Traceback (most recent call last):
File "/rds/user/mgm49/hpc-work/home/bin/wrath/sv_detection/sv_detection_and_heatmap.gmk.py", line 69, in
clustering = AgglomerativeClustering(n_clusters=None, distance_threshold=3, linkage='single').fit(points)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/base.py", line 1152, in wrapper
return fit_method(estimator, *args, kwargs)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/cluster/_agglomerative.py", line 978, in fit
X = self._validate_data(X, ensure_min_samples=2)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/base.py", line 605, in _validate_data
out = check_array(X, input_name="X", check_params)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/utils/validation.py", line 967, in check_array
raise ValueError(
ValueError: Found array with 1 sample(s) (shape=(1, 2)) while a minimum of 2 is required by AgglomerativeClustering.
/home/mgm49/rds/hpc-work/home/bin/wrath/wrath.gmk: line 290: Detecting SVs and plotting of matrix wrath_out/matrices/jaccard_matrix_100000_26_5125000_6806000_47.all.brazil.haplotagging.n93.txt step failed: No such file or directory
SOLUTION
Not sure, not sure which function exactly fails.
This is minor and irrelevant to most, unless the automatic SV function gets developed further to filter for large SVs only, for example, then you might encounter this situation more. Just thought I'd let you know.
When wrath only finds one SV with automatic detection, the program fails.
I noticed this when testing with very large window sizes, for speed.
RUN
OUTPUT
One outlier detected (not really an sv, close to diagonal etc- but not sure there is a filter to get rid of potential artifacts):
Heatmap plot is produced but with no SV plotted (maybe just using plot_heatmap.py, as mentioned in https://github.com/annaorteu/wrath/issues/7 ).
No SVs/ table is produced
ERROR
Traceback (most recent call last): File "/rds/user/mgm49/hpc-work/home/bin/wrath/sv_detection/sv_detection_and_heatmap.gmk.py", line 69, in
clustering = AgglomerativeClustering(n_clusters=None, distance_threshold=3, linkage='single').fit(points)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/base.py", line 1152, in wrapper
return fit_method(estimator, *args, kwargs)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/cluster/_agglomerative.py", line 978, in fit
X = self._validate_data(X, ensure_min_samples=2)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/base.py", line 605, in _validate_data
out = check_array(X, input_name="X", check_params)
File "/home/mgm49/miniconda3/lib/python3.8/site-packages/sklearn/utils/validation.py", line 967, in check_array
raise ValueError(
ValueError: Found array with 1 sample(s) (shape=(1, 2)) while a minimum of 2 is required by AgglomerativeClustering.
/home/mgm49/rds/hpc-work/home/bin/wrath/wrath.gmk: line 290: Detecting SVs and plotting of matrix wrath_out/matrices/jaccard_matrix_100000_26_5125000_6806000_47.all.brazil.haplotagging.n93.txt step failed: No such file or directory
SOLUTION
Not sure, not sure which function exactly fails.
This is minor and irrelevant to most, unless the automatic SV function gets developed further to filter for large SVs only, for example, then you might encounter this situation more. Just thought I'd let you know.