code: def _lowfreq_linear_filter(tumor_index, is_paired):
      
      if is_paired:
          sbf = "FORMAT/SBF[%s]" % tumor_index
          nm = "FORMAT/NM[%s]" % tumor_index
      else:
          sbf = "INFO/SBF"
          nm = "INFO/NM"
      cmd = ("""bcftools filter --soft-filter 'LowFreqBias' --mode '+' """
             """-e  'FORMAT/AF[{tumor_index}] < 0.02 && FORMAT/VD[{tumor_index}] < 30 """
             """&& {sbf} < 0.1 && {nm} >= 2.0'""")
      return cmd.format(**locals())
docs: Linear classifier for removing low frequency false positives.
  
      Uses a logistic classifier based on 0.5% tumor only variants from the smcounter2 paper:
  
      https://github.com/bcbio/bcbio_validations/tree/master/somatic-lowfreq
  
      The classifier uses strand bias (SBF) and read mismatches (NM) and
      applies only for low frequency (<2%) and low depth (<30) variants.