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Read Published TWAS Weights

Source: R/resultReaders.R
readTwasWeights.Rd

Rebuild a TwasWeights from a file exportToBed or exportToVcf wrote, or from any file in the same vocabulary.

A merged table reads back as a multi-row collection, one row per (study, context, trait, method) tuple. A fitted model whose weights were a MATRIX – a joint fit, one column per member – was published as one block per member with trait naming it, so it reads back as one row per member with joint_traits keeping the membership. The weights are identical either way; only the packing differs.

Usage

readTwasWeights(
  path,
  region = NULL,
  format = c("auto", "bed", "vcf"),
  studyName = NULL,
  context = NULL,
  trait = NULL,
  method = NULL,
  dataType = NULL,
  weightStandardized = NULL,
  sampleSelect = NULL
)

Arguments

path

Path to the published file. Bgzipped and tabix-indexed files can be read by region.

region

Optional region to restrict the read to – a "chr:start-end" string, a GRanges, or a one-row data.frame with chrom/start/end. Ignored with a warning when the file is not tabix-indexed.

format

"auto" (default) reads a .vcf / .bcf path as a VCF and anything else as a published table; "bed" / "vcf" say so explicitly for a file named otherwise.

studyName, context, trait, method

Identity values for a file that did not record them. Each FILLS IN the corresponding column when the file lacks it; a value that disagrees with what the file does record is an error rather than a silent override.

dataType

Optional assay / modality label, same fill-in rule.

weightStandardized

Whether the published weights are on the standardized genotype scale. Required when the file does not record it: the scale is not recoverable from the weights themselves.

sampleSelect

For a multi-sample VCF, which samples to read. Each sample is one fitted model. Defaults to all of them.

Value

A TwasWeights.

What is required, and what is not

Variant ids that encode coordinates (or the columns to build them from) and a WGT column – a weight is the whole content of a TwasWeights. The four identity axes must be recorded or supplied, because the collection is keyed by them. Everything else is optional and carried through if present.

Cross-validation metrics are never published (they describe a model scored on held-out folds, which is not per-variant and not data-secure to express per sample), so a read-back collection has no cvResult and no fitted models.

See also

exportToBed, readFineMappingResult

Examples

data(twasWeightsExample)
path <- file.path(tempdir(), "weights.bed")
exportToBed(twasWeightsExample, path)
#> exportToBed: skipping 2 fine-mapping-derived row(s) (susie, susie_inf). Those weights are the fine-mapping posterior re-expressed -- export the fine-mapping result instead, which carries the posterior, its standard error and the credible sets.
readTwasWeights(path)
#> TwasWeights: 9 entries
#>   1 studies, 1 contexts, 1 traits, 9 methods
#>   LD reference: NULL (individual-level fit)