XiaoTaoWang / NeoLoopFinder

A computation framework for genome-wide detection of enhancer-hijacking events from chromatin interaction data in re-arranged genomes
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neoloop-caller error #40

Closed ldyyzhangh closed 1 year ago

ldyyzhangh commented 1 year ago

Hi Xiaotao, I installed NeoLoopFinder and all the dependencies on 2022-11-11, when i run neoloop-caller,error occur: **# ARGUMENT LIST:

Output Path = sample_loops.txt

Cache Folder = CACHEFOLDER

SV assembly = sample.assemblies.txt

Cooler List = ['output.mcool::/resolutions/5000']

Extended Genomic Span = 3000000bp

Balance Type = ICE

Probability threshold = 0.9

No pooling = False

Minimum marginal peaks = 2

Number of Processes = 1

Log file name = neoloop.log

Traceback (most recent call last): File "/home/data/vip02/miniconda3/envs/neoloop/bin/neoloop-caller", line 131, in run models_by_res = download_peakachu_models(cachefolder, cools) File "/home/data/vip02/miniconda3/envs/neoloop/bin/neoloop-caller", line 258, in download_peakachu_models subprocess.check_call(' '.join(command), shell=True) File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/subprocess.py", line 369, in check_call raise CalledProcessError(retcode, cmd) subprocess.CalledProcessError: Command 'wget -O /home/data/vip02/HIC/neoloops/CACHEFOLDER/peakachu_v2.res5000.depth50000000.pkl -L http://3dgenome.fsm.northwestern.edu/peakachu/high-confidence.50million.5kb.w6.pkl' returned non-zero exit status 8.**

Then I download the ".pkl" files from "https://github.com/XiaoTaoWang/NeoLoopFinder/tree/master/neoloop/data" and put the mode into "CACHEFOLDER" ,new error occur:

**# ARGUMENT LIST:

Output Path = sample_loops.txt

Cache Folder = CACHEFOLDER

SV assembly = sample.assemblies.txt

Cooler List = ['output.mcool::/resolutions/5000']

Extended Genomic Span = 3000000bp

Balance Type = ICE

Probability threshold = 0.9

No pooling = True

Minimum marginal peaks = 2

Number of Processes = 1

Log file name = neoloop.log

root INFO @ 11/11/22 21:34:03: Load assembled SVs root INFO @ 11/11/22 21:34:03: Current resolution: 5000 root INFO @ 11/11/22 21:34:03: Calculate the global average contact frequencies at each genomic distance ... root INFO @ 11/11/22 21:36:20: Done Traceback (most recent call last): File "/home/data/vip02/miniconda3/envs/neoloop/bin/neoloop-caller", line 157, in run results = Parallel(n_jobs=args.nproc, verbose=10)(delayed(pipeline)(i) for i in Params) File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/joblib/parallel.py", line 1046, in call while self.dispatch_one_batch(iterator): File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/joblib/parallel.py", line 861, in dispatch_one_batch self._dispatch(tasks) File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/joblib/parallel.py", line 779, in _dispatch job = self._backend.apply_async(batch, callback=cb) File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/joblib/_parallel_backends.py", line 208, in apply_async result = ImmediateResult(func) File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/joblib/_parallel_backends.py", line 572, in init self.results = batch() File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/joblib/parallel.py", line 262, in call return [func(args, *kwargs) File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/joblib/parallel.py", line 262, in return [func(args, kwargs) File "/home/data/vip02/miniconda3/envs/neoloop/bin/neoloop-caller", line 202, in pipeline core.load_models(models_by_res[fu.res]) File "/home/data/vip02/miniconda3/envs/neoloop/lib/python3.10/site-packages/neoloop/callers.py", line 577, in load_models self.w = int((np.sqrt(self.model.featureimportances.size) - 1) / 2) AttributeError: 'dict' object has no attribute 'featureimportances'

I don't know what happens?

XiaoTaoWang commented 1 year ago

Hi, there were some issues on our server. We have fixed them, can you try again?

Xiaotao

ldyyzhangh commented 1 year ago

It works well. Thanks!