pos_neg_select | R Documentation |
adapt clustify to tweak score for pos and neg markers
pos_neg_select(
input,
ref_mat,
metadata,
cluster_col = "cluster",
cutoff_n = 0,
cutoff_score = 0.5
)
input |
single-cell expression matrix |
ref_mat |
reference expression matrix with positive and negative markers(set expression at 0) |
metadata |
cell cluster assignments,
supplied as a vector or data.frame. If
data.frame is supplied then |
cluster_col |
column in metadata that contains cluster ids per cell. Will default to first column of metadata if not supplied. Not required if running correlation per cell. |
cutoff_n |
expression cutoff where genes ranked below n are considered non-expressing |
cutoff_score |
positive score lower than this cutoff will be considered as 0 to not influence scores |
matrix of numeric values, clusters from input as row names, cell types from ref_mat as column names
pn_ref <- data.frame(
"Myeloid" = c(1, 0.01, 0),
row.names = c("CD74", "clustifyr0", "CD79A")
)
pos_neg_select(
input = pbmc_matrix_small,
ref_mat = pn_ref,
metadata = pbmc_meta,
cluster_col = "classified",
cutoff_score = 0.8
)
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