# HG changeset patch # User pjbriggs # Date 1449233010 18000 # Node ID b6ccc7dd7b025f4ed22da97efb4a0c02db051dde # Parent 771ebe02636fe4566d5e3ce759700e37e9e9c2bf Version 0.02.04.3. diff -r 771ebe02636f -r b6ccc7dd7b02 README.rst --- a/README.rst Mon Mar 23 07:01:37 2015 -0400 +++ b/README.rst Fri Dec 04 07:43:30 2015 -0500 @@ -7,16 +7,17 @@ ====================== Installation via the Galaxy Tool Shed will take of installing the tool wrapper and -the pal_finder and primer3_core programs, and setting the appropriate environment -variables. +the pal_finder and primer3_core programs (plus additional dependencies), and setting +the appropriate environment variables. Manual Installation =================== -There are two files to install: +There are three files to install: - ``pal_finder_wrapper.xml`` (the Galaxy tool definition) - ``pal_finder_wrapper.sh`` (the shell script wrapper) +- ``pal_finder_filter_and_assembly.py`` (filtering utility) The suggested location is in a ``tools/pal_finder_wrapper/`` folder. You will then need to modify the ``tools_conf.xml`` file to tell Galaxy to offer the tool @@ -30,10 +31,15 @@ - ``Primer3`` version 2.0.0-alpha (see the pal_finder installation notes) can be obtained from http://primer3.sourceforge.net/releases.php -The tool wrapper must be able to locate the pal_finder Perl script, the example -pal_finder config.txt and simple.ref data files, and the primer3_core program - the -locations of these are taken from the following enviroment variables which you will -need to set manually: +Additionally the filtering script needs ``BioPython`` and the ``PANDASeq`` program: + +- ``BioPython`` can be obtained from https://pypi.python.org/packages/source/b/biopython/ +- ``PANDASeq`` version 2.8.1 can be obtained from https://github.com/neufeld/pandaseq/ + +The tool wrapper must be able to locate the ``pal_finder_v0.02.04.pl`` script, the +example pal_finder ``config.txt`` and ``simple.ref`` data files, and the +``primer3_core`` program - the locations of these are taken from the following +enviroment variables which you will need to set manually: - ``PALFINDER_SCRIPT_DIR``: location of the pal_finder Perl script (defaults to /usr/bin) - ``PALFINDER_DATA_DIR``: location of the pal_finder data files (specifically config.txt @@ -54,6 +60,10 @@ ========== ====================================================================== Version Changes ---------- ---------------------------------------------------------------------- +0.02.04.3 - Update to the Illumina filtering script from Graeme Fox (including + new option to run ``PANDASeq`` assembly/QC steps), and corresponding + update to the tool; add support for input FASTQs to be a dataset + collection pair. 0.02.04.2 - Fix bug that causes tool to fail when prefix includes spaces; add explicit dependency on Perl 5.16.3. 0.02.04.1 - Add option to run Graeme Fox's ``pal_finder_filter.pl`` script to diff -r 771ebe02636f -r b6ccc7dd7b02 pal_finder_filter.pl --- a/pal_finder_filter.pl Mon Mar 23 07:01:37 2015 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,112 +0,0 @@ -############################################################ -# Graeme Fox - 25/09/2014 - graeme.fox@manchester.ac.uk -# -# Program to filter output from pal_finder/primer3 workflow -# -# Filters output based on "Primers found (1=y,0=n)" and -# "occurrences of forward/reverse amplifiable primer in reads". -# Filters out any non-perfect microsatellites. -# Ranks microsatellites by motif size (largest first) -# -# Usage: -# Give it the file that ends with: -# "(microsatellites_with_read_IDs_and_primer_pairs)].txt" -# -# with the following syntax: -# perl pal_finder_filter.pl /path/to/input/file -# -# File will be created called "pal_finder_filter_output.txt" -# in the current directory -############################################################ - -#!