ValueError when no reads (same as #3)

[kautto]

I'm still getting the same issues as described in #3 , when there are chromosomes that have no reads. I've had this occur both when looking at a single chromosome (in my case, chromosome 8) or when looking at whole genome data (in which case it gets to ...21>22>X>Y>MT and breaks).

  mu = data.mean()
/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/numpy-1.13.3-py2.7-linux-x86_64.egg/numpy/core/_methods.py:80: RuntimeWarning: invalid value encountered in double_scalars
  ret = ret.dtype.type(ret / rcount)
/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_distn_infrastructure.py:406: RuntimeWarning: Mean of empty slice.
  m2 = ((data - mu)**2).mean()
/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_distn_infrastructure.py:407: RuntimeWarning: Mean of empty slice.
  m3 = ((data - mu)**3).mean()
/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_distn_infrastructure.py:2286: RuntimeWarning: Mean of empty slice.
  muhat = tmp.mean()
/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_distn_infrastructure.py:2287: RuntimeWarning: Degrees of freedom <= 0 for slice
  mu2hat = tmp.var()
/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/numpy-1.13.3-py2.7-linux-x86_64.egg/numpy/core/_methods.py:105: RuntimeWarning: invalid value encountered in true_divide
  arrmean, rcount, out=arrmean, casting='unsafe', subok=False)
/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/numpy-1.13.3-py2.7-linux-x86_64.egg/numpy/core/_methods.py:127: RuntimeWarning: invalid value encountered in double_scalars
  ret = ret.dtype.type(ret / rcount)
Traceback (most recent call last):
  File "NAIBR.py", line 88, in <module>
    main()
  File "NAIBR.py", line 59, in main
    data = parallel_execute(run_NAIBR,chroms)
  File "src/utils.py", line 386, in parallel_execute
    data = map(function,input_list)
  File "NAIBR.py", line 33, in run_NAIBR
    cands,p_len,p_rate = get_candidates(discs,reads_by_LR)
  File "src/get_reads.py", line 150, in get_candidates
    p_len,p_rate,barcode_overlap = get_distributions(reads_by_LR)
  File "src/distributions.py", line 114, in get_distributions
    p_rate = get_rate_distr(LRs)
  File "src/distributions.py", line 139, in get_rate_distr
    alpha,loc,beta = scipy.stats.gamma.fit(rate)
  File "/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_continuous_distns.py", line 2011, in fit
    return super(gamma_gen, self).fit(data, *args, **kwds)
  File "/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_distn_infrastructure.py", line 2171, in fit
    start = self._fitstart(data)
  File "/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_continuous_distns.py", line 2000, in _fitstart
    return super(gamma_gen, self)._fitstart(data, args=(a,))
  File "/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_distn_infrastructure.py", line 2019, in _fitstart
    loc, scale = self._fit_loc_scale_support(data, *args)
  File "/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/scipy-0.18.1-py2.7-linux-x86_64.egg/scipy/stats/_distn_infrastructure.py", line 2239, in _fit_loc_scale_support
    data_a = np.min(data)
  File "/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/numpy-1.13.3-py2.7-linux-x86_64.egg/numpy/core/fromnumeric.py", line 2372, in amin
    out=out, **kwargs)
  File "/igm/apps/python/Python-2.7.12_install_static/lib/python2.7/site-packages/numpy-1.13.3-py2.7-linux-x86_64.egg/numpy/core/_methods.py", line 29, in _amin
    return umr_minimum(a, axis, None, out, keepdims)
ValueError: zero-size array to reduction operation minimum which has no identity

There's nothing odd about my config file:

# minimum mapping quality (default=40)
min_mapq=40

# input bam file
bam_file=./KAUTTO_Esko/data/17-0020-04_H1576_Tumor.chr8.bam

# output directory (default=.)
outdir=./KAUTTO_Esko/output/NAIBR/17-0020-04_H1576_Tumor/chr8

# list of intervals not to be intcluded in analysis (default=None)
blacklist=None

# list in BEDPE format of novel adjacencies to be scored by NAIBR (default=None)
candidates=None

# maximum distance between read-pairs in a linked-read (default=10000)
d=10000

# minimum size of structural variant (default=lmax)
min_sv=1000

# number of cores (default=1)
cores=4

# minimum number of barcode overlaps supporting a candidate NA (default = 3)
k=3

And I'm using the newest commit eb59166 , so that shouldn't be the issue.. any ideas? Thanks!

[kautto]

So the issue is specifically occuring in get_rate_distr() in distributions.py

The line

rate = rate[len(rate)/10:len(rate)/10*9]

causes nothing to be selected when you have < 10 entries in the input LRs list, because using integer math, you get 0:0 as your selection range, i.e.

rate[0:0*9] = rate[0:0] = []

and that's what causes the script to break a few lines later with the call to

scipy.stats.gamma.fit(rate)

[relyanow]

Thanks for finding the source of this bug. I'll fix it and push an update shortly!