Goal | Package versions used for the wiki page | Required environment variables | Connect to the OMOP database | Define the observation windows | Identify eligible ICD10 three-digit codes | Helper for clean study names | Build the target cohort | Build the visit-based control cohort | Keep only the final selected concepts | Run one ICD10 code and one observation window | Run the full atlas generation loop | Resulting output folders
Package: CohortContrast 1.0.0
Markus Haug
CohortContrast: Enrichment Analysis of Clinically Relevant Concepts in Common Data Model Cohort Data
Identifies clinically relevant concepts in Observational Medical Outcomes Partnership Common Data Model cohorts using an enrichment-based workflow. Defines target and control cohorts and extracts medical interventions that are over-represented in the target cohort during the observation period. Users can tune filtering and selection thresholds. The workflow includes chi-squared tests for two proportions with Yates continuity correction, logistic tests, and hierarchy and correlation mappings for relevant concepts. The results can be optionally explored using the bundled graphical user interface. For workflow details and examples, see <https://healthinformaticsut.github.io/CohortContrast/>.
Authors:
CohortContrast_1.0.0.tar.gz
CohortContrast_1.0.0.zip(r-4.7-any)CohortContrast_1.0.0.zip(r-4.6-any)CohortContrast_1.0.0.zip(r-4.5-any)
CohortContrast_1.0.0.tgz(r-4.6-any)CohortContrast_1.0.0.tgz(r-4.5-any)
CohortContrast_1.0.0.tar.gz(r-4.7-any)CohortContrast_1.0.0.tar.gz(r-4.6-any)
CohortContrast_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CohortContrast/json (API)
| # Install 'CohortContrast' in R: |
| install.packages('CohortContrast', repos = c('https://healthinformaticsut.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/healthinformaticsut/cohortcontrast/issues
Pkgdown/docs site:https://healthinformaticsut.github.io
Last updated from:658d6971d9. Checks:7 NOTE, 2 OK. Indexed: yes.
The latest version of this package failed to build. Look at thebuild logs for more information.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | NOTE | 158 | ||
| source / vignettes | OK | 225 | ||
| linux-release | NOTE | 163 | ||
| macos-release | NOTE | 153 | ||
| macos-oldrel | NOTE | 175 | ||
| windows-devel | NOTE | 113 | ||
| windows-release | NOTE | 112 | ||
| windows-oldrel | NOTE | 85 | ||
| wasm-release | OK | 139 |
Exports:automaticCorrelationCombineConceptsautomaticHierarchyCombineConceptscheckDataModecheckPythonDepsCohortContrastcohortFromCohortTablecohortFromCSVcohortFromDataTablecohortFromJSONconfigurePythoncreateControlCohortInversecreateControlCohortMatchinggenerateMappingTablegetPythonInfogetTopSeparatingConceptsinstallPythonDepsinstallPythonDepsOfflineloadCohortContrastStudymatchCohortsByAgenGramClusterSummarizationnGramDiscoveryprecomputeSummaryremoveTemporalBiasresolveCohortTableOverlapsrunCohortContrastViewerstopCohortContrastViewer
Dependencies:askpassbackportsbitbit64blobCDMConnectorcheckmateclicliprclockCodelistGeneratorcodetoolsCohortConstructorcpp11crayoncurldata.tableDBIdbplyrdoParalleldplyrforeachgenericsgluehmshttr2iteratorsjsonlitelifecyclelubridatemagrittrnanoparquetomopgenericsopensslPatientProfilespillarpkgconfigprettyunitsprogresspurrrR6readrrlangsnakecasestringistringrsystibbletidyrtidyselecttimechangetzdbutf8vctrsvroomwithr
ICD10 Atlas Generation
Last update: 2026-08-25
Started: 2026-04-22
Setup
Introduction | Installation | Load packages | Initiating database connection | Configuring Python dependencies (for GUI and summary precompute) | Air-gapped server setup | Building a target cohort | 1. Target cohort from OHDSI OMOP database. | 2. Target cohort from JSON description file. | 3. Target cohort from a CSV file. | 4. Target cohort from a table | Building a control cohort | 1. Control cohort based on matches | 2. Control cohort based on inverse controls | Other considerations
