--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat/cravat.py	Wed May 13 15:24:18 2015 -0400
@@ -0,0 +1,64 @@
+import sys
+import re
+import requests
+
+chromosome_re = re.compile('[0-9a-zA-Z_:]+\s+(chr[1-9]|chr1[0-9]|chr2[0-2]|chr[XY])\s+[0-9]+\s+[+-]\s+([ATGC]+|-)\s+([ATGC]+|-)', re.IGNORECASE)
+
+def is_correct_input_line (line):
+    if chromosome_re.match(line) != None:
+        return True
+    else:
+        return False
+
+def query (line):
+    url = query_url + '?mutation=' + '_'.join(line.split())
+    r = requests.get(url)
+    annot = r.json()
+    return annot
+
+query_url = 'http://staging.cravat.us/rest/service/query'
+
+first_headers = ['ID',
+                 'Chromosome',
+                 'Position', 
+                 'Strand', 
+                 'Reference base(s)', 
+                 'Alternate base(s)',
+                 'Sample']
+
+input_filename = sys.argv[1]
+output_filename = sys.argv[2]
+
+headers = []
+header_not_loaded = True
+
+f = open(input_filename)
+wf = open(output_filename, 'w')
+for line in f:
+    if is_correct_input_line(line) == False:
+        print 'Wrong format line:' + line[:-1]
+        continue
+
+    toks = line[:-1].split()
+    uid = toks[0]
+    if len(toks) >= 7:
+        sample_id = toks[6]
+    else:
+        sample_id = 'Unknown'
+    annot = query(' '.join(toks[1:]))
+    if header_not_loaded:
+        headers = annot.keys()
+        headers.sort()
+        wf.write('\t'.join(first_headers))
+        for header in headers:
+            if header not in first_headers:
+                wf.write('\t' + header)
+        wf.write('\n')
+        header_not_loaded = False
+    wf.write('\t'.join(toks[:6]) + '\t' + sample_id)
+    for header in headers:
+        if header not in first_headers:
+            wf.write('\t' + annot[header])
+    wf.write('\n')
+f.close()
+wf.close()

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat/cravat.xml	Wed May 13 15:24:18 2015 -0400
@@ -0,0 +1,19 @@
+<tool id='cravat' name='CRAVAT'>
+  <description>CRAVAT annotation</description>
+  <command interpreter='python'>cravat.py $input $output</command>
+  <inputs>
+    <param format='text' name='input' type='data' label='Input file' />
+  </inputs>
+  <outputs>
+    <data format='tabular' name='output' />
+  </outputs>
+
+  <tests>
+    <test>
+      <param name='input' value='test_input.txt' />
+      <output name='out_file1' file='test_output.txt' />
+    </test>
+  </tests>
+
+  <help>This tool queries CRAVAT for variants</help>
+</tool>

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat/test-data/test_input.txt	Wed May 13 15:24:18 2015 -0400
@@ -0,0 +1,5 @@
+TR1 chr22 30421786 + A T sample_1
+TR2 chr22 40814500 - A G sample_1
+TR3 chr22 25115450 + - AGG sample_2
+TR4 chr22 234234 + AGA - sample_2
+TR5 chr2 219134766 + G - sample_3

