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First, load the following packages. Note, some of the packages are not available on CRAN or BioConductor. They can, however, be installed by using the drat package.
pkgLoaded <- suppressPackageStartupMessages({ c(require(bcTSNE), require(data.table), require(batchelor), require(kBET), require(splatter), require(scater), require(Rtsne), require(lisi), require(harmony), require(dlfUtils), require(xtable)) }) pkgLoaded <- all(pkgLoaded)
Uncomment to install kBet & lisi
Note: the packages will require compilation
if (!require(drat)) {install.packages("drat"); library(drat)}
drat::addRepo("daynefiler")
install.packages(c("lisi", "kBET", "harmony", "dlfUtils"))
Create simulated single-cell RNA sequencing data using the splatter package.
if (pkgLoaded) { p <- newSplatParams(seed = 1234, batchCells = rep(200, 4), batch.facLoc = 0.2, batch.facScale = 0.1, group.prob = c(0.1, 0.2, 0.3, 0.4), de.facLoc = 0.1, de.facScale = 0.4) sim <- splatSimulate(p, method = "groups", verbose = FALSE) sizeFactors(sim) <- librarySizeFactors(sim) sim <- logNormCounts(sim) sim <- logNormCounts(sim, log = FALSE) assay(sim, "centered") <- t(scale(t(normcounts(sim)), center = TRUE, scale = FALSE)) Z <- model.matrix( ~ -1 + factor(colData(sim)$Batch)) grp <- factor(sim$Group) bch <- as.integer(factor(sim$Batch)) }
Setup a placeholder for the results:
res <- vector(mode = "list", length = 6) names(res) <- c("btcc", "btlc", "hmlc", "hmcc", "mnn", "tsne")
Start by running the regular t-SNE algorithm:
if (pkgLoaded) { set.seed(1234) res$tsne <- Rtsne(t(assay(sim, "centered")), inital_dims = 50)$Y pltSimRes(res$tsne, "t-SNE") }
t−SNE
Batch:
Cell−type:
Run the BC-t-SNE algorithm on centered:
if (pkgLoaded) { set.seed(1234) res$btcc <- bctsne(t(assay(sim, "centered")), Z, k = 50)$Y pltSimRes(res$btcc, "bcTSNE-centered") }
if (pkgLoaded) { set.seed(1234) sim <- runPCA(sim, 50, exprs_values = "logcounts") sim <- RunHarmony(sim, group.by.vars = "Batch") res$hmlc = Rtsne(reducedDim(sim, "HARMONY"), pca = FALSE)$Y pltSimRes(res$hmlc, "Harmony-logcounts") }
Harmony−logcounts
Batch:
Cell−type:
Run the harmony algorithm on the same set as bcTSNE, centered:
if (pkgLoaded) { set.seed(1234) sim <- runPCA(sim, 50, exprs_values = "centered") sim <- RunHarmony(sim, group.by.vars = "Batch") res$hmcc = Rtsne(reducedDim(sim, "HARMONY"), pca = FALSE)$Y pltSimRes(res$hmcc, "Harmony-centered") }
Harmony−centered
Batch:
Cell−type:
Run the MNN algorithm:
if (pkgLoaded) { set.seed(1234) tmp <- mnnCorrect(sim, batch = factor(sim$Batch)) res$mnn <- Rtsne(t(assay(tmp, "corrected")), initial_dims = 50)$Y rm(tmp) pltSimRes(res$mnn, "mnnRes") }
mnnRes
Batch:
Cell−type:
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if (pkgLoaded) { calcMetrics <- function(Y, bchLst) { calcSil <- function(x) { s <- batch_sil(pca.data = list(x = Y), batch = x, nPCs = 2) 1 - abs(s)
