This vignette documents the left sidepanel controls in the Viewer and how they interact.
One important sidepanel dependency is the detected data mode. The
bundled lc500s example is in summary mode and includes
precomputed clustering results:
summaryStudyPath <- system.file("example", "st", "lc500s", package = "CohortContrast")
# Summary studies expose the available cluster counts up front.
CohortContrast::checkDataMode(summaryStudyPath)[c("mode", "has_clustering", "clusterKValues")]
#> $mode
#> [1] "summary"
#>
#> $has_clustering
#> [1] TRUE
#>
#> $clusterKValues
#> [1] 2 3 4 5This is why controls such as cluster count selection and summary-mode filtering can be enabled immediately when the study is loaded.
Most sidepanel inputs are staged until you click Apply Filters.
Show checkbox edits made in the Dashboard
table.Domain-family include/exclude control.
Range filter on target cohort prevalence.
TARGET_SUBJECT_PREVALENCE_PCT
inside the selected range.Range filter on contrast effect size.
PREVALENCE_DIFFERENCE_RATIO_DISPLAY
inside the selected range.Toggles whether ordinal rows are shown.
Minimum prevalence threshold within the currently selected cluster view.
C1, C2, …).All.Keeps only the top N main concepts with highest prevalence SD across clusters.
0 disables this filter.Optional cluster subset used by Top N by SD ranking.
Selects cluster count (Auto, 2,
3, 4, 5).
Controls whether clustering uses:
All conceptsActive concepts onlyOnly relevant in patient mode; visually disabled in summary mode.
_show from filter criteria.Recluster is enabled.All concepts vs
Active concepts only) is active.Recluster is disabled.Show values manually.