map2bf.mavedb: Calibrate a variant map from MaveDB to Bayes Factors
In jweile/maveclin: Clinical predictions for MaveDB

Description Usage Arguments Value Examples

Calibrate a variant map from MaveDB to Bayes Factors

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map2bf.mavedb(ssid, ensembls, symbols, drawPlot = TRUE, minMaf = 0,
  flip = FALSE, homozygous = FALSE, overrideCache = FALSE,
  logger = NULL)

`ssid`	the scoreset id (URN) from MaveDB
`ensembls`	a vector of ensembl IDs for the target gene
`symbols`	a vector of gene symbols of the target gene
`drawPlot`	boolean value indicating whether a plot of variant distributions should be drawn. Defaults to `TRUE`.
`minMaf`	the minimum Minor Allele Frequency required for variants to be considered benign
`flip`	logical; whether to apply the flip transformation to the scores
`homozygous`	logical; filter benign variants to only those occuring homozygously.
`overrideCache`	logical; whether to override local cache.
`logger`	a yogilogger object to which to write log messages.

a data.frame containing the original scores input with an additional column llr, representing the log likelihood ratio (i.e. log Bayes Factor)

maveUrn <- "urn:mavedb:00000001-c-2"
ensembls <- c("ENSG00000198668","ENSG00000143933","ENSG00000160014")
symbols <- c("CALM1","CALM2","CALM3")
calmBFs <- map2bf.mavedb(maveUrn,ensembls,symbols)