Initializes the Seurat object and some optional filtering
CreateSeuratObject(raw.data, project = "SeuratProject", min.cells = 0,
min.genes = 0, is.expr = 0, normalization.method = NULL,
scale.factor = 10000, do.scale = FALSE, do.center = FALSE,
names.field = 1, names.delim = "_", meta.data = NULL,
display.progress = TRUE, ...)
Raw input data
Project name (string)
Include genes with detected expression in at least this many cells. Will subset the raw.data matrix as well. To reintroduce excluded genes, create a new object with a lower cutoff.
Include cells where at least this many genes are detected.
Expression threshold for 'detected' gene. For most datasets, particularly UMI datasets, will be set to 0 (default). If not, when initializing, this should be set to a level based on pre-normalized counts (i.e. require at least 5 counts to be treated as expresesd) All values less than this will be set to 0 (though maintained in object@raw.data).
Method for cell normalization. Default is no normalization. In this case, run NormalizeData later in the workflow. As a shortcut, you can specify a normalization method (i.e. LogNormalize) here directly.
If normalizing on the cell level, this sets the scale factor.
In object@scale.data, perform row-scaling (gene-based z-score). FALSE by default. In this case, run ScaleData later in the workflow. As a shortcut, you can specify do.scale = TRUE (and do.center = TRUE) here.
In object@scale.data, perform row-centering (gene-based centering)
For the initial identity class for each cell, choose this field from the cell's column name
For the initial identity class for each cell, choose this delimiter from the cell's column name
Additional metadata to add to the Seurat object. Should be a data frame where the rows are cell names, and the columns are additional metadata fields
display progress bar for normalization and/or scaling procedure.
Ignored
Returns a Seurat object with the raw data stored in object@raw.data. object@data, object@meta.data, object@ident, also initialized.
# NOT RUN {
pbmc_raw <- read.table(
file = system.file('extdata', 'pbmc_raw.txt', package = 'Seurat'),
as.is = TRUE
)
pbmc_small <- CreateSeuratObject(raw.data = pbmc_raw)
pbmc_small
# }
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