SuperAPI AI Directory

cerna-analysis

Data & analytics

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Updated 10-15 16:43

About this skill

ceRNA Analysis

When to Use

Use this skill when you need to construct a ceRNA regulatory network from a known key-gene list using the bundled miRNA-mRNA and miRNA-lncRNA reference tables.

Use it for:

  • Building a ceRNA network from one gene list and exporting flat CSV plus PDF outputs
  • Comparing supported miRNA source modes such as combined, starbase, or pairwise overlaps
  • Re-running the same local workflow with different lncRNA strictness, layout, or plotting parameters

Do not use it for:

  • Differential expression, single-cell, enrichment, or survival analysis
  • Workflows that do not start from a key gene list
  • Cases where you want a miRNA-mRNA-only graph without a retained lncRNA ceRNA layer

Input Validation

This skill accepts:

  • A key gene list as a plain-text file (one gene symbol per line) or as a comma-separated string on the CLI
  • Optional parameter overrides for dataset mode, lncRNA strictness, layout, colors, and timeout

If the user's request does not involve building a ceRNA regulatory network from a key gene list — for example, asking to run differential expression, enrichment analysis, single-cell workflows, or survival analysis — do not proceed with the workflow. Instead respond:

"ceRNA Analysis is designed to construct a ceRNA regulatory network from a key gene list using bundled miRNA-mRNA and miRNA-lncRNA reference databases. Your request appears to be outside this scope. Please provide a key gene list and specify a supported miRNA dataset mode, or use a more appropriate skill for differential expression, enrichment analysis, or single-cell workflows."

When to Read External Files

Situation File to Read Purpose
Need algorithm details references/algorithm.md ceRNA construction logic, dataset combinations, filtering rules. Includes worked examples of pairwise intersection network size vs combined mode.
Need to run analysis scripts/main.R Execute: Rscript scripts/main.R --key_genes ... --output_dir .... Note: --help requires igraph to be installed.
Encounter errors references/troubleshooting.md Common errors and solutions
Need CLI examples references/cli-guide.md Detailed local run examples with measured outputs
Need test data tests/data/ Sample key-gene input for testing

Usage

Rscript scripts/main.R \
  --key_genes tests/data/gene.txt \
  --output_dir ./output/ \
  --mirna_dataset combined \
  --lncrna_strictness High \
  --lncrna_freq_thresh 0 \
  --timeout_seconds 600 \
  --seed 42

Dependency note: --help and all analysis modes require igraph to be installed. Install igraph before running any command. Use references/troubleshooting.md for installation guidance.

Arguments

Main Analysis: scripts/main.R

Short Long Type Default Description
-i --key_genes character required Key gene file path or comma-separated gene names
-o --output_dir character ./output/ Output directory
-m --mirna_dataset character combined Dataset: combined, starbase, mirdb, mirtarbase, starbase+mirdb, starbase+mirtarbase, mirdb+mirtarbase
-l --lncrna_strictness character High lncRNA interaction strictness: Low, Median, High
-f --lncrna_freq_thresh integer 0 Minimum retained lncRNA frequency
-r --reference_dir character file.path(script_dir, "..", "references", "database") Database directory
--plot_width double 12 PDF width in inches
--plot_height double 8 PDF height in inches
--layout_type character kk Layout: kk, fr, nicely, circle, grid, randomly
--mrna_color character #D16BA5 mRNA node color
--lncrna_color character #008dcd lncRNA node color
--mirna_color character #00c9a7 miRNA node color
--node_size_base double 15 Base node size
--label_size double 0.8 Node label size
--show_legend logical TRUE Show legend in the PDF
-t --timeout_seconds integer 3600 Elapsed timeout limit
-s --seed integer 42 Random seed for reproducibility

Input Format

Key Genes (key_genes)

Plain-text input with one gene symbol per line, or a comma-separated string passed directly on the CLI.

TP53
BRCA1
MYC

Rules:

  • Blank lines are ignored
  • Lines starting with # are ignored
  • Duplicate genes are removed
  • At least one valid gene is required

Database Directory (reference_dir)

The bundled database directory is references/database/. Required files depend on the selected mirna_dataset plus the selected lncRNA strictness file.

