New upstream version 1.0.0+dfsg

FSOM = fsom/fsom.o

FILEVERCMP = filevercmp/filevercmp.o

INCLUDES = -Itabixpp/htslib -I$(INC_DIR) -L. -Ltabixpp/htslib

LDFLAGS = -L$(LIB_DIR) -lvcflib -lhts -lpthread -lz -lm -llzma -lbz2

# Work out how to find htslib

# Use the one we ship in tabixpp unless told otherwise by the environment

HTS_LIB ?= $(VCF_LIB_LOCAL)/tabixpp/htslib/libhts.a

HTS_INCLUDES ?= -I$(VCF_LIB_LOCAL)/tabixpp/htslib

HTS_LDFLAGS ?= -L$(VCF_LIB_LOCAL)/tabixpp/htslib -lhts -lbz2 -lm -lz -llzma -pthread

INCLUDES = $(HTS_INCLUDES) -I$(INC_DIR) 

LDFLAGS = -L$(LIB_DIR) -lvcflib $(HTS_LDFLAGS) -lpthread -lz -lm -llzma -lbz2

all: $(OBJECTS) $(BINS) scriptToBin

	cd intervaltree && $(MAKE) && cp *.h* $(VCF_LIB_LOCAL)/$(INC_DIR)/

$(TABIX): pre

	cd tabixpp && $(MAKE) && cp *.h* $(VCF_LIB_LOCAL)/$(INC_DIR)/

	cd tabixpp && INCLUDES="$(HTS_INCLUDES)" LIBPATH="-L. $(HTS_LDFLAGS)" HTSLIB="$(HTS_LIB)" $(MAKE) && cp *.h* $(VCF_LIB_LOCAL)/$(INC_DIR)/

$(SMITHWATERMAN): pre

	cd smithwaterman && $(MAKE) && cp *.h* $(VCF_LIB_LOCAL)/$(INC_DIR)/ && cp *.o $(VCF_LIB_LOCAL)/$(OBJ_DIR)/

	rm -rf $(LIB_DIR)

	rm -rf $(INC_DIR)

	rm -rf $(OBJ_DIR)

	cd tabixpp && make clean

	cd smithwaterman && make clean

	cd fastahack && make clean

	cd tabixpp && $(MAKE) clean

	cd smithwaterman && $(MAKE) clean

	cd fastahack && $(MAKE) clean

	cd multichoose && $(MAKE) clean

	cd fsom && $(MAKE) clean

	cd libVCFH && $(MAKE) clean

	cd test && $(MAKE) clean

	cd filevercmp && $(MAKE) clean

	cd intervaltree && $(MAKE) clean

.PHONY: clean all test pre

        -t, --tag-parsed FLAG   Tag records which are split apart of a complex allele

                                with this flag

    If multiple alleleic primitives (gaps or mismatches) are specified in

    a single VCF record, split the record into multiple lines, but drop all

    INFO fields.  "Pure" MNPs are split into multiple SNPs unless the -m

    flag is provided.  Genotypes are phased where complex alleles have been

    decomposed, provided genotypes in the input.

If multiple alleleic primitives (gaps or mismatches) are specified in a single VCF record, split the record into multiple lines, but drop all INFO fields.

"Pure" MNPs are split into multiple SNPs unless the -m flag is provided.

Genotypes are phased where complex alleles have been decomposed, provided genotypes in the input.

### vcfaltcount

Intersect the records in the VCF file with targets provided in a BED file.

Intersections are done on the reference sequences in the VCF file.

    If no VCF filename is specified on the command line (last argument) the VCF

    read from stdin.

If no VCF filename is specified on the command line (last argument) the VCF read from stdin.

### vcfannotategenotypes

    usage: vcfannotategenotypes <annotation-tag> <vcf file> <vcf file>

    annotates genotypes in the first file with genotypes in the second adding the

    genotype as another flag to each sample filed in the first file.

    annotation-tag is the name of the sample flag which is added to store the

    annotation.  also adds a 'has\_variant' flag for sites where the second file has

    a variant.

