Returns a by identity meta.data data.frame with one row per sample. Useful for downstream quick view of sample breakdown, meta data table creation, and/or use in pseudobulk analysis
Extract_Sample_Meta(
object,
sample_name = "orig.ident",
variables_include = NULL,
variables_exclude = NULL,
include_all = FALSE
)
Seurat object
meta.data column to use as sample. Output data.frame will contain one row per level or unique value in this variable.
@meta.data
columns to keep in final data.frame. All other columns will
be discarded. Default is NULL.
columns to discard in final data.frame. Many cell level columns are irrelevant at the sample level (e.g., nFeature_RNA, percent_mito).
Default parameter value is NULL
but internally will set to discard nFeature_ASSAY(s),
nCount_ASSAY(s), percent_mito, percent_ribo, percent_mito_ribo, and log10GenesPerUMI.
If sample level median values are desired for these type of variables the output of this
function can be joined with output of Median_Stats
.
Set parameter to include_all = TRUE
to prevent any columns from being excluded.
logical, whether or not to include all object meta data columns in output data.frame. Default is FALSE.
Returns a data.frame with one row per sample_name
.
library(Seurat)
pbmc_small[["batch"]] <- sample(c("batch1", "batch2"), size = ncol(pbmc_small), replace = TRUE)
sample_meta <- Extract_Sample_Meta(object = pbmc_small, sample_name = "orig.ident")
# Only return specific columns from meta data (orig.ident and batch)
sample_meta2 <- Extract_Sample_Meta(object = pbmc_small, sample_name = "orig.ident",
variables_include = "batch")
# Return all columns from meta data
sample_meta3 <- Extract_Sample_Meta(object = pbmc_small, sample_name = "orig.ident",
include_all = TRUE)