored by clinical trial stage.ggplot2 as a package dependency.chemblQuery(): Removed deprecated variantEffect, clinicalStatus; renamed clinicalPhase to clinicalStage, studyStopReason to trialWhyStopped, studyStopReasonCategories to trialStopReasonCategories.clinVarQuery(): Removed deprecated variantEffect from Evidence query.geneBurdenQuery(): Removed deprecated variantEffect from Evidence query.orphanetQuery(): Removed deprecated variantEffect from Evidence query.indicationsQuery(): Renamed maxPhaseForIndication to maxClinicalStage; replaced references with clinicalReports.knownDrugsChemblQuery(): Replaced removed knownDrugs field on Drug type with indications + clinicalReports.knownDrugsGeneQuery(): Replaced removed knownDrugs field on Target type with drugAndClinicalCandidates.geneOntologyQuery(): Renamed name to label on GeneOntologyTerm type.interactionsQuery(): Changed sourceDatabase parameter type from String to InteractionSourceEnum; fixed error when sourceDatabase is NULL (the default) by omitting it from the GraphQL variables.Following Open Targets' announcement, Open Targets Genetics has been officially merged into the Open Targets Platform API. Consequently, otargen 2.0.0 represents a complete overhaul of the package’s functionality to support this unified API endpoint and schema.
We highly recommend upgrading to otargen 2.0.0 for the best experience with the latest Open Targets Platform API.
plot_l2g function.plot_l2g() function for the cases when the disease parameter were not selected.
The previous function were plotting only top disease for one gene. The function now updated with two more parameters to expand the plot_l2g() functionality for plotting disease agnostic scenario. These two parameters are:
top_n_disease (default: 1): Determines the number of top diseases to plot for each gene, ranked by L2G score. Increase this value to include more diseases in the analysis. Use in conjunction with being disease-agnostic to dynamically select the top diseases for each gene.l2g_cutoff (default: 0.5): Sets the minimum L2G score threshold for diseases to be considered in the plot. Increasing this value can help reduce plot clutter by focusing on higher-confidence associations.variantInfo function where the wrong variable (result) was being referenced, leading to an 'object not found' error. Modified variantInfo() to correctly process the API response data. Additionally, added checks to ensure that the results are not NULL before processing, which improves the function's robustness and error handling.test plot_l2g.R test case to provide better error handling and diagnostic information. The test now uses a tryCatch block to gracefully handle errors and explicitly fail with a clear message, enhancing the reliability and maintainability of the test suite.genesForVariant() on giving an error when using rsId variants.