Inline GWAS Fine-Mapping Settings

How colocPipeline fine-maps gwasInput when it is summary statistics rather than an existing fine-mapping result. Every field is forwarded to fineMappingPipeline; the settings that pipeline exposes but that cannot apply here are deliberately absent: fineMappingResult (the pipeline is being asked to produce one), crossValidationParam (refused on summary statistics) and residualizationParam (nothing to regress out).

The whole bundle is inert when gwasInput is already a fine-mapping result, since no fit is run.

Usage

fineMappingMethods(x, ...)

fineMappingMethods(x, ...) <- value

credibleSetParam(x, ...)

credibleSetParam(x, ...) <- value

susieRssParam(x, ...)

susieRssParam(x, ...) <- value

panelFilterParam(x, ...)

panelFilterParam(x, ...) <- value

initializeWithSusieInf(x, ...)

initializeWithSusieInf(x, ...) <- value

fitRetention(x, ...)

fitRetention(x, ...) <- value

GwasFineMappingParam(
  methods = "susie",
  credibleSetParam = CredibleSetParam(),
  susieRssParam = SusieRssParam(),
  panelFilterParam = PanelFilterParam(),
  initializeWithSusieInf = TRUE,
  fitRetention = c("slim", "full")
)

# S4 method for class 'GwasFineMappingParam'
fineMappingMethods(x)

# S4 method for class 'GwasFineMappingParam'
fineMappingMethods(x) <- value

# S4 method for class 'GwasFineMappingParam'
credibleSetParam(x)

# S4 method for class 'GwasFineMappingParam'
credibleSetParam(x) <- value

# S4 method for class 'GwasFineMappingParam'
susieRssParam(x)

# S4 method for class 'GwasFineMappingParam'
susieRssParam(x) <- value

# S4 method for class 'GwasFineMappingParam'
panelFilterParam(x)

# S4 method for class 'GwasFineMappingParam'
panelFilterParam(x) <- value

# S4 method for class 'GwasFineMappingParam'
initializeWithSusieInf(x)

# S4 method for class 'GwasFineMappingParam'
initializeWithSusieInf(x) <- value

# S4 method for class 'GwasFineMappingParam'
fitRetention(x)

# S4 method for class 'GwasFineMappingParam'
fitRetention(x) <- value

Arguments

x

A GwasFineMappingParam.

...

Unused, present for generic consistency.

value

The replacement value for that setting.

methods

Fine-mapping methods, as a character vector or a FineMappingMethodsParam record. Default "susie".

credibleSetParam

How credible sets are built, built with CredibleSetParam. coverage and L matter most here: they decide the sets whose log Bayes factors coloc scores, so leaving them at the defaults while the QTL side used something else compares two differently-built sets.

susieRssParam

The summary-statistics solver, built with SusieRssParam — serFallback, rMismatch, rFinite and the susie_rss control list. What a GWAS block with an imperfect LD panel needs.

panelFilterParam

LD-reference-panel filters, built with PanelFilterParam.

initializeWithSusieInf

Logical. Chain a SuSiE-inf fit, when methods asks for susieInf alongside susie. Default TRUE.

fitRetention

How much of each fit is kept: "slim" (default) or "full". Only observable when returnGwasFineMapping = TRUE, which is when the fine-mapping result is handed back for other uses.

Value

GwasFineMappingParam returns a GwasFineMappingParam object, a MethodParam. Each accessor returns that setting's value — for the three nested bundles, the MethodParam itself — and each replacement form returns a modified copy.

Examples

GwasFineMappingParam(
    credibleSetParam = CredibleSetParam(coverage = 0.9)
)
#> <GwasFineMappingParam>
#>   methods                  susie
#>   credibleSetParam         coverage, secondaryCoverage, signalCutoff, minAbsCorr, includeAllCs, perCsColumns, maxNumSingleEffects
#>   susieRssParam            serFallback, keepFullFit, rMismatch
#>   panelFilterParam         mafCutoff, macCutoff, imissCutoff
#>   initializeWithSusieInf   TRUE
#>   fitRetention             slim