Package 'craftgrn'

Title: Integrative Chromatin Accessibility and RNA Framework for Gene Regulatory Networks
Description: Provides a reproducible framework for constructing and comparing gene regulatory networks by integrating chromatin accessibility footprint scores with matched RNA expression data. It implements context-specific enhancer-gene linking, transcription factor focused network analysis, differential network analysis, and regulatory topic modeling workflows for systematic exploration of gene regulation across conditions.
Authors: Yaoxiang Li [aut, cre], Chunling Yi [aut]
Maintainer: Yaoxiang Li <[email protected]>
License: GPL (>= 3)
Version: 0.1.4
Built: 2026-06-19 09:30:21 UTC
Source: https://github.com/oncologylab/craftgrn

Help Index

Build a Module 1 QC HTML report

Description

Builds a comprehensive HTML report for Module 1 run parameters, input gates, motif-supported canonical support, prediction output integrity, correlation diagnostics, condition-level CraftGRN multiomic input QC, footprint alignment summaries, warning checks, and related QC artifacts. The report can consume a 'predict_tfbs()' result, a step-by-step Module 1 result list, or a Module 1 output directory.

Usage

build_module1_qc_report(
  module1,
  omics_data = NULL,
  output_dir = NULL,
  report_name = "module1_qc_report.html",
  scan_predicted_tfbs = TRUE,
  top_n = 20L,
  verbose = TRUE
)

Arguments

module1

Module 1 result list or Module 1 output directory.
omics_data

Optional CraftGRN multiomic object. Used when 'module1' is an output directory or does not contain 'omics_data'.
output_dir

Directory where the HTML report should be written. If 'NULL', the report is written under 'reports' inside the Module 1 output directory when available.
report_name

HTML report filename.
scan_predicted_tfbs

Logical; if 'TRUE', scan predicted TFBS chunks to summarize top TFs and condition support. This is comprehensive but can take extra time on full projects.
top_n

Number of TFs to show in top-TF summaries.
verbose

Emit concise progress messages.

Value

Normalized path to the HTML report.

Build a Module 2 QC HTML report

Description

Builds a comprehensive HTML report for Module 2 run parameters, CraftGRN multiomic input handoff, TF-target and FP-target correlation filters, candidate source and distance-to-TSS evidence, final TF-FP-target links, condition activity, CraftGRN multiomic condition context, warning checks, integrity checks, and related browser reports.

Usage

build_module2_qc_report(
  module2,
  multiomic_data = NULL,
  output_dir = NULL,
  report_name = "module2_qc_report.html",
  scan_large_tables = TRUE,
  validate_integrity = TRUE,
  top_n = 20L,
  verbose = TRUE
)

Arguments

module2

Module 2 result list, loaded Module 2 list, or output directory.
multiomic_data

Optional CraftGRN multiomic object used for context.
output_dir

Directory where the HTML report should be written. If 'NULL', the report is written under 'reports' inside the Module 2 output directory when available.
report_name

HTML report filename.
scan_large_tables

Logical; if 'TRUE', scan candidate and link chunks for top-TF, distance, and integrity summaries.
validate_integrity

Logical; if 'TRUE', verify final links against passing TF-target and FP-target keys while scanning link chunks.
top_n

Number of TFs to show in top-TF summaries.
verbose

Emit concise progress messages.

Value

Normalized path to the HTML report.

Build a Module 3 QC HTML report

Description

Writes a self-contained HTML report for Module 3 topic-model outputs. The report summarizes topic-input caches, model rows, theta separation scores, compact topic-link pass counts, and differential-link summaries when available.

Usage

build_module3_qc_report(
  topic_dir,
  output_dir = file.path(topic_dir, "reports"),
  differential_links_dir = NULL,
  title = "Module 3 QC report",
  top_n = 20L,
  verbose = TRUE
)

Arguments

topic_dir

Module 3 topic output directory.
output_dir

Directory where the report is written. Defaults to 'topic_dir/reports'.
differential_links_dir

Optional Module 3 differential-link directory. If 'NULL', CraftGRN tries to detect a sibling or nested 'differential_links' directory.
title

Report title.
top_n

Number of top differential TFs retained per comparison in the QC summary CSV.
verbose

Emit concise progress messages.

Value

Path to the HTML report.

Perform sanity check for predicted links for Module 2 diagnostics

Description

Perform sanity check for predicted links for Module 2 diagnostics

Usage

check_predicted_links(module2)

Arguments

module2

Module 2 result list or loaded output list.

Value

TRUE invisibly when valid.

