Nothing
## ----knitr-options, include = FALSE-------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
## ----setup--------------------------------------------------------------------
suppressPackageStartupMessages({
library("splatter")
library("scater")
library("VariantAnnotation")
library("ggplot2")
})
## ----quick-start--------------------------------------------------------------
vcf <- mockVCF(n.samples = 6)
sim <- splatPopSimulate(vcf = vcf, "nGenes" = 100)
sim <- logNormCounts(sim)
sim <- runPCA(sim, ncomponents = 10)
plotPCA(sim, colour_by = "Sample")
## ----default-SplatPopParams---------------------------------------------------
params <- newSplatPopParams()
params
## ----eqtlEstimate-------------------------------------------------------------
bulk.means <- mockBulkMatrix(n.genes=100, n.samples=100)
bulk.eqtl <- mockBulkeQTL(n.genes=100)
counts <- mockSCE()
params.est <- splatPopEstimate(means = bulk.means,
eqtl = bulk.eqtl,
counts = counts)
params.est
## ----splatPopSimulateMeans----------------------------------------------------
vcf <- mockVCF(n.samples = 6)
gff <- mockGFF(n.genes = 100)
sim.means <- splatPopSimulateMeans(vcf = vcf, gff = gff,
params = newSplatPopParams())
round(sim.means$means[1:5, 1:6], digits = 2)
print(sim.means$key[1:5, ], digits = 2)
## ----splatPopSimulateMeans-from-key-------------------------------------------
sim.means.rep2 <- splatPopSimulateMeans(vcf = vcf, key=sim.means$key,
params = newSplatPopParams())
round(sim.means.rep2$means[1:5, 1:6], digits = 2)
## ----quant-normalize-population-data------------------------------------------
bulk.qnorm <- splatPopQuantNorm(newSplatPopParams(), bulk.means)
round(bulk.qnorm[1:5, 1:5], 3)
## ----eqtl-splatPopSimulateSC-simple-object------------------------------------
sim.sc <- splatPopSimulateSC(params=params,
key = sim.means$key,
sim.means=sim.means$means,
batchCells=50)
sim.sc
## ----eqtl-splatPopSimulateSC-simple-plots-------------------------------------
sim.sc <- logNormCounts(sim.sc)
sim.sc <- runPCA(sim.sc, ncomponents = 10)
plotPCA(sim.sc, colour_by = "Sample")
## ----group-specific-eQTL-simulations------------------------------------------
params.group <- newSplatPopParams(nGenes = 50,
batchCells = 40,
group.prob = c(0.5, 0.5))
sim.sc.gr2 <- splatPopSimulate(vcf = vcf, params = params.group)
sim.sc.gr2 <- logNormCounts(sim.sc.gr2)
sim.sc.gr2 <- runPCA(sim.sc.gr2, ncomponents = 10)
plotPCA(sim.sc.gr2, colour_by = "Group", shape_by = "Sample")
## ----group-specific-eQTL-simulations-bigger-----------------------------------
params.group <- newSplatPopParams(batchCells = 40,
nGenes = 50,
similarity.scale = 6,
eqtl.group.specific = 0.6,
de.prob = 0.5,
de.facLoc = 0.5,
de.facScale = 0.4,
group.prob = c(0.5, 0.5))
sim.sc.gr2 <- splatPopSimulate(vcf = vcf, params = params.group)
sim.sc.gr2 <- logNormCounts(sim.sc.gr2)
sim.sc.gr2 <- runPCA(sim.sc.gr2, ncomponents = 10)
plotPCA(sim.sc.gr2, colour_by = "Group", shape_by = "Sample")
## ----simulate-population-with-batch-effects-----------------------------------
params.batches <- newSplatPopParams(batchCells = c(20, 20),
nGenes = 50,
similarity.scale = 5,
batch.facLoc = 0.3,
batch.facScale = 0.3)
sim.pop.batches <- splatPopSimulate(vcf = vcf, params = params.batches)
sim.pop.batches <- logNormCounts(sim.pop.batches)
sim.pop.batches <- runPCA(sim.pop.batches, ncomponents = 10)
plotPCA(sim.pop.batches, colour_by = "Batch", shape_by = "Sample",
ncomponents = 5:6)
## ----simulate-population-with-path-effects------------------------------------
params.paths <- newSplatPopParams(batchCells = 40,
nGenes = 50,
similarity.scale = 6,
de.facLoc = 0.5,
de.facScale = 0.5,
de.prob = 0.5)
sim.pop.paths <- splatPopSimulate(vcf = vcf, params = params.paths,
method = "paths")
sim.pop.paths <- logNormCounts(sim.pop.paths)
sim.pop.paths <- runPCA(sim.pop.paths, ncomponents = 10)
plotPCA(sim.pop.paths, colour_by = "Step", shape_by = "Sample",
ncomponents = 5:6)
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