--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/imgtconvert.py	Thu Jan 23 08:09:30 2014 -0500
@@ -0,0 +1,138 @@
+import pandas as pd
+import re
+import argparse
+import os
+
+def stop_err( msg, ret=1 ):
+    sys.stderr.write( msg )
+    sys.exit( ret )
+
+#docs.python.org/dev/library/argparse.html
+parser = argparse.ArgumentParser()
+parser.add_argument("--input", help="Input folder with files")
+parser.add_argument("--output", help="Output file")
+
+args = parser.parse_args()
+
+old_summary_columns = [u'Sequence ID', u'JUNCTION frame', u'V-GENE and allele', u'D-GENE and allele', u'J-GENE and allele', u'CDR1-IMGT length', u'CDR2-IMGT length', u'CDR3-IMGT length', u'Orientation']
+old_sequence_columns = [u'CDR1-IMGT', u'CDR2-IMGT', u'CDR3-IMGT']
+old_junction_columns = [u'JUNCTION']
+
+added_summary_columns = [u'Functionality', u'V-REGION identity %', u'V-REGION identity nt', u'D-REGION reading frame', u'AA JUNCTION', u'Functionality comment', u'Sequence']
+added_sequence_columns = [u'FR1-IMGT', u'FR2-IMGT', u'FR3-IMGT', u'CDR3-IMGT', u'JUNCTION', u'J-REGION', u'FR4-IMGT']
+added_junction_columns = [u"P3'V-nt nb", u'N1-REGION-nt nb', u"P5'D-nt nb", u"P3'D-nt nb", u'N2-REGION-nt nb', u"P5'J-nt nb", u"3'V-REGION trimmed-nt nb", u"5'D-REGION trimmed-nt nb", u"3'D-REGION trimmed-nt nb", u"5'J-REGION trimmed-nt nb"]
+
+inputFolder = args.input
+
+dirContents = os.listdir(inputFolder)
+if len(dirContents) == 1:
+    inputFolder = os.path.join(inputFolder, dirContents[0])
+    if os.path.isdir(inputFolder):
+        print "is dir"
+        dirContents = os.listdir(inputFolder)
+files = sorted([os.path.join(inputFolder, f) for f in dirContents])
+
+if len(files) % 3 is not 0:
+    stop_err("Files in zip not a multiple of 3, it should contain the all the 1_, 5_ and 6_ files for a sample")
+    import sys
+    sys.exit()
+
+triplets = []
+step = len(files) / 3
+for i in range(0, step):
+    triplets.append((files[i], files[i + step], files[i + step + step]))
+
+outFile = args.output
+
+fSummary = pd.read_csv(triplets[0][0], sep="\t")
+fSequence = pd.read_csv(triplets[0][1], sep="\t")
+fJunction = pd.read_csv(triplets[0][2], sep="\t")
+tmp = fSummary[["Sequence ID", "JUNCTION frame", "V-GENE and allele", "D-GENE and allele", "J-GENE and allele"]]
+
+tmp["CDR1 Seq"] = fSequence["CDR1-IMGT"]
+tmp["CDR1 Length"] = fSummary["CDR1-IMGT length"]
+
+tmp["CDR2 Seq"] = fSequence["CDR2-IMGT"]
+tmp["CDR2 Length"] = fSummary["CDR2-IMGT length"]
+
+tmp["CDR3 Seq"] = fSequence["CDR3-IMGT"]
+tmp["CDR3 Length"] = fSummary["CDR3-IMGT length"]
+
+tmp["CDR3 Seq DNA"] = fJunction["JUNCTION"]
+tmp["CDR3 Length DNA"] = '1'
+tmp["Strand"] = fSummary["Orientation"]
+tmp["CDR3 Found How"] = 'a'
+
+for col in added_summary_columns:
+    tmp[col] = fSummary[col]
+
+for col in added_sequence_columns:
+    tmp[col] = fSequence[col]
+
+for col in added_junction_columns:
+    tmp[col] = fJunction[col]
+
+outFrame = tmp
+
+for triple in triplets[1:]:
+    fSummary = pd.read_csv(triple[0], sep="\t")
+    fSequence = pd.read_csv(triple[1], sep="\t")
+    fJunction = pd.read_csv(triple[2], sep="\t")
+
+    tmp = fSummary[["Sequence ID", "JUNCTION frame", "V-GENE and allele", "D-GENE and allele", "J-GENE and allele"]]
+
+    tmp["CDR1 Seq"] = fSequence["CDR1-IMGT"]
+    tmp["CDR1 Length"] = fSummary["CDR1-IMGT length"]
+
+    tmp["CDR2 Seq"] = fSequence["CDR2-IMGT"]
+    tmp["CDR2 Length"] = fSummary["CDR2-IMGT length"]
+
+    tmp["CDR3 Seq"] = fSequence["CDR3-IMGT"]
+    tmp["CDR3 Length"] = fSummary["CDR3-IMGT length"]
+
+    tmp["CDR3 Seq DNA"] = fJunction["JUNCTION"]
+    tmp["CDR3 Length DNA"] = '1'
+    tmp["Strand"] = fSummary["Orientation"]
+    tmp["CDR3 Found How"] = 'a'
+
+    for col in added_summary_columns:
+        tmp[col] = fSummary[col]
+
+    for col in added_sequence_columns:
+        tmp[col] = fSequence[col]
+
+    for col in added_junction_columns:
+        tmp[col] = fJunction[col]
+
+    outFrame = outFrame.append(tmp)
+
+outFrame.columns = [u'ID', u'VDJ Frame', u'Top V Gene', u'Top D Gene', u'Top J Gene', u'CDR1 Seq', u'CDR1 Length', u'CDR2 Seq', u'CDR2 Length', u'CDR3 Seq', u'CDR3 Length', u'CDR3 Seq DNA', u'CDR3 Length DNA', u'Strand', u'CDR3 Found How', u'Functionality', 'V-REGION identity %', 'V-REGION identity nt', 'D-REGION reading frame', 'AA JUNCTION', 'Functionality comment', 'Sequence', 'FR1-IMGT', 'FR2-IMGT', 'FR3-IMGT', 'CDR3-IMGT', 'JUNCTION', 'J-REGION', 'FR4-IMGT', 'P3V-nt nb', 'N1-REGION-nt nb', 'P5D-nt nb', 'P3D-nt nb', 'N2-REGION-nt nb', 'P5J-nt nb', '3V-REGION trimmed-nt nb', '5D-REGION trimmed-nt nb', '3D-REGION trimmed-nt nb', '5J-REGION trimmed-nt nb']
+
+vPattern = re.compile(r"IGHV[1-9]-[0-9ab]+-?[1-9]?")
