pos_neg_select: adapt clustify to tweak score for pos and neg markers

In NCBI-Hackathons/clustifyR: Classifier for Single-cell RNA-seq Using Cell Clusters

adapt clustify to tweak score for pos and neg markers

Description

adapt clustify to tweak score for pos and neg markers

Usage

pos_neg_select(
  input,
  ref_mat,
  metadata,
  cluster_col = "cluster",
  cutoff_n = 0,
  cutoff_score = 0.5
)

Arguments

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 needs to be set. Not required if running correlation per cell.
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

Value

matrix of numeric values, clusters from input as row names, cell types from ref_mat as column names

Examples

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
)

NCBI-Hackathons/clustifyR documentation built on July 4, 2025, 10 a.m.