Credible-Set Construction And Reporting

How credible sets are built from a fit and which of them are reported. Every field is read by postprocessFinemappingFits, so these can be changed and a stored fit re-summarized without refitting.

Usage

csCoverage(x, ...)

csCoverage(x, ...) <- value

secondaryCoverage(x, ...)

secondaryCoverage(x, ...) <- value

signalCutoff(x, ...)

signalCutoff(x, ...) <- value

minAbsCorr(x, ...)

minAbsCorr(x, ...) <- value

medianAbsCorr(x, ...)

medianAbsCorr(x, ...) <- value

includeAllCs(x, ...)

includeAllCs(x, ...) <- value

perCsColumns(x, ...)

perCsColumns(x, ...) <- value

maxNumSingleEffects(x, ...)

maxNumSingleEffectsGreedy(x, ...)

CredibleSetParam(
  coverage = 0.95,
  secondaryCoverage = c(0.7, 0.5),
  signalCutoff = 0.025,
  minAbsCorr = 0.8,
  medianAbsCorr = NULL,
  includeAllCs = FALSE,
  perCsColumns = c("none", "alpha", "full"),
  maxNumSingleEffects = 10L,
  maxNumSingleEffectsGreedy = NULL
)

# S4 method for class 'CredibleSetParam'
csCoverage(x)

# S4 method for class 'CredibleSetParam'
csCoverage(x) <- value

# S4 method for class 'CredibleSetParam'
secondaryCoverage(x)

# S4 method for class 'CredibleSetParam'
secondaryCoverage(x) <- value

# S4 method for class 'CredibleSetParam'
signalCutoff(x)

# S4 method for class 'CredibleSetParam'
signalCutoff(x) <- value

# S4 method for class 'CredibleSetParam'
minAbsCorr(x)

# S4 method for class 'CredibleSetParam'
minAbsCorr(x) <- value

# S4 method for class 'CredibleSetParam'
medianAbsCorr(x)

# S4 method for class 'CredibleSetParam'
medianAbsCorr(x) <- value

# S4 method for class 'CredibleSetParam'
includeAllCs(x)

# S4 method for class 'CredibleSetParam'
includeAllCs(x) <- value

# S4 method for class 'CredibleSetParam'
perCsColumns(x)

# S4 method for class 'CredibleSetParam'
perCsColumns(x) <- value

# S4 method for class 'CredibleSetParam'
maxNumSingleEffects(x)

# S4 method for class 'CredibleSetParam'
maxNumSingleEffectsGreedy(x)

Arguments

x: A CredibleSetParam.
...: Unused, present for generic consistency.
value: The replacement value for that setting.
coverage: Primary credible-set coverage. Default 0.95.
secondaryCoverage: Additional coverages to report credible sets at. Default c(0.7, 0.5).
signalCutoff: PIP cutoff for including a non-credible-set variant in the top-loci table. Default 0.025.
minAbsCorr: Minimum absolute within-set correlation for purity. Default 0.8.
medianAbsCorr: Median absolute within-set correlation threshold, or NULL (default) to judge purity on minAbsCorr alone.
includeAllCs: Logical. Report every credible set rather than only the top one. Default FALSE.
perCsColumns: Which per-credible-set variant-level columns are added to the topLoci table. "none" (default) adds only the always-on scalar within_cs_pip; "alpha" also widens alpha into one within_cs_pip_<lab> column per set; "full" additionally widens cs_logbf_, cs_effect_ and cs_effect_var_. includeAllCs decides the <lab> in those names. This governs the table; the stored fit is governed by fitRetention.
maxNumSingleEffects: Integer. Maximum number of single effects the fit may carry, and so the maximum number of credible sets that can exist. Default 10. Seeded onto every SuSiE-family token in methods that did not set it through FineMappingMethodsParam.
maxNumSingleEffectsGreedy: Integer or NULL. Maximum number of single effects for the greedy initialization stage, where the engine has one. NULL (the default) leaves the engine's own default in place.

Value

CredibleSetParam returns a CredibleSetParam object, a MethodParam. Each accessor returns that setting's value; each replacement form returns a modified copy. maxNumSingleEffects and maxNumSingleEffectsGreedy have no replacement form: they are seeded onto the fitting tokens, so changing one needs a refit rather than a re-summary.

Examples

CredibleSetParam(coverage = 0.9, includeAllCs = TRUE)
#> <CredibleSetParam>
#>   coverage                 0.9
#>   secondaryCoverage        0.7, 0.5
#>   signalCutoff             0.025
#>   minAbsCorr               0.8
#>   includeAllCs             TRUE
#>   perCsColumns             none
#>   maxNumSingleEffects      10
#>   unset: medianAbsCorr, maxNumSingleEffectsGreedy