Create a GwasFineMappingResult Collection

Construct a GwasFineMappingResult collection from per-(study, method) tuples and a list of FineMappingRow payloads. The collection can represent either a single LD block (one row per (study, method)) or a genome-wide sweep across blocks (multiple rows per (study, method), each covering its own genomic range).

Rows are identified by (study, method) plus the element's own range, which is derived from the variants rather than stored, so it cannot drift out of step with them and stays correct after subsetRegion.

Usage

GwasFineMappingResult(
  study,
  method,
  entry,
  blockId = NULL,
  traitPos = NULL,
  ldSketch = NULL
)

Arguments

study

Character vector of study identifiers (per tuple).

method

Character vector of fine-mapping method names (per tuple).

entry

List / SimpleList of FineMappingRow objects.

blockId

Optional character vector (per tuple) keying the external LD block manifest, e.g. "chr22_10516173_17414263". Provenance only, not part of the identity key. Supply it when the block BOUNDARIES matter: those are the one thing not recoverable from the variants, since adjacent blocks' spans leave gaps.

traitPos

Optional per-row trait genomic anchor (a GRanges or NULL), carried forward as provenance; not part of the identity key. NULL (default) omits the column.

ldSketch

An optional genotype panel (see readGenotypes).

Value

A GwasFineMappingResult object.

Examples

tl <- data.frame(variant_id = paste0("chr1:", 100 * 1:3, ":A:G"),
  pip = c(0.9, 0.5, 0.1), cs = c(1L, 1L, NA))
fe <- fineMappingRow(
  variantIds = tl$variant_id, susieFit = list(), topLoci = tl)
GwasFineMappingResult(study = "t1", method = "susie", entry = list(fe))
#> GwasFineMappingResult: 1 entries
#>   1 studies, 1 methods
#>   LD sketch: NULL