Return metadata for configured external CraftGRN demo data

Description

Return metadata for configured external CraftGRN demo data

Usage

craftgrn_demo_data_info(demo = NULL)

Arguments

demo

Optional demo bundle name. No external demo bundle is currently configured.

Value

A data frame with the bundle URL, checksum, archive file name, and extracted project directory name. When no demo bundle is configured, the returned data frame has zero rows.

Download and unpack configured external CraftGRN demo data

Description

Downloads a processed demo data archive from a configured external source, verifies its MD5 checksum by default, extracts it, and returns the extracted project directory. Demo bundles are external to the R package so package installation remains small and CRAN-friendly. No external demo bundle is currently configured.

Usage

download_craftgrn_demo_data(
  destdir = ".",
  demo = NULL,
  overwrite = FALSE,
  checksum = TRUE,
  verbose = TRUE
)

Arguments

destdir

Directory where the archive should be downloaded and unpacked.
demo

Optional demo bundle name. No external demo bundle is currently configured.
overwrite

Logical; if 'TRUE', download the archive again and replace an existing extracted project directory.
checksum

Logical; if 'TRUE', verify the downloaded archive MD5.
verbose

Logical; if 'TRUE', emit concise status messages.

Details

If the download fails, inspect 'craftgrn_demo_data_info()' and download the configured asset manually. If checksum verification fails, rerun with 'overwrite = TRUE' to replace a stale or partial archive. The extracted project uses 'base_dir: "."', so pass the returned directory or its project config path directly to package functions after moving the folder.

Value

The normalized path to the extracted demo project directory.

Examples

craftgrn_demo_data_info()

Export predicted TFBS as BED files

Description

Export predicted TFBS as BED files

Usage

export_predicted_tfbs_bed(
  predicted_tfbs,
  out_file = NULL,
  out_dir = NULL,
  tf = NULL,
  split_by = c("none", "tf")
)

Arguments

predicted_tfbs

Compact predicted TFBS table or path.
out_file

BED output path. Required when split_by is none.
out_dir

Directory for split BED outputs.
tf

Optional TF subset.
split_by

One of none or tf.

Value

Output path or manifest tibble, invisibly.

Export predicted TF-target links as BEDPE

Description

Export predicted TF-target links as BEDPE

Usage

export_tf_target_bedpe(module2, output_file, tf = NULL)

Arguments

module2

Module 2 result list or loaded output list.
output_file

BEDPE output file.
tf

Optional TF subset.

Value

Output path invisibly.

Load a CraftGRN YAML config into an environment

Description

Reads a YAML file and assigns each top-level key as a variable in the target environment (e.g., 'db', 'threshold_tf_expr', etc.). Also runs standard config initialization helpers when available.

Usage

load_config(path, env = .craftgrn_state)

Arguments

path

Character path to a YAML file.
env

Environment to populate. Defaults to the internal CraftGRN config state.

Value

(Invisibly) the parsed list.

Examples

## Not run: 
load_config("craftgrn_grn.yaml")
# Config values are now available to CraftGRN helper functions.

## End(Not run)

Load a multi-omic data object from disk

Description

Load a multi-omic data object from disk

Usage

load_omics_data(file, verbose = TRUE)

Arguments

file

Path to an RDS file produced by save_omics_data().
verbose

Emit status messages.

Value

The loaded multi-omic data list.

Load predicted links from Module 2

Description

Load predicted links from Module 2

Usage

load_predicted_links(path)

Arguments

path

Module 2 output directory or module2_manifest.csv path.

Value

A named list of Module 2 tables.

Load TFBS predicted from Module 1

Description

Load TFBS predicted from Module 1

Usage

load_predicted_tfbs(path)

Arguments

path

Path to a predicted TFBS manifest, Parquet file, or CSV file.

Value

A tibble.

Load and prepare the Module 1 multi-omic object

Description

Build the rebuilt Module 1 data object from cached aligned footprints or from raw footprint overview files plus ATAC, RNA, and sample metadata inputs. The returned object is the canonical input for downstream Step 1 TFBS correlation.

