Negative hic_gamma

[jenniferzev]

Hi!

I am running scE2G on multiome scRNAseq+scATAC seq data.
I have already run the ABC model in the past using bulk ATAC, HiC and H3K27ac data in the same cell type. I have estimated the contact powerlaw coefficient and I would like to used them when running scE2G.
I modified the parameters in the ABC submodule config file with my own powerlaw parameters but now I have an error message because the hic_gamma is negative.
I looked into the archived repositories of the ABC model to see what the gamma value should look like, but they are also all negative in the examples.
Any idea why that might happen ?

Thank you

-Jennifer

`[Wed Mar 4 10:48:48 2026]
rule abc_create_predictions:
input: /lustre06/project/6001867/jzev/programs/scE2G/results_powerlaw_NT/telohaec_tnfa_24hr/Neighborhoods/EnhancerList.txt, /lustre06/project/6001867/jzev/programs/scE2G/results_powerlaw_NT/telohaec_tnfa_24hr/Neighborhoods/GeneList.txt
output: /lustre06/project/6001867/jzev/programs/scE2G/results_powerlaw_NT/telohaec_tnfa_24hr/Predictions/EnhancerPredictionsAllPutative.tsv.gz, /lustre06/project/6001867/jzev/programs/scE2G/results_powerlaw_NT/telohaec_tnfa_24hr/Predictions/EnhancerPredictionsAllPutativeNonExpressedGenes.tsv.gz
jobid: 35
reason: Missing output files: /lustre06/project/6001867/jzev/programs/scE2G/results_powerlaw_NT/telohaec_tnfa_24hr/Predictions/EnhancerPredictionsAllPutative.tsv.gz; Input files updated by another job: /lustre06/project/6001867/jzev/programs/scE2G/results_powerlaw_NT/telohaec_tnfa_24hr/Neighborhoods/EnhancerList.txt, /lustre06/project/6001867/jzev/programs/scE2G/results_powerlaw_NT/telohaec_tnfa_24hr/Neighborhoods/GeneList.txt
wildcards: biosample=telohaec_tnfa_24hr
resources: tmpdir=/tmp, mem_mb=20000, mem_mib=19074

Activating conda environment: .snakemake/conda/779eb13256f0178b03b3d0d8ef47877a_
/lustre06/project/6001867/jzev/programs/scE2G/.snakemake/conda/779eb13256f0178b03b3d0d8ef47877a_/lib/python3.10/site-packages/pyranges/methods/init.py:45: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.
return {k: v for k, v in df.groupby(grpby_key)}
/lustre06/project/6001867/jzev/programs/scE2G/.snakemake/conda/779eb13256f0178b03b3d0d8ef47877a_/lib/python3.10/site-packages/pyranges/methods/init.py:45: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.
return {k: v for k, v in df.groupby(grpby_key)}
WARNING: Hi-C not provided. Model will only compute ABC score using powerlaw!
reading genes
reading enhancers
Making predictions for chromosome: chr1
Making putative predictions table...
Done. There are 1664174 putative enhancers for chromosome chr1
Elapsed time: 1.1991169452667236
Traceback (most recent call last):
File "/lustre06/project/6001867/jzev/programs/scE2G/ENCODE_rE2G/ABC/workflow/scripts/predict.py", line 312, in
main()
File "/lustre06/project/6001867/jzev/programs/scE2G/ENCODE_rE2G/ABC/workflow/scripts/predict.py", line 251, in main
this_chr = make_predictions(
File "/lustre06/project/6001867/jzev/programs/scE2G/ENCODE_rE2G/ABC/workflow/scripts/predictor.py", line 24, in make_predictions
pred = add_powerlaw_to_predictions(pred, args, hic_gamma, hic_scale)
File "/lustre06/project/6001867/jzev/programs/scE2G/ENCODE_rE2G/ABC/workflow/scripts/predictor.py", line 449, in add_powerlaw_to_predictions
pred["powerlaw_contact"] = get_powerlaw_at_distance(
File "/lustre06/project/6001867/jzev/programs/scE2G/ENCODE_rE2G/ABC/workflow/scripts/hic.py", line 258, in get_powerlaw_at_distance
assert gamma > 0
AssertionError`