clustify_nudge: Combined function to compare scRNA-seq data to bulk RNA-seq...

In clustifyr: Classifier for Single-cell RNA-seq Using Cell Clusters

Description

Combined function to compare scRNA-seq data to bulk RNA-seq data and marker list

Usage

clustify_nudge(input, ...)

## Default S3 method:
clustify_nudge(
  input,
  ref_mat,
  marker,
  metadata = NULL,
  cluster_col = NULL,
  query_genes = NULL,
  compute_method = "spearman",
  weight = 1,
  seurat_out = FALSE,
  threshold = -Inf,
  dr = "umap",
  norm = "diff",
  call = TRUE,
  marker_inmatrix = TRUE,
  mode = "rank",
  obj_out = FALSE,
  rename_prefix = NULL,
  lookuptable = NULL,
  ...
)

## S3 method for class 'seurat'
clustify_nudge(
  input,
  ref_mat,
  marker,
  cluster_col = NULL,
  query_genes = NULL,
  compute_method = "spearman",
  weight = 1,
  seurat_out = TRUE,
  obj_out = FALSE,
  threshold = -Inf,
  dr = "umap",
  norm = "diff",
  marker_inmatrix = TRUE,
  mode = "rank",
  rename_prefix = NULL,
  ...
)

## S3 method for class 'Seurat'
clustify_nudge(
  input,
  ref_mat,
  marker,
  cluster_col = NULL,
  query_genes = NULL,
  compute_method = "spearman",
  weight = 1,
  seurat_out = TRUE,
  obj_out = FALSE,
  threshold = -Inf,
  dr = "umap",
  norm = "diff",
  marker_inmatrix = TRUE,
  mode = "rank",
  rename_prefix = NULL,
  ...
)

Arguments

input	express matrix or object
...	passed to matrixize_markers
ref_mat	reference expression matrix
marker	matrix of markers
metadata	cell cluster assignments, supplied as a vector or data.frame. If data.frame is supplied then cluster_col needs to be set.
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.
query_genes	A vector of genes of interest to compare. If NULL, then common genes between the expr_mat and ref_mat will be used for comparision.
compute_method	method(s) for computing similarity scores
weight	relative weight for the gene list scores, when added to correlation score
seurat_out	output cor matrix or called seurat object
threshold	identity calling minimum score threshold, only used when obj_out = T
dr	stored dimension reduction
norm	whether and how the results are normalized
call	make call or just return score matrix
marker_inmatrix	whether markers genes are already in preprocessed matrix form
mode	use marker expression pct or ranked cor score for nudging
obj_out	whether to output object instead of cor matrix
rename_prefix	prefix to add to type and r column names
lookuptable	if not supplied, will look in built-in table for object parsing

Value

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

Examples

# Seurat2
clustify_nudge(
    input = s_small,
    ref_mat = cbmc_ref,
    marker = cbmc_m,
    cluster_col = "res.1",
    threshold = 0.8,
    seurat_out = FALSE,
    mode = "pct",
    dr = "tsne"
)

# Seurat3
clustify_nudge(
    input = s_small3,
    ref_mat = cbmc_ref,
    marker = cbmc_m,
    cluster_col = "RNA_snn_res.1",
    threshold = 0.8,
    seurat_out = FALSE,
    mode = "pct",
    dr = "tsne"
)

# Matrix
clustify_nudge(
    input = pbmc_matrix_small,
    ref_mat = cbmc_ref,
    metadata = pbmc_meta,
    marker = as.matrix(cbmc_m),
    query_genes = pbmc_vargenes,
    cluster_col = "classified",
    threshold = 0.8,
    call = FALSE,
    marker_inmatrix = FALSE,
    mode = "pct"
)

clustifyr documentation built on Nov. 8, 2020, 5:32 p.m.