##' Compare the LL for separated or merged model
##'
##' Calcualte LL for each treatment and merginalized data, and see the difference
##' @title calculateLLDiff
##' @param treatment1 character, first treatment
##' @param treatment2 character, second treatment
##' @param gene.vec character vec, gene names used in this comparison
##' @param ptcomp.df data frame, contain expression and annotation
##' @return diff.ll.df data frame, gene name, treatment1 ll, treatment2 ll, merged ll
##' @author Yasuhiro Kojima
##' @export
calculateLLDiff <- function(treatment1, treatment2, gene.vec, ptcomp.df, sparse.gp.res = 20){
tr.gp.df.list <- purrr::map(
list(tr1 = treatment1, tr2 = treatment2, merge = c(treatment1, treatment2)),
function(treatment){
calculateGPDf(
gene.vec,
dplyr::filter(ptcomp.df, treatment %in% !!treatment),
sparse.gp.res = sparse.gp.res)
})
dplyr::inner_join(
tr.gp.df.list$tr1,
tr.gp.df.list$tr2,
by = "gene",
suffix = c(".tr1", ".tr2")) %>%
dplyr::inner_join(
tr.gp.df.list$merge) %>%
dplyr::select(gene, ll.tr1, ll.tr2, ll) %>%
dplyr::mutate(diff.ll = ll.tr1 + ll.tr2 - ll)
}
##' Permutate treatment labels
##'
##' @title permutateTreatment
##' @param ptcomp.df data frame, contain expression and annotation
##' @return permutated.ptcomp.df data frame, contain expression and annotation
##' @author Yasuhir Kojima
##' @export
permutateTreatment <- function(ptcomp.df){
ptcomp.df$treatment <- sample(ptcomp.df$treatment)
ptcomp.df
}
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