Load a MultiStudyQtlDataset from manifests

Build a MultiStudyQtlDataset from a QtlDataset manifest (individual-level studies) and, optionally, a QtlSumStats manifest (summary-only studies).

Usage

loadMultiStudyQtlDatasetFromManifest(
  qtlDatasetsManifest,
  sumStatsManifest = NULL,
  genome = NULL,
  ldReference = NULL,
  region = NULL,
  minLdOverlapWarn = 0.5,
  columnMapping = NULL,
  sampleSelect = NULL,
  formatMapping = NULL,
  transposeCovariates = FALSE,
  scaleResiduals = TRUE,
  genotypeFilterParam = GenotypeFilterParam()
)

Arguments

qtlDatasetsManifest

A data.frame or path. The QtlDataset schema with study and genotypePath mandatory (grouping key = study); one QtlDataset is built per study group.

sumStatsManifest

Optional QtlSumStats manifest (see loadQtlSumStatsFromManifest).

genome, ldReference, region, minLdOverlapWarn

Passed to the QtlSumStats loader for sumStatsManifest.

columnMapping, sampleSelect, formatMapping

Passed to the QtlSumStats loader for sumStatsManifest.

transposeCovariates

Transpose covariate TSVs (QTLtools layout).

scaleResiduals

Pass-through QtlDataset argument, applied to every study.

genotypeFilterParam

Pass-through QtlDataset filtering options, built with GenotypeFilterParam and applied to every study.

Value

A MultiStudyQtlDataset object.

Examples

d <- system.file("extdata", "qtl_mini", package = "pecotmr")
manifest <- data.frame(study = c("s1", "s2"), context = "brain",
  phenotypePath = file.path(d, "example_geneexpr.bed.gz"),
  genotypePath = file.path(d, "example.chr22"))
loadMultiStudyQtlDatasetFromManifest(qtlDatasetsManifest = manifest)
#> MultiStudyQtlDataset: 2 individual-level + 0 sumstats studies
#>   Individual-level studies: s1, s2