Maelstrom_Motif2TF {AnanseSeurat}

Maelstrom_Motif2TF

Description

create motif-factor links & export tables for printing motif score alongside its binding factor

Usage

Maelstrom_Motif2TF(
  seurat_object,
  mot_mat = NULL,
  m2f_df = NULL,
  cluster_id = "seurat_clusters",
  maelstrom_dir = "./maelstrom/",
  combine_motifs = "means",
  RNA_expression_assay = "RNA",
  RNA_expression_slot = "data",
  expr_tresh = 10,
  cor_tresh = 0.3,
  curated_motifs = FALSE,
  cor_method = "pearson",
  return_df = FALSE
)

Arguments

seurat_object

object

mot_mat

motif_matrix, if not provided extracts one from the single cell object from the maelstrom assay

m2f_df

motif to factor dataframe, if not provided extracts from the maelstrom directory

cluster_id

ID used for finding clusters of cells

maelstrom_dir

directory where the GimmeMotifs m2f table is stored

combine_motifs

means (take mean multiple motifscores), max_var (take motif with highest variance), or max_cor (take motif with best correlation to gene expression)

RNA_expression_assay

Seurat assay containing factor expression info

RNA_expression_slot

slot within assay used for calculating mean factor expression per cluster

expr_tresh

minimum sum of gene counts over all cells in RNA_expression_assay to filter genes by

cor_tresh

minimum value of to filter the cor() output by

curated_motifs

use only curated motifs (T), or all motifs in the database (F)

cor_method

specify one of the cor() methods

return_df

return both the seurat object and two dataframes with maelstrom scores and expression values as a list

Value

seurat object with two assays added, MotifTFcor for TFs with positive correlation to the linked motif, and MotifTFanticor for TFs with positive correlation to the linked motif

Examples

sce_small <- readRDS(system.file("extdata","sce_small.Rds",package = 'AnanseSeurat'))
maelstrom_dir_path <- system.file("extdata","maelstrom",package = 'AnanseSeurat')
sce_small <- Maelstrom_Motif2TF(sce_small, maelstrom_dir = maelstrom_dir_path)