Last update: 2026-07-14
Started: 2024-12-17
Article Case Study Generation
Goal | Expected JSON layout | Notes | Package versions used for the wiki page | Required environment variables | Connect to the OMOP database | Define study cases | Build the target cohort | Build the visit-based control cohort | Keep only the final selected concepts | Run one final mapped study | Run all configured cases | Resulting study folders
Last update: 2026-07-14
Started: 2026-04-22
Air-gapped Server Setup
Scope | What differs in air-gapped environments | Offline setup workflow | 1. Prepare wheels on a connected machine | 2. Transfer wheels to the air-gapped server | 3. Configure Python in R | 4. Install dependencies from local wheels | 5. Validate before production usage | Offline smoke test | Summary precompute | GUI in server context | Runtime mode guidance for servers | Common failures and fixes | Minimal offline checklist
Last update: 2026-04-09
Started: 2026-03-17
Dashboard Composite Plot
Introduction | What the composite shows | How to use it | Interpretation guidance
Last update: 2026-04-09
Started: 2026-03-17
Demographics Tab
Introduction | Components | Controls | Patient vs Summary mode behavior | Interpretation
Last update: 2026-04-09
Started: 2026-03-17
Execution
Executing the study | The parameters | Mandatory: | Customization: | Notes: | Reloading a saved study
Last update: 2026-04-09
Started: 2024-12-17
Graphical User Interface
Introduction | Select a study and mode | Main workflow in the UI | Tabs | Mappings overview
Last update: 2026-04-09
Started: 2025-01-10
Mappings Tab
Introduction | Manual Merge | Hierarchy Suggestions | Correlation Suggestions | Mapping History
Last update: 2026-04-09
Started: 2026-03-17
Overlap Tab
Introduction | Components | Interpretation
Last update: 2026-04-09
Started: 2026-03-17
Patient vs Summary Mode
Introduction | How each mode is produced | What is different in the UI | Recommended usage
Last update: 2026-04-09
Started: 2026-03-17
Sidepanel Filters and Controls
Introduction | Important model: staged vs applied | Action buttons | Apply Filters | Apply Table Selection | Recluster | Sidepanel controls | Heritage Types | Target Prevalence (%) | Prevalence Difference Ratio | Show ordinal data rows for active main concepts | Cluster Prevalence (%) | Top N Concepts by SD (across clusters) | Divergence Cluster Scope | Clusters | Clustering scope | Override and precedence rules | Mode-specific behavior | Patient mode | Summary mode | Recommended operating sequence
Last update: 2026-04-09
Started: 2026-03-17
Trajectories Tab
Introduction | Controls | Interpretation
Last update: 2026-04-09
Started: 2026-03-17
Interpreting Results with lc500
Goal | Object Overview | data_initial | data_person | data_features | data_patients | complementaryMappingTable | selectedFeatureData | selectedFeatureData$selectedFeatureNames preview | selectedFeatureData$selectedFeatureIds preview | selectedFeatureData$selectedFeatures | conceptsData | conceptsData$concept_ancestor | conceptsData$concept | config | config$metadata scalar fields preview
Last update: 2026-04-02
Started: 2026-04-02
Interpreting Summary Results with lc500s
Goal | Summary Folder Metadata (metadata.json) | concept_summaries.parquet | ordinal_summaries.parquet | clustering_k*_summary.parquet | clustering_k2_summary.parquet | clustering_k3_summary.parquet | clustering_k4_summary.parquet | clustering_k5_summary.parquet | clustering_k*_pairwise_overlap.parquet | clustering_k2_pairwise_overlap.parquet | clustering_k3_pairwise_overlap.parquet | clustering_k4_pairwise_overlap.parquet | clustering_k5_pairwise_overlap.parquet | complementaryMappingTable.parquet
Last update: 2026-04-02
Started: 2026-04-02
