## ----packages, include=F------------------------------------------------------ library(knitr) opts_chunk$set( fig.pos = "!h", out.extra = "", fig.align = "center" ) ## ---- warning=FALSE, message=F------------------------------------------------ # For analysis library(condiments) library(slingshot) set.seed(21) ## ----------------------------------------------------------------------------- data("toy_dataset", package = "condiments") df <- toy_dataset$sd rd <- as.matrix(df[, c("Dim1", "Dim2")]) sds <- slingshot(rd, df$cl) ## ----------------------------------------------------------------------------- top_res <- topologyTest(sds = sds, conditions = df$conditions, rep = 10) knitr::kable(top_res) ## ----------------------------------------------------------------------------- top_res <- topologyTest(sds = sds, conditions = df$conditions, rep = 10, methods = c("KS_mean", "Classifier"), threshs = c(0, .01, .05, .1)) knitr::kable(top_res) ## ----------------------------------------------------------------------------- top_res <- topologyTest(sds = sds, conditions = df$conditions, rep = 10, methods = "wasserstein_permutation", args_wass = list(fast = TRUE, S = 100, iterations = 10^2)) knitr::kable(top_res) ## ---- eval = FALSE------------------------------------------------------------ # library(BiocParallel) # BPPARAM <- bpparam() # BPPARAM$progressbar <- TRUE # BPPARAM$workers <- 4 # top_res <- topologyTest(sds = sds, conditions = df$conditions, rep = 100, # parallel = TRUE, BPPARAM = BPPARAM) # knitr::kable(top_res) ## ----------------------------------------------------------------------------- prog_res <- progressionTest(sds, conditions = df$conditions) knitr::kable(prog_res) dif_res <- fateSelectionTest(sds, conditions = df$conditions) knitr::kable(dif_res) ## ----------------------------------------------------------------------------- prog_res <- progressionTest(sds, conditions = df$conditions, method = "Classifier") knitr::kable(prog_res) dif_res <- fateSelectionTest(sds, conditions = df$conditions, thresh = .05) knitr::kable(dif_res) ## ----------------------------------------------------------------------------- prog_res <- progressionTest(sds, conditions = df$conditions, method = "Classifier", args_classifier = list(method = "rf")) knitr::kable(prog_res) dif_res <- fateSelectionTest(sds, conditions = df$conditions) knitr::kable(dif_res) ## ----------------------------------------------------------------------------- sessionInfo()