clustify_nudge {clustifyr} | R Documentation |
Combined function to compare scRNA-seq data to bulk RNA-seq data and marker list
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, ... )
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 |
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 |
single cell object, or matrix of numeric values, clusters from input as row names, cell types from ref_mat as column names
# 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" )