Usage

load_prep_multiomic_data(
  config = NULL,
  genome = NULL,
  gene_symbol_col = "HGNC",
  fp_aligned = NULL,
  do_preprocess = FALSE,
  do_motif_clustering = FALSE,
  trim_hocomoco = FALSE,
  fp_root_dir = NULL,
  fp_cache_dir = NULL,
  fp_cache_tag = NULL,
  footprint_sample_scope = "metadata",
  mid_slop = 10L,
  round_digits = 1L,
  score_match_pct = 0.8,
  output_mode = c("full", "distinct"),
  write_outputs = FALSE,
  write_fp_score_qn_csv = TRUE,
  atac_data = NULL,
  rna_tbl = NULL,
  metadata = NULL,
  atac_data_path = NULL,
  rna_path = NULL,
  metadata_path = NULL,
  step1_out_dir_name = "predict_tf_binding_sites",
  label_col,
  expected_n = NULL,
  tf_list = NULL,
  motif_db = NULL,
  threshold_gene_expr = NULL,
  threshold_fp_score = NULL,
  use_parallel = TRUE,
  verbose = TRUE,
  time_log = verbose
)

Arguments

config

Optional YAML config path.
genome

Optional genome string used to override the config value.
gene_symbol_col

Gene-symbol column in the RNA table.
fp_aligned

Optional pre-aligned footprint object.
do_preprocess

Logical; if 'TRUE', load and align raw footprints before building the object. If 'FALSE', use cached aligned footprints.
do_motif_clustering

Logical; if 'TRUE', run motif clustering during preprocessing when available.
trim_hocomoco

Logical; trim HOCOMOCO manifests when the trimming helper is available.
fp_root_dir

Optional root directory for raw footprint overview files.
fp_cache_dir

Cache directory for aligned footprint files.
fp_cache_tag

Cache tag, typically the motif database name.
footprint_sample_scope

Footprint sample selection rule.
mid_slop, round_digits, score_match_pct

Alignment parameters passed to 'align_footprints()'.
output_mode

Output mode for aligned footprints. One of '"full"' or '"distinct"'.
write_outputs

Logical; if 'TRUE', save the prepared object as an RDS cache under 'predict_tf_binding_sites/'.
write_fp_score_qn_csv

Logical; if 'TRUE' and 'write_outputs = TRUE', also save quantile-normalized footprint scores as '01_fp_scores_qn_<db>.csv' under the Module 1 output directory.
atac_data, rna_tbl, metadata

Optional in-memory input tables.
atac_data_path, rna_path, metadata_path

Optional explicit file paths for the input tables.
step1_out_dir_name

Output folder name under 'base_dir'.
label_col

Metadata column used to aggregate matched conditions.
expected_n

Optional expected matched sample count.
tf_list

Optional TF allowlist for downstream correlation.
motif_db

Optional motif metadata table.
threshold_gene_expr

Expression threshold for Step 1 expression flags.
threshold_fp_score

Footprint-score threshold for Step 1 bound flags.
use_parallel

Logical; if 'TRUE', allow parallel work in supported helpers.
verbose

Logical; if 'TRUE', emit concise progress messages.
time_log

Logical; if TRUE, emit elapsed-time messages.

Value

A rebuilt Module 1 multi-omic object.

Examples

## Not run: 
omics_data <- load_prep_multiomic_data(
  config = "dev/config/pdac_nutrient_stress_strict_jaspar2024_demo.yaml",
  genome = "hg38",
  label_col = "strict_match_rna",
  do_preprocess = FALSE,
  verbose = TRUE
)

## End(Not run)

Correlate TFs to their canonical TFBS

Description

Correlate TFs to their canonical TFBS

Usage

module1_correlate_TF_to_canonical_tfbs(
  module1_inputs,
  r_cutoff = 0.3,
  p_cutoff = NULL,
  fdr_cutoff = NULL,
  min_non_na = 3L,
  cores = NULL,
  verbose = TRUE
)

Arguments

module1_inputs

Output from module1_prepare_tfbs_inputs.
r_cutoff

Minimum positive best correlation.
p_cutoff

Optional best-method p-value cutoff.
fdr_cutoff

Optional best-method FDR cutoff.
min_non_na

Minimum finite condition pairs required.
cores

Number of worker cores; NULL uses all available cores.
verbose

Emit concise progress messages.

Value

A tibble with Pearson, Spearman, best-method statistics, and pass flags.

Filter footprints with canonical binding for full TFBS prediction

Description

Filter footprints with canonical binding for full TFBS prediction

Usage

module1_filter_canonical_bound_tfbs(
  module1_inputs,
  motif_supported_correlations,
  r_cutoff = 0.3,
  p_cutoff = NULL,
  fdr_cutoff = NULL,
  filter_to_canonical_bound = TRUE,
  verbose = TRUE
)

Arguments

module1_inputs

Output from module1_prepare_tfbs_inputs.
motif_supported_correlations

Output from module1_correlate_TF_to_canonical_tfbs.
r_cutoff

Minimum positive best correlation.
p_cutoff

Optional p-value cutoff.
fdr_cutoff

Optional FDR cutoff.
filter_to_canonical_bound

Keep only footprints with a passing motif-supported TF.
verbose

Emit concise progress messages.

