Read 10X alignment data (including V3)
This function generates a sparse matrix (genes x cells) from the data generated by 10X's cellranger count pipeline. It can process V2 and V3 data together, producing either a single merged matrix or list of matrices. Also handles multiple data types produced by 10X V3 (Gene Expression, Antibody Capture, CRISPR, CUSTOM).
read10X( sample.dirs, sample.names, merge = TRUE, num.cells = NULL, min.umis = 0, use.filtered = FALSE, reference = NULL, data.type = "rna", verbose = TRUE )
sample.dirs |
List of directories containing either matrix.mtx(.gz) file along with genes.tsv, (features.tsv), and barcodes.tsv, or outer level 10X output directory (containing outs directory). |
sample.names |
Vector of names to use for samples (corresponding to sample.dirs) |
merge |
Whether to merge all matrices of the same data type across samples or leave as list of matrices (default TRUE). |
num.cells |
Optional limit on number of cells returned for each sample (only for Gene Expression data). Retains the cells with the highest numbers of transcripts (default NULL). |
min.umis |
Minimum UMI threshold for cells (default 0). |
use.filtered |
Whether to use 10X's filtered data (as opposed to raw). Only relevant for sample.dirs containing 10X outs directory (default FALSE). |
reference |
For 10X V<3, specify which reference directory to use if sample.dir is outer level 10X directory (only necessary if more than one reference used for sequencing). (default NULL) |
data.type |
Indicates the protocol of the input data. If not specified, input data will be considered scRNA-seq data (default 'rna', alternatives: 'atac'). |
verbose |
Print messages (TRUE by default) |
List of merged matrices across data types (returns sparse matrix if only one data type detected), or nested list of matrices organized by sample if merge=F.
## Not run:
# 10X output directory V2 -- contains outs/raw_gene_bc_matrices/<reference>/...
sample.dir1 <- "path/to/outer/dir1"
# 10X output directory V3 -- for two data types, Gene Expression and CUSTOM
sample.dir2 <- "path/to/outer/dir2"
dges1 <- read10X(list(sample.dir1, sample.dir2), c("sample1", "sample2"), min.umis = 50)
ligerex <- createLiger(expr = dges1[["Gene Expression"]], custom = dges1[["CUSTOM"]])
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