Adds cell metadata to the giotto object
Usage
addCellMetadata(
gobject,
spat_unit = NULL,
feat_type = NULL,
new_metadata,
vector_name = NULL,
by_column = FALSE,
column_cell_ID = NULL
)Arguments
- gobject
giotto object
- spat_unit
spatial unit
- feat_type
feature type
- new_metadata
new cell metadata to use (data.table, data.frame, vector, factor, ...)
- vector_name
(optional) custom name for new metadata column if single vector or factor is provided
- by_column
merge metadata based on cell_ID column in
pDataDT(default = FALSE)- column_cell_ID
column name of new metadata to use if
by_column = TRUE
Details
You can add additional cell metadata in several manners:
1. Provide a data.frame-like object, vector, or factor with cell annotations in the same order as the cell_ID column in pDataDT(gobject). This is a bit risky and not the most recommended.
2. Provide a data.frame-like object with cell annotations and specify which column contains the cell IDs, these cell IDs need to match with the cell_ID column in pDataDT(gobject)
3. Provide a vector or factor that is named with the cell IDs they correspond to. These names will be matched against the cell_ID column in pDataDT(gobject).
Examples
g <- GiottoData::loadGiottoMini("visium")
#> 1. read Giotto object
#> 2. read Giotto feature information
#> 3. read Giotto spatial information
#> 3.1 read Giotto spatial shape information
#> 3.2 read Giotto spatial centroid information
#> 3.3 read Giotto spatial overlap information
#> 4. read Giotto image information
#> python already initialized in this session
#> active environment : 'giotto_env'
#> python version : 3.10
#> checking default envname 'giotto_env'
#> a system default python environment was found
#> Using python path:
#> "/usr/share/miniconda/envs/giotto_env/bin/python"
m <- pDataDT(g)
m <- m[, c("cell_ID", "leiden_clus")]
m$cell_type <- paste0("cell_type_", m$leiden_clus)
m <- m[, c("cell_ID", "cell_type")]
g <- addCellMetadata(
g,
new_metadata = m,
by_column = TRUE,
column_cell_ID = "cell_ID"
)
pDataDT(g)
#> cell_ID in_tissue nr_feats perc_feats total_expr leiden_clus
#> <char> <int> <int> <num> <num> <num>
#> 1: AACTCGATGGCGCAGT-1 1 265 41.79811 1057.9308 2
#> 2: GGCTGGCTAGCTTAAA-1 1 279 44.00631 1064.7493 5
#> 3: GACGCCTGTTGCAGGG-1 1 219 34.54259 964.9294 2
#> 4: GAGGGCATCGCGTATC-1 1 294 46.37224 1142.7664 2
#> 5: TCAACACATTGGGTAA-1 1 261 41.16719 1063.3517 2
#> ---
#> 620: GGTAGTGCTCGCACCA-1 1 179 28.23344 768.4749 5
#> 621: AAGCTCGTGCCAAGTC-1 1 195 30.75710 756.0675 5
#> 622: TATTCAATTCTAATCC-1 1 247 38.95899 921.8264 5
#> 623: TTCAAAGTCTCTAGCC-1 1 384 60.56782 916.5929 6
#> 624: TTGAATATGGACTTTC-1 1 380 59.93691 912.3051 6
#> custom_leiden cell_type
#> <num> <char>
#> 1: 4 cell_type_2
#> 2: 3 cell_type_5
#> 3: 3 cell_type_2
#> 4: 3 cell_type_2
#> 5: 3 cell_type_2
#> ---
#> 620: 4 cell_type_5
#> 621: 4 cell_type_5
#> 622: 4 cell_type_5
#> 623: 7 cell_type_6
#> 624: 4 cell_type_6