Value

A list with canonical-bound and prediction footprint tables.

Predict full TFBS for all expressed TFs

Description

Predict full TFBS for all expressed TFs

Usage

module1_predict_full_tfbs(
  module1_inputs,
  prediction_footprints,
  out_dir = "predict_tf_binding_sites",
  r_cutoff = 0.3,
  p_cutoff = NULL,
  fdr_cutoff = NULL,
  min_non_na = 3L,
  cores = NULL,
  write_outputs = TRUE,
  output_format = c("csv", "parquet", "auto"),
  return_prediction_stats = NULL,
  verbose = TRUE
)

Arguments

module1_inputs

Output from module1_prepare_tfbs_inputs.
prediction_footprints

Footprint table from module1_filter_canonical_bound_tfbs.
out_dir

Output directory.
r_cutoff

Minimum positive best correlation.
p_cutoff

Optional best-method p-value cutoff.
fdr_cutoff

Optional best-method FDR cutoff.
min_non_na

Minimum finite condition pairs required.
cores

Number of worker cores; NULL uses all available cores.
write_outputs

Write predicted TFBS outputs.
output_format

One of csv, parquet, or auto.
return_prediction_stats

Return full prediction statistics in memory.
verbose

Emit concise progress messages.

Value

A list with prediction statistics or manifests and predicted TFBS outputs.

Prepare Module 1 TFBS prediction inputs

Description

Prepare Module 1 TFBS prediction inputs

Usage

module1_prepare_tfbs_inputs(
  omics_data,
  label_col = NULL,
  tf_subset = NULL,
  verbose = TRUE
)

Arguments

omics_data

CraftGRN multiomic object returned by 'load_prep_multiomic_data()'.
label_col

Optional metadata column used to rebuild condition matrices.
tf_subset

Optional TF symbols to keep.
verbose

Emit concise progress messages.

Value

A list containing prepared data, condition columns, TFs, and footprint universe.

Correlate FP score with target gene expression

Description

Correlate FP score with target gene expression

Usage

module2_correlate_fp_targets(
  module2_inputs,
  candidates,
  n_cores = NULL,
  verbose = TRUE
)

Arguments

module2_inputs

Output from module2_identify_candidate_links.
candidates

Output from module2_link_fp_targets.
n_cores

Number of worker cores; NULL uses all available cores.
verbose

Emit concise progress messages.

Value

An FP-target correlation table with pass flags.

Correlate TF expression with target gene expression

Description

Correlate TF expression with target gene expression

Usage

module2_correlate_tf_targets(module2_inputs, n_cores = NULL, verbose = TRUE)

Arguments

module2_inputs

Output from module2_identify_candidate_links.
n_cores

Number of worker cores; NULL uses all available cores.
verbose

Emit concise progress messages.

Value

A TF-target correlation table with pass flags.

Link TFs to potential target genes based on TFBS-TSS proximity or 3D interaction data

Description

Link TFs to potential target genes based on TFBS-TSS proximity or 3D interaction data

Usage

module2_identify_candidate_links(
  multiomic_data,
  predicted_tfbs,
  gene_tss = NULL,
  regulatory_prior = NULL,
  project_config = NULL,
  max_distance_bp = NULL,
  verbose = TRUE
)

Arguments

multiomic_data

CraftGRN multiomic object.
predicted_tfbs

Predicted TFBS table or path from Module 1.
gene_tss

Optional gene TSS table or path.
regulatory_prior

Optional generic FP-target prior.
project_config

Optional project config path or list.
max_distance_bp

Maximum signed distance to TSS.
verbose

Emit concise progress messages.

Value

A list of normalized Module 2 inputs used by downstream step functions.

Build restricted candidate FP-target links

Description

Build restricted candidate FP-target links

Usage

module2_link_fp_targets(module2_inputs, tf_target_corr, verbose = TRUE)

Arguments

module2_inputs

Output from internal Module 2 input preparation.
tf_target_corr

Output from module2_correlate_tf_targets.
verbose

Emit concise progress messages.

Value

A candidate table restricted by TF-target pass calls and genomic priors.

Assemble, filter, and output final predicted TF-FP-target links

Description

Assemble, filter, and output final predicted TF-FP-target links

Usage

module2_output_predicted_links(
  module2_inputs,
  candidates,
  tf_target_corr,
  fp_target_corr,
  output_dir = NULL,
  output_format = c("auto", "parquet", "csv"),
  verbose = TRUE
)

Arguments

module2_inputs

Output from [module2_identify_candidate_links()].
candidates

Candidate table from [module2_link_fp_targets()].
tf_target_corr

TF-target correlation table from [module2_correlate_tf_targets()].
fp_target_corr

FP-target correlation table from [module2_correlate_fp_targets()].
output_dir

Optional output directory.
output_format

One of auto, parquet, or csv.
verbose

Emit concise progress messages.

