scRead | R Documentation |
A function to read single-cell expression matrix
scRead(
sample_name = NULL,
data_dir = NULL,
gene_column = 2,
min_cells = 5,
min_features = 200,
min_rnas = 1000,
percent_mito = 20,
mito_pattern = "^GRCh38_MT-|^mm10___mt-|^MT-|^mt-",
project_name = "Seurat",
group_name = NULL,
strip_suffix = TRUE,
meta_file = NULL,
human.prefix = "GRCh38_",
mouse.prefix = "mm10___",
organism.thres = 0.9,
organism.use = NULL,
meta_features = NULL
)
sample_name |
Name of the sample |
data_dir |
Directory containing the quantification matrix (matrix.mtx, features.tsv, and barcodes.tsv) |
gene_column |
Column of genes.tsv to use for gene names, default is 2 |
min_cells |
Minimum number of cells express this feature |
min_features |
Minimum number of features expressed in this cell |
min_rnas |
Minimum number of molecules detected within a cell. |
percent_mito |
Maximum percent of mito in a cell |
mito_pattern |
regex pattern for mitochondrial genes, default is '^GRCh38_MT-|^mm10___mt-|^MT-|^mt-' |
project_name |
Project name for the Seurat object |
group_name |
Group name for the Seurat object |
strip_suffix |
Remove trailing '-1' in cell barcodes |
meta_file |
Meta file to use |
human.prefix |
The prefix denoting rownames for human cells. Default is 'GRCh38_'. Just for PDX samples |
mouse.prefix |
The prefix denoting rownames for mouse cells. Default is 'mm10___'. Just for PDX samples |
organism.thres |
Threshould fraction of reads to separate organism and background, Default is 0.9. Just for PDX samples |
organism.use |
Which organism is used. Default is NULL, means all organisms will be used. Just for PDX samples |
meta_features |
Features used to store in the meta.data slot |
read scRNA matrix
It supports read gene expression matrix and microbiome quantification matrix simultaneously
A Seurat object.
Inspired by Stuart and Butler et al, Cell (2019)
x <- scRead(sample_name = "Infected",
data_dir = system.file("extdata/H3N2_10X_matrix/Infected/",
package="Yeskit"),
gene_column = 2,
project_name = "H3N2",
group_name = "Infected",
meta_file = system.file("extdata/H3N2_10X_matrix/Infected/microbes.tsv",
package="Yeskit"),
)
x
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