Annotates genotypes in the first file with genotypes in the second adding the genotype as another flag to each sample filed in the first file.

Annotation-tag is the name of the sample flag which is added to store the annotation.

Also adds a 'has\_variant' flag for sites where the second file has a variant.

### vcfbreakmulti

    usage: vcfbreakmulti [options] [file]

    If multiple alleles are specified in a single record, break the record into

    multiple lines, preserving allele-specific INFO fields.

If multiple alleles are specified in a single record, break the record into multiple lines, preserving allele-specific INFO fields.

### vcfcheck

        -r --region REGION  A region specifier of the form chrN:x-y to bound the merge

Combines VCF files positionally, combining samples when sites and alleles are identical.

Any number of VCF files may be combined.  The INFO field and other columns are taken from

one of the files which are combined when records in multiple files match.  Alleles must

have identical ordering to be combined into one record.  If they do not, multiple records

will be emitted.

Any number of VCF files may be combined.

The INFO field and other columns are taken from one of the files which are combined when records in multiple files match.

Alleles must

have identical ordering to be combined into one record.

If they do not, multiple records will be emitted.

### vcfcommonsamples

    usage: vcfcommonsamples <vcf file> <vcf file> outputs each record in the

    first file, removing samples not present in the second

    usage: vcfcommonsamples <vcf file> <vcf file>

Outputs each record in the first file, removing samples not present in the second.

### vcfcountalleles

    usage: vcfentropy [options] <vcf file>

    options: -f, --fasta-reference  FASTA reference file to use to obtain

primer sequences -w, --window-size      Size of the window over which to

calculate entropy

    options:

        -f, --fasta-reference  FASTA reference file to use to obtain primer sequences

        -w, --window-size      Size of the window over which to calculate entropy

Anotates the output VCF file with, for each record, EntropyLeft,

EntropyRight, EntropyCenter, which are the entropies of the sequence of the

Operators can be any of: =, !, <, >, |, &

    Any number of filters may be specified.  They are combined via logical AND

    unless --or is specified on the command line.  Obtain logical negation through

    the use of parentheses, e.g. "! ( DP = 10 )"

Any number of filters may be specified.  They are combined via logical AND unless --or is specified on the command line.

Obtain logical negation through the use of parentheses, e.g. "! ( DP = 10 )"

    For convenience, you can specify "QUAL" to refer to the quality of the site, even

    though it does not appear in the INFO fields.

For convenience, you can specify "QUAL" to refer to the quality of the site, even though it does not appear in the INFO fields.

### vcffixup

Count the allele frequencies across alleles present in each record in the 

VCF file.  (Similar to vcftools --freq.)

Count the allele frequencies across alleles present in each record in the VCF file. (Similar to vcftools --freq.)

Uses genotypes from the VCF file to correct AC (alternate allele count), AF

(alternate allele frequency), NS (number of called), in the VCF records.  For

    usage: vcfflatten [file]

    Removes multi-allelic sites by picking the most common alternate.  Requires

    allele frequency specification 'AF' and use of 'G' and 'A' to specify the

    fields which vary according to the Allele or Genotype. VCF file may be

    specified on the command line or piped as stdin.

Removes multi-allelic sites by picking the most common alternate.

Requires allele frequency specification 'AF' and use of 'G' and 'A' to specify the fields which vary according to the Allele or Genotype.

VCF file may be specified on the command line or piped as stdin.

### vcfgeno2haplo

### vcfgenotypecompare

    usage: vcfgenotypecompare <other-genotype-tag> <vcf file>

    adds statistics to the INFO field of the vcf file describing the

    amount of discrepancy between the genotypes (GT) in the vcf file and the

    genotypes reported in the <other-genotype-tag>.  use this after

    vcfannotategenotypes to get correspondence statistics for two vcfs.