Value

A Module 2 result list.

Construct input documents for topic modeling

Description

Builds and caches the document-level link table, document-term table, sparse document-term matrix, and summary metadata used by Module 3 topic modeling.

Usage

module3_construct_docs(
  filtered_dir,
  output_dir,
  tf_cluster_map = NULL,
  check_repeated_values = FALSE,
  ...
)

Arguments

filtered_dir

Directory containing Module 3 filtered differential-link CSV files.
output_dir

Directory where topic input caches are written.
tf_cluster_map

Named vector mapping TF names to motif clusters.
check_repeated_values

Warn about repeated inconsistent term values. The high-throughput default is 'FALSE'; set to 'TRUE' for diagnostic audits.
...

Additional topic-document construction arguments passed to the internal Module 3 document builder.

Value

A list with cache paths and input summary counts.

Extract Module 3 regulatory topics

Description

Public step function for extracting regulatory topics, pathway summaries, topic-link tables, and review outputs from trained Module 3 topic models.

Usage

module3_extract_topics(
  k,
  model_dir,
  output_dir,
  flatten_single_output = TRUE,
  ...
)

Arguments

k

Integer K selected for extraction.
model_dir

Directory containing trained topic model outputs.
output_dir

Directory to write extracted topic outputs.
flatten_single_output

Whether to write a single selected model directly under 'output_dir'. Defaults to 'TRUE' for the public step API.
...

Additional arguments passed to the internal extraction engine, such as 'backend', 'doc_mode', 'weight_label', and 'topic_report_args'.

Value

Invisibly returns TRUE when extraction completes.

Prepare differential links for Module 3

Description

Converts Module 2 link manifests into the filtered differential-link files consumed by CraftGRN topic-modeling utilities. This avoids writing full per-condition GRN matrices and keeps Module 3 compatible with the existing '*_filtered_links_up.csv' and '*_filtered_links_down.csv' contract.

Usage

module3_prepare_differential_links(
  module2,
  multiomic_data,
  compar = NULL,
  project_config = NULL,
  output_dir = NULL,
  n_cores = NULL,
  pseudocount = 1,
  rna_de_results = NULL,
  fp_signal_mode = NULL,
  overwrite = FALSE,
  verbose = TRUE
)

Arguments

module2

Module 2 object returned by [predict_tf_targets()] or a path to a Module 2 output directory containing 'module2_manifest.csv'.
multiomic_data

CraftGRN multiomic object returned by [load_prep_multiomic_data()].
compar

Comparison table or CSV path with 'cond1_label' and 'cond2_label'. If 'NULL', 'data/episcope_comparisons.csv' under 'base_dir' is used.
project_config

Project config list or YAML path.
output_dir

Directory for filtered differential links. If 'NULL', 'regulatory_topics/differential_links' under 'base_dir' is used.
n_cores

Number of data.table threads to use while reading and joining chunks. Defaults to all available cores. Comparison-level parallelism is controlled by 'module3_comparison_workers' in the project config and defaults to 1 for RAM safety.
pseudocount

Pseudocount for log2 fold-change calculations.
rna_de_results

Optional standardized RNA differential expression table or CSV. When provided, target-gene and TF log2 fold changes are read from this table and direct condition fold changes are used only for missing genes.
fp_signal_mode

FP signal used for differential FP fold changes. actual uses the measured FP score in both conditions. link_padded sets the FP score to zero in conditions where the TF-FP-gene link is not active before calculating delta_fp_score and log2FC_fp_score.
overwrite

Overwrite existing filtered link files.
verbose

Emit concise progress messages.

Value

A tibble manifest with one row per comparison.

Train Module 3 topic models

Description

Public step function for training one Module 3 topic-model setup after [module3_prepare_differential_links()] has produced filtered differential links. This is a thin Module 3-named wrapper around the internal training engine.

Usage

module3_train_topic_models(
  k_grid,
  filtered_dir,
  output_dir,
  flat_output = TRUE,
  ...
)

Arguments

k_grid

Integer vector of K values for training.
filtered_dir

Directory containing Module 3 filtered differential-link files.
output_dir

Directory to write topic model outputs.
flat_output

Whether to write this selected setup directly under 'output_dir'. Defaults to 'TRUE' for the public step API.
...

Additional arguments passed to the internal training engine, such as 'doc_design', 'fp_term_mode', 'backend', and 'local_threads'.

