IHC Heterogeneity Analysis
Usage
ihcheterogeneity(
data,
wholesection = NULL,
biopsy1,
biopsy2 = NULL,
biopsy3 = NULL,
biopsy4 = NULL,
biopsies = NULL,
spatial_id = NULL,
compareCompartments = FALSE,
compartmentTests = FALSE,
analysis_type = "comprehensive",
sampling_strategy = "unknown",
cv_threshold = 20,
correlation_threshold = 0.8,
show_variability_plots = FALSE,
variance_components = FALSE,
power_analysis = FALSE,
generate_recommendations = FALSE,
showSummary = FALSE,
showGlossary = FALSE
)Arguments
- data
the data as a data frame
- wholesection
Optional reference measurement for comparison with regional measurements. Can be whole section average, hotspot area, or overall tumor measurement. Leave empty for inter-regional comparison studies. Example: Ki67 proliferation index (0-100 percent), ER H-score (0-300), PR percentage (0-100 percent).
- biopsy1
Continuous biomarker measurement from first tissue region or area. Should represent same biomarker as reference measurement for heterogeneity comparison. Example: Ki67 percent from tumor periphery, ER H-score from invasive front.
- biopsy2
Second tissue region biomarker measurement for heterogeneity analysis
- biopsy3
Third tissue region biomarker measurement
- biopsy4
Fourth tissue region biomarker measurement
- biopsies
additional simulated biopsy measurements
- spatial_id
identifier for spatial regions or tissue areas (e.g., Central/Invasive, Preinvasive/Invasive)
- compareCompartments
Perform statistical comparison of heterogeneity patterns between spatial compartments. Requires spatial_id variable. Compares ICC, CV, and bias across compartments.
- compartmentTests
Perform statistical tests to determine if heterogeneity differs significantly between compartments. Uses Levene's test for variance equality and Kruskal-Wallis for distributional differences.
- analysis_type
primary focus of biopsy simulation analysis
- sampling_strategy
biopsy sampling strategy used
- cv_threshold
Coefficient of variation threshold for acceptable sampling variability. Typical clinical values: 15-25 percent for immunohistochemistry (Ki67, ER, PR), 10-20 percent for molecular assays, 20-30 percent for heterogeneous markers (HER2, PD-L1). Lower values indicate more stringent quality requirements.
- correlation_threshold
Minimum Spearman correlation between biopsy and whole section measurements. Clinical guidelines: ≥0.80 excellent agreement, ≥0.70 good agreement, ≥0.60 moderate agreement, <0.60 poor agreement. Higher values indicate better representativeness of biopsy samples.
- show_variability_plots
display plots showing sampling variability
- variance_components
perform variance component decomposition
- power_analysis
perform power analysis for sample size recommendations
- generate_recommendations
provide recommendations for optimal heterogeneity assessment strategy
- showSummary
Display natural-language summary of heterogeneity analysis results
- showGlossary
Display definitions of statistical terms (ICC, CV, correlation)
Value
A results object containing:
results$welcome | Welcome screen shown when no variables selected | ||||
results$interpretation | a html | ||||
results$report_sentences | Pre-formatted sentences ready for clinical reports and publications | ||||
results$assumptions | Analysis assumptions, data requirements, and methodological considerations | ||||
results$summary | Natural-language summary of heterogeneity analysis results | ||||
results$glossary | Definitions of key statistical terms used in the analysis | ||||
results$reproducibilitytable | Correlation and reliability metrics | ||||
results$samplingbiastable | Systematic bias assessment between methods | ||||
results$variancetable | Sources of measurement variability | ||||
results$poweranalysistable | Sample size recommendations and power calculations | ||||
results$spatialanalysistable | Variability across spatial regions | ||||
results$compartmentComparison | Statistical comparison of heterogeneity metrics between compartments | ||||
results$compartmentTests | Formal statistical tests comparing heterogeneity across compartments | ||||
results$biopsyplot | Distribution comparison across regional measurements and reference (if provided) | ||||
results$variabilityplot | Coefficient of variation by case | ||||
results$spatialplot | Spatial distribution of biomarker values |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$reproducibilitytable$asDF
as.data.frame(results$reproducibilitytable)