## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" ) ## ----summix example----------------------------------------------------------- library(Summix) # load the data data("ancestryData") # Estimate 5 reference ancestry proportion values for the gnomAD African/African American group # using a starting guess of .2 for each ancestry proportion. summix(data = ancestryData, reference=c("reference_AF_afr", "reference_AF_eas", "reference_AF_eur", "reference_AF_iam", "reference_AF_sas"), observed="gnomad_AF_afr", pi.start = c(.2, .2, .2, .2, .2), goodness.of.fit=TRUE) ## ----adjAF example------------------------------------------------------------ library(Summix) # load the data data("ancestryData") adjusted_data<-adjAF(data = ancestryData, reference = c("reference_AF_afr", "reference_AF_eur"), observed = "gnomad_AF_afr", pi.target = c(1, 0), pi.observed = c(.85, .15), adj_method = 'average', N_reference = c(704,741), N_observed = 20744, filter = TRUE) print(adjusted_data$adjusted.AF[1:5,]) ## ----summix_local example----------------------------------------------------- library(Summix) # load the data data("ancestryData") results <- summix_local(data = ancestryData, reference = c("reference_AF_afr", "reference_AF_eas", "reference_AF_eur", "reference_AF_iam", "reference_AF_sas"), NSimRef = c(704,787,741,47,545), observed="gnomad_AF_afr", goodness.of.fit = T, type = "variants", algorithm = "fastcatch", minVariants = 150, maxVariants = 250, maxStepSize = 1000, diffThreshold = .02, override_fit = F, override_removeSmallAnc = TRUE, selection_scan = F, position_col = "POS") print(results$results)