## ----knitr-options, echo = FALSE, message = FALSE, warning = FALSE------------ knitr::opts_chunk$set(collapse = TRUE, comment = "#>") options(max.print = 30) ## ----install-bioc, eval = FALSE, include=TRUE--------------------------------- # BiocManager::install("simPIC") ## ----quickstart--------------------------------------------------------------- # Load package suppressPackageStartupMessages({ library(simPIC) }) # Load test data set.seed(12) counts <- readRDS(system.file("extdata", "test.rds", package = "simPIC")) # Estimate parameters est <- simPICestimate(counts) # Simulate data using estimated parameters sim <- simPICsimulate(est) ## ----pic, eval=FALSE, include=TRUE-------------------------------------------- # pic_mat <- PIC_counting( # cells = cells, # fragment_tsv_gz_file_location = fragment_tsv_gz_file_location, # peak_sets = peak_sets # ) ## ----simPICparams------------------------------------------------------------- sim.params <- newsimPICcount() ## ----params------------------------------------------------------------------- sim.params ## ----getParam----------------------------------------------------------------- simPICget(sim.params, "nPeaks") ## ----setParam----------------------------------------------------------------- sim.params <- setsimPICparameters(sim.params, nPeaks = 2000) simPICget(sim.params, "nPeaks") ## ----getParams-setParams------------------------------------------------------ # Set multiple parameters at once (using a list) sim.params <- setsimPICparameters(sim.params, update = list(nPeaks = 8000, nCells = 500) ) # Extract multiple parameters as a list params <- simPICgetparameters( sim.params, c("nPeaks", "nCells", "peak.mean.shape") ) # Set multiple parameters at once (using additional arguments) params <- setsimPICparameters(sim.params, lib.size.sdlog = 3.5, lib.size.meanlog = 9.07 ) params ## ----simPICestimate----------------------------------------------------------- # Get the counts from test data count <- readRDS(system.file("extdata", "test.rds", package = "simPIC")) # Check that counts is a dgCMatrix class(count) typeof(count) # Check the dimensions, each row is a peak, each column is a cell dim(count) # Show the first few entries count[1:5, 1:5] new <- newsimPICcount() new <- simPICestimate(count) ## estimating using gamma distribution ## new <- simPICestimate(count, pm.distr = "gamma") ## ----simPICsimulate----------------------------------------------------------- sim <- simPICsimulate(new, nCells = 1000) sim ## simulating using gamma distribution ## sim <- simPICsimulate(new, nCells =1000, pm.distr = "gamma") ## ----SCE---------------------------------------------------------------------- # Access the counts counts(sim)[1:5, 1:5] # Information about peaks head(rowData(sim)) # Information about cells head(colData(sim)) # Peak by cell matrices names(assays(sim)) ## ----comparison--------------------------------------------------------------- sim1 <- simPICsimulate(nPeaks = 20000, nCells = 1000) sim2 <- simPICsimulate(nPeaks = 20000, nCells = 1000) comparison <- simPICcompare(list(real = sim1, simPIC = sim2)) names(comparison) names(comparison$Plots) ## ----comparison-means--------------------------------------------------------- comparison$Plots$Means ## ----citation----------------------------------------------------------------- citation("simPIC") ## ----sessionInfo-------------------------------------------------------------- sessionInfo()