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat/test-data/test_output.tsv	Wed May 13 15:24:18 2015 -0400
@@ -0,0 +1,6 @@
+ID	Chromosome	Position	Strand	Reference base(s)	Alternate base(s)	Sample	1000 Genomes allele frequency	Driver Genes	ESP6500 allele frequency (African American)	ESP6500 allele frequency (European American)	ExAC allele frequency (African/African American)	ExAC allele frequency (East Asian)	ExAC allele frequency (Finnish)	ExAC allele frequency (Latino)	ExAC allele frequency (Non-Finnish European)	ExAC allele frequency (Other)	ExAC allele frequency (South Asian)	ExAC total allele frequency	HUGO symbol	Mappability Warning	Occurrences in COSMIC [exact nucleotide change]	Occurrences in COSMIC by primary sites [exact nucleotide change]	Protein sequence change in COSMIC	Sequence ontology	Sequence ontology all transcripts	Sequence ontology protein change	Sequence ontology transcript	TARGET	Transcript in COSMIC
+TR1	chr22	30421786	+	A	T	sample_1	0.0077875400893390178680419921875		0.02269629947841167449951171875	0	0.0238370001316070556640625	0	0	0.001123600057326257228851318359375	0	0.0011037499643862247467041015625	0	0.0021585500799119472503662109375	MTMR3					MS	NM_153051.2:N1161I(MS), NM_153050.2:N1170I(MS), ENST00000323630:N1062I(MS), ENST00000351488:N1161I(MS), ENST00000333027:N1170I(MS), ENST00000406629:N1170I(MS), ENST00000401950:N1198I(MS)	N1198I	NM_021090.3		
+TR2	chr22	40814500	-	A	G	sample_1	0.4832270145416259765625		0.860644996166229248046875	0.396977007389068603515625	0.871408998966217041015625	0.110581003129482269287109375	0.330637991428375244140625	0.1900829970836639404296875	0.3895820081233978271484375	0.3936649858951568603515625	0.4774529933929443359375	0.4003469944000244140625	MKL1		1	stomach(1)	p.S648G (stomach 1)	MS	ENST00000396617:S648G(MS), ENST00000402042:S598G(MS), ENST00000407029:S648G(MS), ENST00000355630:S648G(MS)	S648G	NM_020831.3		ENST00000355630
+TR3	chr22	25115450	+	-	AGG	sample_2	0		0	0	0	0	0	0	0	0	0	0	PIWIL3					II	NM_001255975.1:871(II), ENST00000533313:762(II), ENST00000527701:762(II), ENST00000332271:880(II)	880	NM_001008496.3		
+TR4	chr22	234234	+	AGA	-	sample_2	0		0	0	0	0	0	0	0	0	0	0	Non-Coding										
+TR5	chr2	219134766	+	G	-	sample_3	0		0	0	0.00038654799573123455047607421875	0	0	0	0.000482450588606297969818115234375	0	0	0.0002977323601953685283660888671875	AAMP		2	large_intestine(2)	p.P15fs*5 (large_intestine 2)	FD	ENST00000248450:15(FD), ENST00000444053:15(FD)	15	NM_001087.3		ENST00000248450

