Run cisTarget motif enrichment on a GRN adjacency table

cisTarget performs motif enrichment analysis on gene regulatory network adjacency tables. For each transcription factor, it identifies target genes whose regulatory regions are enriched for the TF's binding motifs, producing regulons (TF + enriched target gene sets).

Usage

RunCisTarget(
  adj,
  species = c("Homo_sapiens", "Mus_musculus", "Drosophila_melanogaster"),
  backend = c("python", "r"),
  ranking_dbs = NULL,
  motif_annotations = NULL,
  expression_mtx = NULL,
  ctx_output = NULL,
  min_regulon_size = 10,
  gmt_output = NULL,
  txt_output = NULL,
  work_dir = NULL,
  prefix = "cisTarget",
  data_dir = NULL,
  envname = NULL,
  conda = "auto",
  prepare_env = TRUE,
  cores = 1,
  force = FALSE,
  verbose = TRUE,
  ...
)

Arguments

adj

A data frame with columns TF, target, and optionally importance, or a path to a TSV adjacency file. This is typically the output of RunGRNBoost2(), RunGENIE3(), or RunSCENIC() step 1.

species

Species used to select cisTarget reference files when ranking_dbs, motif_annotations, or regulators is NULL. Supported values are "Homo_sapiens", "Mus_musculus", and "Drosophila_melanogaster".

backend

cisTarget runtime backend.

"python"

Uses the pySCENIC/ctxcore Python pipeline. This is the most tested backend and produces results identical to official SCENIC.

"r"

Uses the RcisTarget Bioconductor package. Requires the cisTarget ranking databases and motif annotations to be available in the same format as the Python backend (feather files and motif2tf table).

ranking_dbs

Character vector of cisTarget ranking feather files.

motif_annotations

Motif annotation table path (motif2tf).

expression_mtx

Optional expression matrix path (CSV). When NULL and backend = "python", the expression matrix is reconstructed from the unique genes in adj as a minimal stub.

ctx_output

Optional output file path for the cisTarget result.

min_regulon_size

Minimum number of target genes per regulon.

gmt_output

Optional output path for the regulon GMT file.

txt_output

Optional output path for the regulon TXT file.

work_dir

Working directory used by Python backend.

prefix

Prefix for output files.

data_dir

Directory used to cache automatically prepared SCENIC reference files. If NULL, files are stored under tools::R_user_dir("scop", "data")/SCENIC/<species>.

envname

Python environment name (Python backend only).

conda

Conda-compatible executable (Python backend only).

prepare_env

Whether to prepare the Python environment.

cores

Number of workers.

force

Whether to rebuild existing outputs.

verbose

Whether to print progress messages.

...

Additional arguments passed to the backend.

Value

A named list with components regulons (list of gene vectors), ctx_file (path to raw cisTarget output), gmt_file, and txt_file.

Examples

if (FALSE) { # \dontrun{
data(pancreas_sub)
pancreas_sub <- standard_scop(pancreas_sub)

# First run GRN inference
grn <- RunGRNBoost2(
  pancreas_sub,
  regulators = c("Neurod1", "Arx", "Pax6"),
  backend = "cpp"
)

# Then run cisTarget (Python backend)
regulons <- RunCisTarget(
  grn,
  species = "Mus_musculus",
  backend = "python"
)
} # }