Adds statistics to the INFO field of the vcf file describing the amount of discrepancy between the genotypes (GT) in the vcf file and the genotypes reported in the <other-genotype-tag>.

Use this after vcfannotategenotypes to get correspondence statistics for two vcfs.

### vcfgenotypes

For bed-vcf intersection, alleles which fall into the targets are retained.

    For vcf-vcf intersection and union, unify on equivalent alleles within window-size bp

    as determined by haplotype comparison alleles.

For vcf-vcf intersection and union, unify on equivalent alleles within window-size bp as determined by haplotype comparison alleles.

### vcfkeepgeno

    usage: vcfkeepgeno <vcf file> [FIELD1] [FIELD2] ...

    outputs each record in the vcf file, removing FORMAT fields not listed

    on the command line from sample specifications in the output

Outputs each record in the vcf file, removing FORMAT fields not listed on the command line from sample specifications in the output.

### vcfkeepinfo

    usage: vcfkeepinfo <vcf file> [FIELD1] [FIELD2] ...

    outputs each record in the vcf file, removing INFO fields not listed on the command line

 Outputs each record in the vcf file, removing INFO fields not listed on the command line.

### vcfkeepsamples

    usage: vcfkeepsamples <vcf file> [SAMPLE1] [SAMPLE2] ...

    outputs each record in the vcf file, removing samples not listed on the command line

Outputs each record in the vcf file, removing samples not listed on the command line.

### vcfleftalign

        -r, --reference FILE  Use this reference as a basis for realignment.

        -w, --window N        Use a window of this many bp when left aligning (150).

    Left-aligns variants in the specified input file or stdin.  Window size is determined

    dynamically according to the entropy of the regions flanking the indel.  These must have

    entropy > 1 bit/bp, or be shorter than ~5kb.

Left-aligns variants in the specified input file or stdin.

Window size is determined dynamically according to the entropy of the regions flanking the indel.

These must have entropy > 1 bit/bp, or be shorter than ~5kb.

### vcflength

        -f, --fasta-reference  FASTA reference file to use to obtain primer sequences

        -l, --primer-length    The length of the primer sequences on each side of the variant

    For each VCF record, extract the flanking sequences, and write them to stdout as FASTA

    records suitable for alignment.  This tool is intended for use in designing validation

    experiments.  Primers extracted which would flank all of the alleles at multi-allelic

    sites.  The name of the FASTA "reads" indicates the VCF record which they apply to.

    The form is >CHROM_POS_LEFT for the 3' primer and >CHROM_POS_RIGHT for the 5' primer,

    for example:

For each VCF record, extract the flanking sequences, and write them to stdout as FASTA records suitable for alignment.

This tool is intended for use in designing validation experiments.

Primers extracted which would flank all of the alleles at multi-allelic sites.

The name of the FASTA "reads" indicates the VCF record which they apply to.

The form is >CHROM_POS_LEFT for the 3' primer and >CHROM_POS_RIGHT for the 5' primer, for example:

    >20_233255_LEFT

    CCATTGTATATATAGACCATAATTTCTTTATCCAATCATCTGTTGATGGA

        -p, --random-seed N  use this random seed

Randomly sample sites from an input VCF file, which may be provided as stdin.

    Scale the sampling probability by the field specified in KEY.  This may be

    used to provide uniform sampling across allele frequencies, for instance.

Scale the sampling probability by the field specified in KEY.

This may be used to provide uniform sampling across allele frequencies, for instance.

### vcfremap

### vcfremovesamples

    usage: vcfremovesamples <vcf file> [SAMPLE1] [SAMPLE2] ...

    outputs each record in the vcf file, removing samples listed on the command line

Outputs each record in the vcf file, removing samples listed on the command line.

### vcfroc

        -w, --window-size N       compare records up to this many bp away (default 30)

        -r, --reference FILE      FASTA reference file

    Generates a pseudo-ROC curve using sensitivity and specificity estimated against

    a putative truth set.  Thresholding is provided by successive QUAL cutoffs.

