copy_number -> copy_call bins inconsistent

[ymahlich]

There seem to be differences in how copy_number is converted to copy_call for HCMI in comparison to all other datasets.
Is there a specific reason for this or is this an oversight / bug? If this intentional, that does in turn mean that the copy_number value (not copy_call) won't be comparable between HCMI and other?

Maybe I am deeply misunderstanding something here but it seems odd to me.

I attached the code for every conversion below with references to the code itself below:

Broad Sanger (02-broadSangerOmics.R: lines 119-122):

dplyr::mutate(IMPROVE=ifelse(copy_number<0.5210507,'deep del',
                               ifelse(copy_number<0.7311832,'het loss',
                                      ifelse(copy_number<1.214125,'diploid',
                                             ifelse(copy_number<1.422233,'gain','amp')))))|>

CPTAC (getCptacData.py: lines 213-224):

    for a in arr:
        a = 2**float(a)
        if float(a) < 0.5210507:
            b = 'deep del'
        elif float(a) < 0.7311832:
            b = 'het loss'
        elif float(a) < 1.214125:
            b = 'diploid'
        elif float(a) <1.42233:
            b = 'gain'
        else:
            b = 'amp'

HCMI (02-getHCMIData.py: lines 479-488):

a_val = math.log2(float(a)+0.000001) ###this should not be exponent, should be log!!! 2**float(a)
if a_val < 0.0: #0.5210507:
          return 'deep del'
      elif a_val < 0.7311832:
          return 'het loss'
      elif a_val < 1.214125:
          return 'diploid'
      elif a_val < 1.731183:
          return 'gain'
      else:
          return 'amp'

MPNST (01_mpnst_get_omics.R: lines 173-176):

dplyr::mutate(copy_call=ifelse(copy_number<0.5210507,'deep del',
                               ifelse(copy_number<0.7311832,'het loss',
                                      ifelse(copy_number<1.214125,'diploid',
                                             ifelse(copy_number<1.422233,'gain','amp')))))|>