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varfilter.py

#!/software/bin/python

# Author: lh3, converted to python and modified to add -C option by Aylwyn Scally
#
# About:
#   varfilter.py is a port of Heng's samtools.pl varFilter script into 
#   python, with an additional -C INT option. This option sets a minimum 
#   consensus score, above which the script will output a pileup line 
#   wherever it _could have_ called a variant, even if none is actually 
#   called (i.e. hom-ref positions). This is important if you want to
#   subsequently merge the calls with those for another individual to get a
#   synoptic view of calls at each site. Without this option, and in all 
#   other respects, it behaves like samtools.pl varFilter.
#   
#   Aylwyn Scally as6@sanger.ac.uk


# Filtration code:
#
# C low CNS quality (hom-ref only)
# d low depth
# D high depth
# W too many SNPs in a window (SNP only)
# G close to a high-quality indel (SNP only)
# Q low RMS mapping quality (SNP only)
# g close to another indel with higher quality (indel only)
# s low SNP quality (SNP only)
# i low indel quality (indel only)


import sys
import getopt

def usage():
      print '''usage: varfilter.py [options] [cns-pileup]

Options: -Q INT   minimum RMS mapping quality for SNPs
             -q INT     minimum RMS mapping quality for gaps
             -d INT     minimum read depth 
             -D INT     maximum read depth
             -S INT     minimum SNP quality
             -i INT     minimum indel quality
             -C INT     minimum consensus quality for hom-ref sites

             -G INT     min indel score for nearby SNP filtering
             -w INT     SNP within INT bp around a gap to be filtered

             -W INT     window size for filtering dense SNPs
             -N INT     max number of SNPs in a window

             -l INT     window size for filtering adjacent gaps

             -p print filtered variants'''

def varFilter_aux(first, is_print):
      try:
            if first[1] == 0:
                  sys.stdout.write("\t".join(first[4:]) + "\n")
            elif is_print:
                  sys.stderr.write("\t".join(["UQdDWGgsiCX"[first[1]]] + first[4:]) + "\n")
      except IOError:
            sys.exit()
 
mindepth = 3
maxdepth = 100
gapgapwin = 30
minsnpmapq = 25
mingapmapq = 10
minindelscore = 25
scorefactor = 100
snpgapwin = 10
densesnpwin = 10
densesnps = 2
printfilt = False
minsnpq = 0
minindelq = 0
mincnsq = 0

try:
      options, args = getopt.gnu_getopt(sys.argv[1:], 'pq:d:D:l:Q:w:W:N:G:S:i:C:', [])
except getopt.GetoptError:
      usage()
      sys.exit(2)
for (oflag, oarg) in options:
      if oflag == '-d': mindepth = int(oarg)
      if oflag == '-D': maxdepth = int(oarg)
      if oflag == '-l': gapgapwin = int(oarg)
      if oflag == '-Q': minsnpmapq = int(oarg)
      if oflag == '-q': mingapmapq = int(oarg)
      if oflag == '-G': minindelscore = int(oarg)
      if oflag == '-s': scorefactor = int(oarg)
      if oflag == '-w': snpgapwin = int(oarg)
      if oflag == '-W': densesnpwin = int(oarg)
      if oflag == '-C': mincnsq = int(oarg)
      if oflag == '-N': densesnps = int(oarg)
      if oflag == '-p': printfilt = True
      if oflag == '-S': minsnpq = int(oarg)
      if oflag == '-i': minindelq = int(oarg)

if len(args) < 1:
      inp = sys.stdin
else:
      inp = open(args[0])

# calculate the window size
max_dist = max(gapgapwin, snpgapwin, densesnpwin)

staging = []
for t in (line.strip().split() for line in inp):
      (flt, score) = (0, -1)
      # non-var sites
      if t[3] == '*/*':
            continue
      is_snp = t[2].upper() != t[3].upper()
      if not (is_snp or mincnsq):
            continue
      # clear the out-of-range elements
      while staging:
            # Still on the same chromosome and the first element's window still affects this position?  
            if staging[0][4] == t[0] and int(staging[0][5]) + staging[0][2] + max_dist >= int(t[1]):
                  break
            varFilter_aux(staging.pop(0), printfilt)
      
      # first a simple filter
      if int(t[7]) < mindepth:
            flt = 2
      elif int(t[7]) > maxdepth:
            flt = 3
      if t[2] == '*': # an indel
            if minindelq and minindelq > int(t[5]):
                  flt = 8
      elif is_snp:
            if minsnpq and minsnpq> int(t[5]):
                  flt = 7
      else:
            if mincnsq and mincnsq > int(t[4]):
                  flt = 9

      # site dependent filters
      dlen = 0
      if flt == 0:
            if t[2] == '*': # an indel
                  # If deletion, remember the length of the deletion
                  (a,b) = t[3].split('/')
                  alen = len(a) - 1
                  blen = len(b) - 1
                  if alen>blen:
                        if a[0] == '-': dlen=alen 
                  elif b[0] == '-': dlen=blen 

                  if int(t[6]) < mingapmapq:
                        flt = 1
                  # filtering SNPs
                  if int(t[5]) >= minindelscore:
                        for x in (y for y in staging if y[3]):
                              # Is it a SNP and is it outside the SNP filter window?
                              if x[0] >= 0 or int(x[5]) + x[2] + snpgapwin < int(t[1]):
                                    continue
                              if x[1] == 0:
                                    x[1] = 5
                  
                  # calculate the filtering score (different from indel quality)
                  score = int(t[5])
                  if t[8] != '*':
                        score += scorefactor * int(t[10])
                  if t[9] != '*':
                        score += scorefactor * int(t[11])
                  # check the staging list for indel filtering
                  for x in (y for y in staging if y[3]):
                    # Is it a SNP and is it outside the gap filter window
                        if x[0] < 0 or int(x[5]) + x[2] + gapgapwin < int(t[1]):
                              continue
                        if x[0] < score:
                              x[1] = 6
                        else:
                              flt = 6
                              break
            else: # a SNP or hom-ref
                  if int(t[6]) < minsnpmapq:
                        flt = 1
                  # check adjacent SNPs
                  k = 1
                  for x in (y for y in staging if y[3]):
                        if x[0] < 0 and int(x[5]) + x[2] + densesnpwin >= int(t[1]) and (x[1] == 0 or x[1] == 4 or x[1] == 5):
                              k += 1
                  
                  # filtering is necessary
                  if k > densesnps:
                        flt = 4
                        for x in (y for y in staging if y[3]):
                              if x[0] < 0 and int(x[5]) + x[2] + densesnpwin >= int(t[1]) and x[1] == 0:
                                    x[1] = 4
                  else: # then check gap filter
                        for x in (y for y in staging if y[3]):
                              if x[0] < 0 or int(x[5]) + x[2] + snpgapwin < int(t[1]):
                                    continue
                              if x[0] >= minindelscore:
                                    flt = 5
                                    break
      
      staging.append([score, flt, dlen, is_snp] + t)
  
# output the last few elements in the staging list
while staging:
      varFilter_aux(staging.pop(0), printfilt)

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