Hi
I am analyzing ATAC-seq data and want to visualize GC bias using the DeepTools function "computeGCBias". However, I always get a number of warnings and lastly an error.
deepTools version: 3.3.0
python version: 3.6.7
Command:
computeGCBias -b sample.bam --effectiveGenomeSize 2862010578 -g hg38.2bit -freq sample_GCfreq.txt -bl hg38-blacklist.v2.bed -p 8 --biasPlot sample_GCbias.png -v
The complete output to the terminal is way to large to paste in here, but I will give some examples of the problems I encountered. To begin with, I get warnings according to the following (many lines):
WARNING: too many NNNs present in chr1:16799045-16799187
WARNING: too many NNNs present in chr1:16799110-16799252
WARNING: too many NNNs present in chr1:16799175-16799317
WARNING: too many NNNs present in chr1:16799240-16799382
WARNING: too many NNNs present in chr1:16799305-16799447
.
.
.
This is somewhat surprising to me, because previously the FastQC reported that there was very low amount of Ns in my raw sequencing data files. I am not sure whether this pose any problems though.
Secondly, the process ends with the following error:
Traceback (most recent call last):
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/multiprocessing/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/multiprocessing/pool.py", line 44, in mapstar
return list(map(*args))
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/site-packages/deeptools/computeGCBias.py", line 234, in tabulateGCcontent_wrapper
return tabulateGCcontent_worker(*args)
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/site-packages/deeptools/computeGCBias.py", line 388, in tabulateGCcontent_worker
index, index / (endTime - countTime),
UnboundLocalError: local variable 'index' referenced before assignment
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/simso02/anaconda2/envs/Py2.7/bin/computeGCBias", line 12, in
main(args)
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/site-packages/deeptools/computeGCBias.py", line 712, in main
region=args.region)
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/site-packages/deeptools/computeGCBias.py", line 433, in tabulateGCcontent
region=region)
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/site-packages/deeptools/mapReduce.py", line 142, in mapReduce
res = pool.map_async(func, TASKS).get(9999999)
File "/home/simso02/anaconda2/envs/Py2.7/lib/python3.6/multiprocessing/pool.py", line 670, in get
raise self._value
UnboundLocalError: local variable 'index' referenced before assignment
I am not sure how to interpret this. Any help would be highly appreciated.
I have tested increasing --sampleSize (as was suggested in #849), from the default 50 million to 100 and 500 million, but it still gives the same error as above.
Best regards,
Simon Söderholm
Hi
I am analyzing ATAC-seq data and want to visualize GC bias using the DeepTools function "computeGCBias". However, I always get a number of warnings and lastly an error.
deepTools version: 3.3.0
python version: 3.6.7
Command:
computeGCBias -b sample.bam --effectiveGenomeSize 2862010578 -g hg38.2bit -freq sample_GCfreq.txt -bl hg38-blacklist.v2.bed -p 8 --biasPlot sample_GCbias.png -vThe complete output to the terminal is way to large to paste in here, but I will give some examples of the problems I encountered. To begin with, I get warnings according to the following (many lines):
This is somewhat surprising to me, because previously the FastQC reported that there was very low amount of Ns in my raw sequencing data files. I am not sure whether this pose any problems though.
Secondly, the process ends with the following error:
I am not sure how to interpret this. Any help would be highly appreciated.
I have tested increasing --sampleSize (as was suggested in #849), from the default 50 million to 100 and 500 million, but it still gives the same error as above.
Best regards,
Simon Söderholm