Generates a pseudo-ROC curve using sensitivity and specificity estimated against a putative truth set.

Thresholding is provided by successive QUAL cutoffs.

### vcfsamplediff

    usage: vcfsamplediff <tag> <sample> <sample> [ <sample> ... ] <vcf file>

    tags each record where the listed sample genotypes differ with <tag>

Tags each record where the listed sample genotypes differ with <tag>

The first sample is assumed to be germline, the second somatic.

    Each record is tagged with <tag>={germline,somatic,loh} to specify the type of

    variant given the genotype difference between the two samples.

Each record is tagged with <tag>={germline,somatic,loh} to specify the type of variant given the genotype difference between the two samples.

### vcfsamplenames

    application: 

        vcfsom -a output.som -f "AF DP ABP" test.vcf >results.vcf

    vcfsomtrains and/or applies a self-organizing map to the input VCF data

    on stdin, adding two columns for the x and y coordinates of the winning

    neuron in the network and an optional euclidean distance from a given

    node (--center).

vcfsom trains and/or applies a self-organizing map to the input VCF data on stdin, adding two columns for the x and y coordinates of the winning neuron in the network and an optional euclidean distance from a given node (--center).

    If a map is provided via --apply,  map will be applied to input without

    training.  Automated filtering to an estimated FP rate is 

If a map is provided via --apply,  map will be applied to input without training.

Automated filtering to an estimated FP rate is 

    options:

#!/usr/bin/env python

from __future__ import print_function

import sys

for line in sys.stdin:

    span = len(fields[3]) # handle multi-base alleles

    end = start + span

    name = fields[2]

    print "\t".join(map(str, [chrom, start, end, name]))

    print("\t".join(str(x) for x in [chrom, start, end, name]))

#!/usr/bin/env python

from __future__ import print_function

import sys

import re

import sqlite3

if len(sys.argv) < 2:

    print "usage", sys.argv[0], " [dbname]"

    print "reads VCF on stdin, and writes output to a sqlite3 db [dbname]"

    print("usage {} [dbname]").format(sys.argv[0])

    print("reads VCF on stdin, and writes output to a sqlite3 db [dbname]")

    exit(1)

dbname = sys.argv[1]

        n = re.search("Number=(.*?),", line)

        t = re.search("Type=(.*?),", line)

        if i and n and t:

            id = i.groups()[0]

            iden = i.groups()[0]

            number = n.groups()[0]

            if number == "A":

                number = -1

            else:

                number = int(number)

            typestr = t.groups()[0]

            infotypes[id] = typestr

            infonumbers[id] = number

            infotypes[iden] = typestr

            infonumbers[iden] = number

        else:

            continue

    elif line.startswith('##'):

for line in sys.stdin:

    fields = line.split('\t')

    chrom, pos, id, ref, alts, qual, filter, info = fields[:8]

    chrom, pos, iden, ref, alts, qual, filt, info = fields[:8]

    alts = alts.split(",")

    altindex = 0

    chrom = "\'" + chrom + "\'"

    id = "\'" + id + "\'"

    iden = "\'" + iden + "\'"

    ref = "\'" + ref + "\'"

    filter = "\'" + filter + "\'"

    filt = "\'" + filt + "\'"

    for alt in alts:

        alt = "\'" + alt + "\'"

        info_values = {}

                    value = "0"

            ordered_insertion.append(value)

        cmd = "insert into alleles values (" \

            + ", ".join([chrom, pos, id, ref, alt, qual, filter]) \

            + ", ".join([chrom, pos, iden, ref, alt, qual, filt]) \

            + ", " \

            + ", ".join(ordered_insertion) + ")"

        conn.execute(cmd)

#!/usr/bin/env python

#

from __future__ import print_function

import sys

for line in sys.stdin:

    if line.startswith("#"):

        print line.strip()

        print(line.strip())

    else:

        fields = line.strip().split("\t")

        fields[2] = "."

        print "\t".join(fields)

        print("\t".join(fields))