--- /dev/null
+#!/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)