Value

Invisibly returns TRUE when training completes.

Output predicted TFBS

Description

Output predicted TFBS

Usage

output_predicted_tfbs(
  prediction_stats,
  out_dir = NULL,
  output_format = c("auto", "parquet", "csv"),
  include_support = TRUE
)

Arguments

prediction_stats

Module 1 TFBS prediction statistic table.
out_dir

Optional output directory. If supplied, a predicted TFBS table and manifest are written for Module 2.
output_format

Output format: auto, parquet, or csv.
include_support

Include compact condition support when available.

Value

A predicted TFBS tibble when 'out_dir' is NULL; otherwise a list with output paths and row counts.

Predict TF targets through TFBS-target and TF-target correlations

Description

Predict TF targets through TFBS-target and TF-target correlations

Usage

predict_tf_targets(
  multiomic_data,
  predicted_tfbs,
  gene_tss = NULL,
  regulatory_prior = NULL,
  project_config = NULL,
  output_dir = NULL,
  max_distance_bp = NULL,
  n_cores = NULL,
  output_format = c("auto", "parquet", "csv"),
  verbose = TRUE,
  write_qc_report = TRUE,
  qc_report_validate = FALSE
)

Arguments

multiomic_data

CraftGRN multiomic object returned by 'load_prep_multiomic_data()'.
predicted_tfbs

Compact Module 1 predicted TFBS table or manifest path.
gene_tss

Optional gene TSS annotation table or path. If 'NULL', the table is resolved from 'project_config$gene_tss' or generated from the configured 'ref_genome'.
regulatory_prior

Optional generic FP-target regulatory prior.
project_config

Optional project YAML path or list.
output_dir

Optional output directory.
max_distance_bp

Maximum signed distance to TSS for window candidates.
n_cores

Number of CPU cores.
output_format

Output format: auto, parquet, or csv.
verbose

Emit concise progress messages.
write_qc_report

Write a Module 2 HTML QC report when 'output_dir' is supplied.
qc_report_validate

Run relational integrity checks in the automatic QC report.

Value

Compact Module 2 relational result list.

Predict transcription factor binding sites from matched footprint and RNA data

Description

Run the Module 1 TFBS workflow as one user-facing operation. The function first uses motif-supported FP-TF correlations to define high-confidence footprints, then predicts sparse FP-TF binding events for expressed TFs.

Usage

predict_tfbs(
  omics_data,
  out_dir = "predict_tf_binding_sites",
  db = "JASPAR2024",
  label_col = NULL,
  r_cutoff = 0.3,
  p_cutoff = NULL,
  fdr_cutoff = NULL,
  filter_to_canonical_bound = TRUE,
  tf_subset = NULL,
  write_outputs = TRUE,
  write_stats = FALSE,
  write_bed = FALSE,
  write_qc_report = TRUE,
  qc_report_scan = FALSE,
  output_format = c("csv", "parquet", "auto"),
  return_prediction_stats = NULL,
  prediction_return_limit = getOption("craftgrn.module1_prediction_return_limit", 5e+06),
  min_non_na = 3L,
  cores = NULL,
  verbose = TRUE,
  time_log = verbose
)

Arguments

omics_data

CraftGRN multiomic object returned by 'load_prep_multiomic_data()'.
out_dir

Output directory.
db

Motif database label used in output metadata.
label_col

Metadata column used to build condition-level matrices when missing from 'omics_data'.
r_cutoff

Minimum positive correlation used for motif-supported and prediction calls.
p_cutoff

Optional best-method p-value cutoff. If 'NULL', p-value filtering is disabled.
fdr_cutoff

Optional best-method adjusted p-value cutoff. If 'NULL', FDR filtering is disabled.
filter_to_canonical_bound

Logical; if 'TRUE', only footprints with at least one motif-supported TF passing the cutoffs are used for the all-expressed-TF prediction stage.
tf_subset

Optional TF subset.
write_outputs

Write Module 1 output files.
write_stats

Retain and write full FP-TF correlation statistics.
write_bed

Write optional BED-like browser files for high-confidence footprints and in-memory TFBS prediction statistics.
write_qc_report

Write a Module 1 HTML QC report when outputs are written.
qc_report_scan

Scan predicted TFBS chunks for top-TF summaries in the QC report.
output_format

Output format for large streamed TFBS prediction statistic chunks.
return_prediction_stats

Return the TFBS prediction statistic table in memory. If 'NULL', large output-writing runs are streamed to disk and return a manifest.
prediction_return_limit

Maximum number of predicted events to keep in memory when 'return_prediction_stats = NULL' and 'write_outputs = TRUE'.
min_non_na

Minimum finite condition pairs required for correlation.
cores

Number of worker cores for the dense prediction correlation step. If 'NULL', use available cores.
verbose

Emit concise progress messages.
time_log

Logical; if TRUE, emit elapsed-time messages.

