Datasets:

HarriziSaad
/

Nullomer

# Clone the repository
git clone https://huggingface.co/datasets/HarriziSaad/Nullomer
cd Nullomer

# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate       # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Running the Analysis

Option 1 — Full pipeline (recommended)

bash run_all.sh

This runs all six scripts in order and takes approximately 60–90 minutes on standard hardware. The main bottleneck is the NEM scanning in script 02 (~30–60 min depending on CPU).

Option 2 — Individual scripts

Run from the repo root. Scripts must be run in order as each depends on outputs from the previous one.

python scripts/01_nullomer_identification.py   # ~50 s
python scripts/02_nem_analysis.py              # ~30–60 min
python scripts/03_stress_element_analysis.py   # ~5 min
python scripts/04_thermodynamic_analysis.py    # ~2 min
python scripts/05_ml_and_network_analysis.py   # ~10 min
python scripts/06_statistical_synthesis.py     # ~1 min

What Each Script Does

Script	Analysis	Key output
`01`	Identifies all 11-mer nullomers in the S. cerevisiae R64-1-1 genome	`results/nullomers_k11.txt`
`02`	Finds NEMs across 26 ABC transporter genes and 1000 bp promoters	`results/nem_comprehensive_summary.csv`
`03`	Scans promoters for PDRE/STRE/HSE/AP-1; correlates with NEM density	`results/stress_element_nem_correlation.csv`
`04`	Computes ΔG and Tm for 10,000 nullomers vs random controls	`results/thermodynamic_summary.json`
`05`	Random Forest prediction, GP fitness landscape, STRING network	`results/ml_model_performance.json`
`06`	Hypothesis tests H1–H4 and Fisher's meta-analysis	`results/statistical_synthesis.json`

Expected Key Results

Verify your run matches the manuscript by checking these values in the output files:

`results/nullomers_k11.txt`

Line count: 463,220

`results/nem_comprehensive_summary.csv`

Total NEM count (sum of nem_count): 174,799
Promoter mean NEM density: 1,331.9 NEMs/kb
Gene body mean NEM density: 1,085.7 NEMs/kb
Promoter enrichment over gene body: 22.6%

`results/stress_element_nem_correlation.csv`

PDRE sites total: 30 across 8 genes
STRE sites total: 228
HSE sites total: 2,540
AP-1 sites total: 36

`results/thermodynamic_summary.json`

{
  "nullomer_Tm_mean": 41.73,
  "random_Tm_mean": 35.56,
  "nullomer_dG_mean": -13.96,
  "random_dG_mean": -12.13,
  "delta_dG_kcal_mol": 1.83,
  "boltzmann_fold_disadvantage": 19.4,
  "GC_Tm_pearson_r": 0.803,
  "pct_very_stable_nullomers": 99.7,
  "pct_hairpin": 22.4,
  "pct_g4": 1.0,
  "pct_imotif": 1.2
}

`results/ml_model_performance.json`

{
  "test_r2": 0.760,
  "test_rmse": 41.46,
  "cv_r2_mean": 0.717,
  "cv_r2_std": 0.045,
  "gp_r2": 0.896
}

`results/statistical_synthesis.json`

{
  "H2_PDRE_correlation": {
    "spearman_rho": 0.685,
    "spearman_p": 0.000111,
    "linear_slope_nems_per_pdre": 85.5
  },
  "H4_promoter_vs_gene": {
    "enrichment_pct": 22.6,
    "wilcoxon_p": 0.003
  },
  "meta_analysis_fishers": {
    "chi2_statistic": 51.32,
    "combined_p": 2.28e-08
  }
}

Data Sources

All data is downloaded automatically at runtime. No manual downloads are needed.

Resource	URL	Used by
S. cerevisiae genome R64-1-1	Ensembl release 110 FASTA	scripts 01, 02, 03
Gene annotations GFF3	Ensembl release 110 GFF3	scripts 02, 03
Protein interactions	STRING v11.5 API (TaxID 4932, score ≥ 400)	script 05

Troubleshooting

Download failures — If Ensembl is unreachable, retry or download manually:

https://ftp.ensembl.org/pub/release-110/fasta/saccharomyces_cerevisiae/dna/
https://ftp.ensembl.org/pub/release-110/gff3/saccharomyces_cerevisiae/

Place files in data/ and rename to match the filenames used in the scripts.

Memory errors during NEM scanning — Script 02 holds the genome and nullomer set in memory simultaneously (~2–3 GB). Close other applications or run on a machine with more RAM.

STRING API timeout — Script 05 will catch the error and proceed with an empty network. The network results will be absent from network_topology.csv but all other outputs are unaffected.

Missing dependencies — Reinstall cleanly:

pip install --upgrade --force-reinstall -r requirements.txt

Runtime Estimates

Script	Approximate time
01 Nullomer identification	50 seconds
02 NEM analysis	30–60 minutes
03 Stress element analysis	5 minutes
04 Thermodynamic analysis	2 minutes
05 ML and network analysis	10 minutes
06 Statistical synthesis	1 minute
Total	~60–90 minutes

Times measured on a standard laptop (8-core CPU, 16 GB RAM).

Getting Help

If results do not match expected values:

Confirm you are running Python 3.8+ and have installed all packages from requirements.txt
Check that scripts are run from the repo root, not from inside scripts/
Open an issue at https://huggingface.co/datasets/HarriziSaad/Nullomer/discussions with your Python version, OS, and the full error output

Citation

Harrizi S., Nait Irahal I., Kabine M. (2025). Forbidden Words: How Nullomer
Constraints Channel Regulatory Evolution in ABC Transporters.