  • combined: miRNA_mRNA.csv
  • starbase: starbase_miRNA_mRNA.csv
  • mirdb: miRDB_miRNA_mRNA.csv
  • mirtarbase: miRTarbase_miRNA_mRNA.csv
  • starbase+mirdb: starbase_miRNA_mRNA.csv and miRDB_miRNA_mRNA.csv
  • starbase+mirtarbase: starbase_miRNA_mRNA.csv and miRTarbase_miRNA_mRNA.csv
  • mirdb+mirtarbase: miRDB_miRNA_mRNA.csv and miRTarbase_miRNA_mRNA.csv
  • lncRNA file: one of starbase_miRNA_lncRNA_High.csv, starbase_miRNA_lncRNA_Median.csv, or starbase_miRNA_lncRNA_Low.csv

Output Files

File Description
ceRNA_network_edges.csv Edge table with node1,node2 columns
ceRNA_network_nodes.csv Node table with node,type,degree columns
ceRNA_network.pdf ceRNA network visualization
session_info.txt R session details and loaded package versions

Workflow

Step 1: Validate Input

  • Check key-gene input existence or parse comma-separated genes
  • Validate parameter choices, numeric limits, timeout, and colors
  • Verify the database directory and required files

Step 2: Load Interaction Data

  • Load the selected miRNA-mRNA dataset
  • Load the selected miRNA-lncRNA dataset by strictness level
  • Recompute pairwise intersections when requested

Step 3: Filter the Network

  • Retain miRNA-mRNA pairs linked to the provided key genes
  • Retain miRNA-lncRNA pairs connected to the retained miRNAs
  • Apply the lncRNA frequency threshold
  • Stop with SKILL_INVALID_DATA if no lncRNA interactions remain after filtering, because the ceRNA layer has collapsed

Step 4: Build Outputs

  • Construct edge and node tables
  • Save CSV, PDF, and session information in the output directory root

Methods

combined

Uses the bundled precomputed overlap across three miRNA-mRNA resources for higher-confidence interactions.

Pairwise Intersections

starbase+mirdb, starbase+mirtarbase, and mirdb+mirtarbase recompute the overlap between two bundled databases. Pairwise intersections typically yield 20–40% fewer edges than combined mode because only interactions present in both selected databases are retained. Use pairwise modes when you need higher-confidence edges at the cost of reduced network coverage.

lncRNA Strictness

High, Median, and Low select different bundled starBase evidence levels for miRNA-lncRNA interactions.

Examples

Basic Combined Analysis

Rscript scripts/main.R \
  -i ./key_genes.txt \
  -o ./output \
  -m combined

Single Database Analysis

Rscript scripts/main.R \
  -i ./key_genes.txt \
  -o ./output_starbase \
  -m starbase \
  -l Median \
  -f 1

Error Handling

Error Cause Solution
SKILL_FILE_NOT_FOUND Input file or database file is missing Check the file path or bundled database directory
SKILL_EMPTY_FILE A required file exists but has no content Replace or regenerate the file
SKILL_EMPTY_DATA A required reference table has no usable rows Verify the input content and regenerate the file if needed
SKILL_MISSING_COLUMNS An input table lacks required columns Verify the expected schema
SKILL_INVALID_PARAMETER An invalid CLI value was provided Use one of the documented parameter values
SKILL_INVALID_DATA The input data cannot build a valid ceRNA network, or lncRNA filtering removes the ceRNA layer entirely Verify the key genes and database files, then lower --lncrna_freq_thresh or choose a different dataset / strictness
SKILL_DEPENDENCY_MISSING A required package is not installed (igraph required for all modes including --help) Install the missing package before running any command
SKILL_TIMEOUT The run exceeded the timeout limit Increase --timeout_seconds
SKILL_RUNTIME_ERROR An unexpected runtime failure occurred Re-run after checking the console error message

IF error persists, READ: references/troubleshooting.md

Testing

Test with Sample Data

# Run with sample data (igraph must be installed first)
Rscript scripts/main.R \
  -i tests/data/gene.txt \
  -o tests/output/

Validation Commands

# Inspect edge output
wc -l tests/output/ceRNA_network_edges.csv

# Check plot exists
ls -la tests/output/ceRNA_network.pdf