Value

A list containing 'omics_data', 'high_confidence_footprints', 'motif_supported_correlations', 'prediction_stats', 'prediction_stats', 'reports', and 'parameters'.

Query specific links by TF(s) and/or distance to TSS

Description

Query specific links by TF(s) and/or distance to TSS

Usage

query_predicted_links(
  module2,
  tf = NULL,
  fp_id = NULL,
  target_gene = NULL,
  max_distance_to_tss = NULL,
  pass_only = TRUE
)

Arguments

module2

Module 2 result list or loaded output list.
tf

Optional TF filter.
fp_id

Optional FP filter.
target_gene

Optional target-gene filter.
max_distance_to_tss

Optional maximum absolute distance to TSS.
pass_only

Keep only passing links.

Value

A tibble of matching final links.

Export an interactive HTML browser of direct TF-TF regulations

Description

Export an interactive HTML browser of direct TF-TF regulations

Usage

report_direct_tf_tf_regulations(
  module2,
  output_dir,
  multiomic_data = NULL,
  k_values = c(5L, 7L, 10L),
  verbose = TRUE
)

Arguments

module2

Module 2 result list, loaded output list, or output directory.
output_dir

Output directory.
multiomic_data

Optional CraftGRN multiomic object for condition-filtered reports.
k_values

Cluster counts.
verbose

Emit concise progress messages.

Value

A tibble report manifest.

Export an interactive HTML browser of TF-TF co-regulatory activities

Description

Export an interactive HTML browser of TF-TF co-regulatory activities

Usage

report_tf_tf_coregulations(
  module2,
  output_dir,
  multiomic_data = NULL,
  k_values = c(5L, 7L, 10L),
  verbose = TRUE
)

Arguments

module2

Module 2 result list, loaded output list, or output directory.
output_dir

Output directory.
multiomic_data

Optional CraftGRN multiomic object for condition-filtered reports.
k_values

Cluster counts.
verbose

Emit concise progress messages.

Value

A tibble report manifest.

Export an interactive HTML browser of individual TF regulons

Description

Export an interactive HTML browser of individual TF regulons

Usage

report_top_tf_targets(module2, output_dir, tfs, top_n = 100L, verbose = TRUE)

Arguments

module2

Module 2 result list, loaded output list, or output directory.
output_dir

Output directory.
tfs

TFs to report.
top_n

Number of top targets per TF.
verbose

Emit concise progress messages.

Value

A tibble report manifest.

Run the Shiny Application

Description

Run the Shiny Application

Usage

run_app(
  onStart = NULL,
  options = list(),
  enableBookmarking = NULL,
  uiPattern = "/",
  ...
)

Arguments

onStart

A function that will be called before the app is actually run. This is only needed for shinyAppObj, since in the shinyAppDir case, a global.R file can be used for this purpose.
options

Named options that should be passed to the runApp call (these can be any of the following: "port", "launch.browser", "host", "quiet", "display.mode" and "test.mode"). You can also specify width and height parameters which provide a hint to the embedding environment about the ideal height/width for the app.
enableBookmarking

Can be one of "url", "server", or "disable". The default value, NULL, will respect the setting from any previous calls to enableBookmarking(). See enableBookmarking() for more information on bookmarking your app.
uiPattern

A regular expression that will be applied to each GET request to determine whether the ui should be used to handle the request. Note that the entire request path must match the regular expression in order for the match to be considered successful.
...

arguments to pass to golem_opts. See '?golem::get_golem_options' for more details.

Run topic modeling

Description

Wrapper function to conduct the full regulatory topic-modeling workflow for one selected topic-document construction method.

Usage

run_topic_modeling(
  filtered_dir,
  multiomic_data = NULL,
  comparisons,
  output_dir,
  project_config = NULL,
  method = NULL,
  k_grid = NULL,
  warplda_iterations = NULL,
  topic_link_output = NULL,
  vae_device = NULL,
  vae_batch_size = NULL,
  pathway_backend = NULL,
  ...
)

Arguments

filtered_dir

Directory containing Module 3 filtered differential-link files.
multiomic_data

Optional CraftGRN multiomic object. Required when 'replicate_documents = TRUE'.
comparisons

