read.data: Read and Preprocess Data

In robustSingleCell: Robust Clustering of Single Cell RNA-Seq Data

Description

Read 10X data files or a raw data matrix and perform normalization, QC filtering and duplicates removal.

Usage

read.data(environment, genome = "mm10", min.genes.per.cell = 500,
  max.genes.per.cell.quantile = 0.98,
  max.UMIs.per.cell.quantile = 0.98, min.cells.per.gene = 1,
  max.mitochondrial.frac = 0.1, max.ribosomal.frac = NA,
  cell.filters = NA, raw.data.matrices = NA, rerun = F,
  subsample = NULL, seed = 0)

Arguments

environment	environment object
genome	genome annotation
min.genes.per.cell	minimum required number of genes per cell
max.genes.per.cell.quantile	upper quantile for number of genes per cell
max.UMIs.per.cell.quantile	upper quantile for number of UMIs per cell
min.cells.per.gene	minimum required number of cells per gene
max.mitochondrial.frac	maximum fraction of reads mapped to mitochondrial genes per cell
max.ribosomal.frac	maximum fraction of reads mapped to ribosomal genes per cell
cell.filters	filtering option for cells based on marker genes
raw.data.matrices	logical indicating if data matrices is provided instead of 10X dataset
rerun	whether to rerun loading the dataset or load from cache
subsample	number of cells to subsample
seed	seed for subsampling of cells

Examples

LCMV1 <- setup_LCMV_example()
data.path <- system.file("extdata/LCMV1_small.txt", package = "robustSingleCell")
# name of list should be the same as LCMV1$datasets
raw_LCMV1 <- as.matrix(read.table(data.path, check.names = FALSE))
LCMV1 <- read.data(LCMV1,
raw.data.matrices = list(LCMV1 = raw_LCMV1),
min.genes.per.cell = 100,
max.genes.per.cell.quantile = 1,
max.UMIs.per.cell.quantile = 1,
min.cells.per.gene = 1)

robustSingleCell documentation built on May 2, 2019, 2:11 p.m.