View source: R/calc-similarity.R
calc_similarity | R Documentation |
Calculate repertoire similarity
calc_similarity(
input,
data_col,
cluster_col,
method = abdiv::jaccard,
chain = NULL,
chain_col = global$chain_col,
prefix = NULL,
return_mat = FALSE,
sep = global$sep
)
input |
Object containing V(D)J data. If a data.frame is provided, the cell barcodes should be stored as row names. |
data_col |
meta.data column containing values to use for calculating pairwise similarity between clusters, e.g. 'clonotype_id' |
cluster_col |
meta.data column containing cluster IDs to use for calculating repertoire overlap |
method |
Method to use for comparing clusters, possible values include:
|
chain |
Chain to use for comparing clusters. To perform calculations using a single chain, the column passed to the data_col argument must contain per-chain data such as CDR3 sequences. Set to NULL to include all chains. |
chain_col |
meta.data column containing chains for each cell |
prefix |
Prefix to add to new columns |
return_mat |
Return a matrix with similarity values. If set to FALSE, results will be added to the input object. |
sep |
Separator used for storing per-chain V(D)J data for each cell |
Single cell object or data.frame with similarity values
plot_similarity()
, calc_mds()
, plot_mds()
# Calculate repertoire overlap
res <- calc_similarity(
vdj_sce,
data_col = "clonotype_id",
cluster_col = "orig.ident",
method = abdiv::jaccard
)
head(slot(res, "colData"), 1)
# Add a prefix to the new columns
# this is useful if multiple calculations are stored in the meta.data
res <- calc_similarity(
vdj_sce,
data_col = "clonotype_id",
cluster_col = "orig.ident",
prefix = "bcr_"
)
head(slot(res, "colData"), 1)
# Return a matrix instead of adding the results to the input object
calc_similarity(
vdj_sce,
data_col = "clonotype_id",
cluster_col = "orig.ident",
return_mat = TRUE
)
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