Comparison or condition grouping table, or a CSV path.
output_dir

Topic output directory.
project_config

Optional project YAML path or config list. When supplied, 'topic_method', 'topic_k' or 'topic_k_grid', 'warplda_iterations', and 'topic_link_output' are used for arguments that are left as 'NULL'.
method

Single Module 3 method ID. If 'NULL', read from 'project_config' or use the package default.
k_grid

Integer topic numbers. If 'NULL', read from 'project_config' or use '10'.
warplda_iterations

Number of native WarpLDA iterations. If 'NULL', read from 'project_config' or use '2000'.
topic_link_output

Topic-link output mode. If 'NULL', read from 'project_config' or use '"pass"'.
vae_device

VAE device, for example '"auto"', '"cpu"', or '"cuda"'. If 'NULL', read from 'project_config' or use '"auto"'.
vae_batch_size

VAE mini-batch size. If 'NULL', read from 'project_config' or use '64'.
pathway_backend

Pathway enrichment backend. Use '"enrichly"' for local cached enrichment or '"enrichr"' for the Enrichr web API. If 'NULL', read from 'project_config' or use '"enrichly"'.
...

Additional arguments passed to the internal topic-modeling wrapper.

Value

An invisible list with topic input/model/extraction paths, review outputs, and 'qc_report' when requested.

Save a multi-omic data object to disk

Description

Save a multi-omic data object to disk

Usage

save_omics_data(
  omics_data,
  file = NULL,
  out_dir = NULL,
  db = NULL,
  prefix = "omics_data",
  compress = "xz",
  verbose = TRUE
)

Arguments

omics_data

A multi-omic data list (e.g., output of load_prep_multiomic_data()).
file

Optional full path to an RDS file. If NULL, uses out_dir/db/prefix.
out_dir

Output directory used when file is NULL.
db

Optional database tag appended to the filename when file is NULL.
prefix

Filename prefix used when file is NULL.
compress

Compression passed to saveRDS().
verbose

Emit status messages.

Value

Path to the written file (invisible).

Validate config values

Description

Ensures required config keys (e.g. thresholds and db) exist in the chosen environment before running pipelines.

Usage

validate_config(
  required = c("db", "ref_genome", "threshold_expr", "threshold_fp_score",
    "threshold_fp_tf_corr_r", "link_window_bp", "threshold_rna_gene_corr_r",
    "threshold_fp_gene_corr_r"),
  numeric_required = c("threshold_expr", "threshold_fp_score", "threshold_fp_tf_corr_r",
    "link_window_bp", "threshold_rna_gene_corr_r", "threshold_fp_gene_corr_r"),
  env = .craftgrn_state
)

Arguments

required

Character vector of required variable names.
numeric_required

Character vector of required numeric variable names.
env

Environment to check. Defaults to the internal CraftGRN config state.

Value

TRUE invisibly when validation passes.

Export an interactive HTML browser of differential GRNs

Description

Builds an interactive TF-to-gene network browser from Module 3 filtered differential links. Users can select a comparison, choose up or down differential links, adjust the number of top TFs and links to display, and inspect footprint-supported edge evidence in tooltips.

Usage

visualize_differential_grns(
  differential_links_dir,
  output_dir = file.path(differential_links_dir, "reports"),
  top_tf_n = 10L,
  top_link_n = 300L,
  default_direction = "up",
  browser_max_rows_per_file = 50000L,
  top_n = NULL,
  verbose = TRUE
)

Arguments

differential_links_dir

Module 3 differential-link directory.
output_dir

Directory where the browser HTML and CSV summaries are written.
top_tf_n

Default number of top TFs shown in the browser.
top_link_n

Default number of top TF-to-gene links shown in the browser.
default_direction

Initial direction selected in the browser.
browser_max_rows_per_file

Maximum filtered-link rows read from each comparison/direction file when building the browser payload. The full filtered-link CSVs remain the authoritative data source; this cap keeps the self-contained HTML browser responsive for large projects.
top_n

Deprecated compatibility alias for top_tf_n.
verbose

Emit concise progress messages.

Value

Path to the HTML browser.

Export interactive HTML browsers of topic modeling results

Description

Builds a self-contained index browser for existing Module 3 topic-modeling review outputs at the topic, condition, comparison, and pathway levels. This function organizes existing outputs and does not train or extract models.

Usage

visualize_topic_modeling_results(
  topic_dir,
  output_dir = file.path(topic_dir, "reports"),
  include = c("topic", "condition", "comparison", "pathway"),
  verbose = TRUE
)

Arguments

topic_dir

Module 3 topic output directory.
output_dir

Directory where the browser HTML and manifest are written.
include

Existing output families to include.
verbose

Emit concise progress messages.

Value

Path to the HTML browser.