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat/vcf_to_cravat.py	Wed May 13 15:24:18 2015 -0400
@@ -0,0 +1,133 @@
+import sys
+import re
+
+def extract_vcf_variant (strand, pos, ref, alt):
+    pos = int(pos)
+    reflen = len(ref)
+    altlen = len(alt)
+    minlen = min(reflen, altlen)
+    new_ref = ref
+    new_alt = alt
+
+    if reflen == 1 and altlen == 1 and ref == alt:
+        return pos, ref, alt
+
+    for nt_pos in xrange(0, minlen):
+        if ref[reflen - nt_pos - 1] == alt[altlen - nt_pos - 1]:
+            new_ref = ref[:reflen - nt_pos - 1]
+            new_alt = alt[:altlen - nt_pos - 1]
+        else:
+            break
+    newreflen = len(new_ref)
+    newaltlen = len(new_alt)
+
+    minlen = min(newreflen, newaltlen)
+    new_pos = pos
+    new_ref2 = new_ref
+    new_alt2 = new_alt
+
+    for nt_pos in xrange(minlen):
+        if new_ref[nt_pos] == new_alt[nt_pos]:
+            if strand == '+':
+                new_pos += 1
+            elif strand == '-':
+                new_pos -= 1
+            new_ref2 = new_ref[nt_pos + 1:]
+            new_alt2 = new_alt[nt_pos + 1:]
+        else:
+            new_ref2 = new_ref[nt_pos:]
+            new_alt2 = new_alt[nt_pos:]
+            break
+    if new_ref == '':
+        new_ref2 = '-'
+    if new_alt2 == '':
+        new_alt2 = '-'
+
+    return new_pos, new_ref2, new_alt2
+
+input_filename = sys.argv[1]
+output_filename = sys.argv[2]
+
+f = open(input_filename)
+wf = open(output_filename, 'w')
+
+vcf_line_no = 0
+
+for line in f:
+    vcf_line_no += 1
+    if len(line) < 6:
+        continue
+    if line[:6] == '#CHROM':
+        toks = re.split('\s+', line.rstrip())
+        if len(toks) > 8:
+            samples = toks[9]
+        break
+no_samples = len(samples)
+
+for line in f:
+    vcf_line_no += 1
+
+    if line[0] == '#':
+        continue
+
+    toks = re.split('\s+', line.rstrip())
+
+    if len(toks) < 8:
+        continue
+
+    [chrom, pos, uidbase, ref, alts, dummy, dummy, dummy] = toks[:8]
+    reflen = len(ref)
+    if uidbase == '.':
+        uidbase = 'VAR' + str(vcf_line_no)
+    if chrom[:3].lower != 'chr':
+        chrom = 'chr' + chrom
+    alts = alts.split(',')
+
+    len_alts = len(alts)
+    if len(toks) == 8:
+        for altno in xrange(len_alts):
+            alt = alts[altno]
+            if len_alts == 1:
+                uid = uidbase
+            else:
+                uid = uidbase + '_' + str(altno + 1)
+            newpos, newref, newalt = extract_vcf_variant('+', pos, ref, alt)
+            cravat_line = '\t'.join([uid, chrom, str(newpos), '+', newref, newalt, 'Unknown'])
+            wf.write(cravat_line + '\n')
+    elif len(toks) > 8:
+        sample_datas = toks[9:]
+
+        genotype_fields = {}
+        genotype_field_no = 0
+        for genotype_field in toks[8].split(':'):
+            genotype_fields[genotype_field] = genotype_field_no
+
+        if not ('GT' in genotype_fields):
+            print 'No GT Field at line ' + str(vcf_line_no) + ' [' + line.strip() + ']'
+            continue
+        
+        gt_field_no = genotype_fields['GT']
+
+        for sample_no in xrange(len(sample_datas)):
+            sample = samples[sample_no]
+            sample_data = sample_datas[sample_no].split(':')
+            gts = {}
+            for gt in sample_data[gt_field_no].replace('/', '|').split('|'):
+                if gt == '.':
+                    continue
+                else:
+                    gts[int(gt)] = True
+            for gt in gts.keys():
+                if gt == 0:
+                    continue
+                else:
+                    alt = alts[gt - 1]
+                    if len_alts == 1:
+                        uid = uidbase
+                    else:
+                        uid = uidbase + ':' + str(gt)
+                    newpos, newref, newalt = extract_vcf_variant('+', pos, ref, alt)
+                    cravat_line = '\t'.join([uid + '_' + sample, chrom, str(newpos), '+', newref, newalt, sample])
+                    wf.write(cravat_line + '\n')
+f.close()
+wf.close()

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cravat/vcf_to_cravat.xml	Wed May 13 15:24:18 2015 -0400
@@ -0,0 +1,19 @@
+<tool id='vcf_to_cravat' name='VCF to CRAVAT'>
+  <description>VCF to CRAVAT input format conversion</description>
+  <command interpreter='python'>vcf_to_cravat.py $input $output</command>
+  <inputs>
+    <param format='vcf' name='input' type='data' label='Input file' />
+  </inputs>
+  <outputs>
+    <data format='tabular' name='output' />
+  </outputs>
+
+  <tests>
+    <test>
+      <param name='input' value='test_input.txt' />
+      <output name='out_file1' file='test_output.txt' />
+    </test>
+  </tests>
+
+  <help>This tool converts a VCF format file to a CRAVAT input format file.</help>
+</tool>