+dPattern = re.compile(r"IGHD[1-9]-[0-9ab]+")
+jPattern = re.compile(r"IGHJ[1-9]")
+
+def filterGenes(s, pattern):
+    if type(s) is not str:
+        return "NA"
+    res = pattern.search(s)
+    if res:
+        return res.group(0)
+    return "NA"
+
+
+outFrame["Top V Gene"] = outFrame["Top V Gene"].apply(lambda x: filterGenes(x, vPattern))
+outFrame["Top D Gene"] = outFrame["Top D Gene"].apply(lambda x: filterGenes(x, dPattern))
+outFrame["Top J Gene"] = outFrame["Top J Gene"].apply(lambda x: filterGenes(x, jPattern))
+
+
+
+tmp = outFrame["VDJ Frame"]
+tmp = tmp.replace("in-frame", "In-frame")
+tmp = tmp.replace("null", "Out-of-frame")
+tmp = tmp.replace("out-of-frame", "Out-of-frame")
+outFrame["VDJ Frame"] = tmp
+outFrame["CDR3 Length DNA"] = outFrame["CDR3 Seq DNA"].map(str).map(len)
+safeLength = lambda x: len(x) if type(x) == str else 0
+outFrame = outFrame[(outFrame["CDR3 Seq DNA"].map(safeLength) > 0) & (outFrame["Top V Gene"] != "NA") & (outFrame["Top D Gene"] != "NA") & (outFrame["Top J Gene"] != "NA")] #filter out weird rows?
+outFrame.to_csv(outFile, sep="\t", index=False, index_label="index")
\ No newline at end of file

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/imgtconvert.sh	Thu Jan 23 08:09:30 2014 -0500
@@ -0,0 +1,57 @@
+#!/bin/bash
+dir="$(cd "$(dirname "$0")" && pwd)"
+mkdir $PWD/files
+
+
+#!/bin/bash
+f=$(file $1)
+zip7Type="7-zip archive"
+tarType="tar archive"
+bzip2Type="bzip2 compressed"
+gzipType="gzip compressed"
+zipType="Zip archive"
+rarType="RAR archive"
+
+if [[ "$f" == *"$zip7Type"* ]]; then
+	echo "7-zip"
+	echo "Trying: 7za e $1 -o$PWD/files/"
+	7za e $1 -o$PWD/files/
+fi
+
+if [[ "$f" == *"$tarType"* ]]
+then
+	echo "tar archive"
+	echo "Trying: tar xvf $1 -C $PWD/files/"
+	tar xvf $1 -C $PWD/files/
+fi
+
+if [[ "$f" == *"$bzip2Type"* ]]
+then
+	echo "bzip2 compressed data"
+	echo "Trying: tar jxf $1 -C $PWD/files/"
+	tar jxf $1 -C $PWD/files/
+fi
+
+if [[ "$f" == *"$gzipType"* ]]
+then
+	echo "gzip compressed data"
+	echo "Trying: tar xvzf $1 -C $PWD/files/"
+	tar xvzf $1 -C $PWD/files/
+fi
+
+if [[ "$f" == *"$zipType"* ]]
+then
+	echo "Zip archive"
+	echo "Trying: unzip $1 -d $PWD/files/"
+	unzip $1 -d $PWD/files/
+fi
+
+if [[ "$f" == *"$rarType"* ]]
+then
+	echo "RAR archive"
+	echo "Trying: unrar e $1 $PWD/files/"
+	unrar e $1 $PWD/files/
+fi
+find $PWD/files/ -type f |  grep -v "1_Summary_\|5_AA-sequences_\|6_Junction_" | xargs rm -f
+python $dir/imgtconvert.py --input $PWD/files --output $2
+

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/imgtconvert.xml	Thu Jan 23 08:09:30 2014 -0500
@@ -0,0 +1,16 @@
+<tool id="imgt_loader_igg" name="IMGT Loader" version="1.0">
+	<description> </description>
+	<command interpreter="bash">
+		imgtconvert.sh $in_file $out_file
+	</command>
+	<inputs>
+        <param name="in_file" type="data" label="Archive with files" />
+	</inputs>
+	<outputs>
+		<data format="tabular" name="out_file" />
+	</outputs>
+	<help>
+		Converting all 1_Summary, 5_AA-sequence and 6_Junction files belonging to a sample from an archive (supported: 7z, rar, tar, tar.bz2, tar.gz and zip) into a single file to be used in the Immune repertoire toolchain (Step 3)
+	</help>
+
+</tool>