clustify_lists {clustifyr} | R Documentation |
Main function to compare scRNA-seq data to gene lists.
clustify_lists(input, ...) ## Default S3 method: clustify_lists( input, marker, marker_inmatrix = TRUE, metadata = NULL, cluster_col = NULL, if_log = TRUE, per_cell = FALSE, topn = 800, cut = 0, genome_n = 30000, metric = "hyper", output_high = TRUE, lookuptable = NULL, obj_out = TRUE, seurat_out = TRUE, rename_prefix = NULL, threshold = 0, low_threshold_cell = 0, verbose = TRUE, input_markers = FALSE, details_out = FALSE, ... ) ## S3 method for class 'Seurat' clustify_lists( input, metadata = NULL, cluster_col = NULL, if_log = TRUE, per_cell = FALSE, topn = 800, cut = 0, marker, marker_inmatrix = TRUE, genome_n = 30000, metric = "hyper", output_high = TRUE, dr = "umap", seurat_out = TRUE, obj_out = TRUE, threshold = 0, rename_prefix = NULL, verbose = TRUE, details_out = FALSE, ... ) ## S3 method for class 'SingleCellExperiment' clustify_lists( input, metadata = NULL, cluster_col = NULL, if_log = TRUE, per_cell = FALSE, topn = 800, cut = 0, marker, marker_inmatrix = TRUE, genome_n = 30000, metric = "hyper", output_high = TRUE, dr = "umap", seurat_out = TRUE, obj_out = TRUE, threshold = 0, rename_prefix = NULL, verbose = TRUE, details_out = FALSE, ... )
input |
single-cell expression matrix or Seurat object |
... |
passed to matrixize_markers |
marker |
matrix or dataframe of candidate genes for each cluster |
marker_inmatrix |
whether markers genes are already in preprocessed matrix form |
metadata |
cell cluster assignments,
supplied as a vector or data.frame.
If data.frame is supplied then |
cluster_col |
column in metadata with cluster number |
if_log |
input data is natural log, averaging will be done on unlogged data |
per_cell |
compare per cell or per cluster |
topn |
number of top expressing genes to keep from input matrix |
cut |
expression cut off from input matrix |
genome_n |
number of genes in the genome |
metric |
adjusted p-value for hypergeometric test, or jaccard index |
output_high |
if true (by default to fit with rest of package), -log10 transform p-value |
lookuptable |
if not supplied, will look in built-in table for object parsing |
obj_out |
whether to output object instead of cor matrix |
seurat_out |
output cor matrix or called seurat object (deprecated, use obj_out instead) |
rename_prefix |
prefix to add to type and r column names |
threshold |
identity calling minimum correlation score threshold, only used when obj_out = T |
low_threshold_cell |
option to remove clusters with too few cells |
verbose |
whether to report certain variables chosen and steps |
input_markers |
whether input is marker data.frame of 0 and 1s (output of pos_neg_marker), and uses alternate enrichment mode |
details_out |
whether to also output shared gene list from jaccard |
dr |
stored dimension reduction |
matrix of numeric values, clusters from input as row names, cell types from marker_mat as column names
# Annotate a matrix and metadata # Annotate using a different method clustify_lists( input = pbmc_matrix_small, marker = cbmc_m, metadata = pbmc_meta, cluster_col = "classified", verbose = TRUE, metric = "jaccard" )