binarize function error

[apal6]

Hi,

I have been trying to look for tutorials to do the downstream analysis from the outputs i got from the pyscenic. I have three files:
regulons.csv
expr_mat.adjacencies.tsv
auc_mtx.csv
and exprMat_T.tsv (expression matrix)
I was trying to run the binarize function but it gave this error-

auc_matrix = pd.read_csv("/scratch/users/apal6/scenic/auc_mtx.csv") auc_mtx_bi = binarize(auc_matrix)
error:
`The above exception was the direct cause of the following exception:

UFuncTypeError Traceback (most recent call last)
/tmp/ipykernel_5764/2213639410.py in
----> 1 auc_mtx_bi = binarize(auc_matrix)

~/.local/lib/python3.9/site-packages/pyscenic/binarization.py in binarize(auc_mtx, threshold_overides, seed, num_workers)
92 return pd.Series(index=auc_mtx.columns, data=thrs)
93
---> 94 thresholds = derive_thresholds(auc_mtx)
95 if threshold_overides is not None:
96 thresholds[list(threshold_overides.keys())] = list(threshold_overides.values())

~/.local/lib/python3.9/site-packages/pyscenic/binarization.py in derive_thresholds(auc_mtx, seed)
87 def derive_thresholds(auc_mtx, seed=seed):
88 with Pool(processes=num_workers) as p:
---> 89 thrs = p.starmap(
90 derive_threshold, [(auc_mtx, c, seed) for c in auc_mtx.columns]
91 )

/share/software/user/open/python/3.9.0/lib/python3.9/multiprocessing/pool.py in starmap(self, func, iterable, chunksize)
370 func and (a, b) becomes func(a, b).
371 '''
--> 372 return self._map_async(func, iterable, starmapstar, chunksize).get()
373
374 def starmap_async(self, func, iterable, chunksize=None, callback=None,

/share/software/user/open/python/3.9.0/lib/python3.9/multiprocessing/pool.py in get(self, timeout)
769 return self._value
770 else:
--> 771 raise self._value
772
773 def _set(self, i, obj):

/share/software/user/open/python/3.9.0/lib/python3.9/multiprocessing/pool.py in worker()
123 job, i, func, args, kwds = task
124 try:
--> 125 result = (True, func(*args, **kwds))
126 except Exception as e:
127 if wrap_exception and func is not _helper_reraises_exception:

/share/software/user/open/python/3.9.0/lib/python3.9/multiprocessing/pool.py in starmapstar()
49
50 def starmapstar(args):
---> 51 return list(itertools.starmap(args[0], args[1]))
52
53 #

~/.local/lib/python3.9/site-packages/pyscenic/binarization.py in derive_threshold()
54 return gmm2.bic(X) <= gmm1.bic(X)
55
---> 56 if not isbimodal(data, method):
57 # For a unimodal distribution the threshold is set as mean plus two standard deviations.
58 return data.mean() + 2.0 * data.std()

~/.local/lib/python3.9/site-packages/pyscenic/binarization.py in isbimodal()
41 if method == "hdt":
42 # Use Hartigan's dip statistic to decide if distribution deviates from unimodality.
---> 43 _, pval, _ = diptst(np.msort(data))
44 return (pval is not None) and (pval <= 0.05)
45 else:

~/.local/lib/python3.9/site-packages/pyscenic/diptest.py in diptst()
52 """diptest with pval"""
53 # sample dip
---> 54 d, (_, idxs, left, _, right, _) = dip_fn(dat, is_hist)
55
56 # simulate from null uniform

~/.local/lib/python3.9/site-packages/pyscenic/diptest.py in dip_fn()
100
101 while True:
--> 102 left_part, left_touchpoints = gcm(work_cdf - work_histogram, work_idxs)
103 right_part, right_touchpoints = lcm(work_cdf, work_idxs)
104

~/.local/lib/python3.9/site-packages/pyscenic/diptest.py in gcm()
28 touchpoints = [0]
29 while len(work_cdf) > 1:
---> 30 distances = work_idxs[1:] - work_idxs[0]
31 slopes = (work_cdf[1:] - work_cdf[0]) / distances
32 minslope = slopes.min()

UFuncTypeError: ufunc 'subtract' did not contain a loop with signature matching types (dtype('<U20'), dtype('<U20')) -> None
`

It looks like something is clashing due to mismatch in a NumPy operation. I wonder if my inputs were processed in a way that pyscenic isnt optimised for? Any help? I would also appreciate if you could direct me to a tutorial to perform downstream analysis usign these outputs?

Thank you,
Aastha