/usr/bin/perl -w -use strict; - -my @lines; -my @output; -my $outfile = 'pal_finder_filter_output.txt'; - -# Open the file for reading -my $filename = $ARGV[0]; -open (my $file, '<', $filename); - -# Grab the headers and store them -my $header; -while (my $line = <$file>) -{ - if ($line =~ m/^readPair/) { -# push (@output, $line) - $header = $line; - } else { - -# Send everything else to array for sorting - push (@lines, $line); - } -} -close $file; -chomp (@lines); - -############################################################ -# Filter the file on the "Primers found (1=y,0=n)" column -# ie. Drop all the lines which do not have primer sequences -############################################################ -my @temporary1; -my @temporary2; -foreach (@lines) { -@temporary1 = split(/\t/, $_); - if ($temporary1[5] == 1) { - push (@temporary2, $_); - } -} - -############################################################ -# Filter any lines which do not have "1" in the "Occurances -# of Reverse/Forward Primer in Reads" field -############################################################ -my @temporary3; -my @temporary4; -foreach (@temporary2) { -@temporary3 = split(/\t/, $_); - if ($temporary3[16] == 1 && $temporary3[15] == 1) { - push (@temporary4, $_); - } -} - -############################################################ -# Filter any non-perfect repeats -############################################################ -my @temporary5; -my @temporary6; -my $count; -foreach (@temporary4) { - @temporary5 = split(/\t/, $_); - $count = ($temporary5[1] =~ tr/\(//); - if ($count == 1) { - push (@temporary6, $_); - } -} -############################################################ -# Get size of repeat motif. Order by size (largest first) -############################################################ -my @temporary7; -my @temporary8; -my $motif; -my $count2 = 2; -while ($count2 < 10) { - foreach (@temporary6) { - @temporary7 = split(/\t/, $_); - #get size of motif: - $motif = () = ($temporary7[1] =~ /[A-Z]/gi ); - if ($motif == $count2) { - unshift (@output, join( "\t", @temporary7),"\n"); - } - } -$count2++; -} -############################################################ -# Open and populate the output file -############################################################ -unshift (@output, $header); -open (FILE, "> $outfile") || die "Problem opening $outfile\n"; -print FILE @output; -close(FILE); diff -r 771ebe02636f -r b6ccc7dd7b02 pal_finder_filter_and_assembly.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pal_finder_filter_and_assembly.py Fri Dec 04 07:43:30 2015 -0500 @@ -0,0 +1,363 @@ +#!/usr/bin/python -tt + +########################################################### +# Graeme Fox - 26/09/2015 - graeme.fox@manchester.ac.uk +# Tested on (L)ubuntu 15.04 only, with Python 2.7 +########################################################### +# PROGRAM DESCRIPTION +# Program to pick optimum loci from the output of pal_finder_v0.02.04 +# and to predict the fragment length. +# +# This program can be used to filter pal_finder output to choose the 'optimum' loci. +# +# Additionally this program can assemble the two paired end reads, +# find the primers within HQ assembly, log their positions +# and calculate the difference to give the fragment length. +# +# For best results in your PCR, I suggest doing both. +# +########################################################### +# Requirements: +# Must have Biopython (www.biopython.org). +# +# If you with to perform the assembly QC step, you must have: +# PandaSeq (https://github.com/neufeld/pandaseq) +# PandaSeq must be in your path / able to run from anywhere +########################################################### +# Required options: +# -i forward_paired_ends.fastQ +# -j reverse_paired_ends.fastQ +# -p pal_finder output - the "(microsatellites with read IDs and primer pairs)" file +# +# By default it does nothing. +# +# Non-required options: +# -assembly: turn on the pandaseq assembly QC step +# -primers: filter microsatellite loci to just those which have primers designed +# -occurrences: filter microsatellite loci to those with primers which appear only once in the dataset +# -rankmotifs: filter microsatellite loci to just those with perfect motifs. Rank the output by size of motif (largest first) +# +########################################################### +# For repeat analysis, the following extra non-required options may be useful: +# PandaSeq Assembly, and fastq -> fasta conversion are slow. +# +# Do them the first time, generate the files and then skip either, or both steps with the following: +# -a: skip assembly step +# -c: skip fastq -> fasta conversion step +# +# # Just make sure to keep the files in the correct directory with the correct filename +########################################################### +# +# Example usage: +# pal_finder_filter_and_assembly.py -i R1.fastq -j R2.fastq -p pal_finder_output_(microsatellites with read IDs and primer pairs).tabular -primers -occurrences -rankmotifs -assembly +# +########################################################### +import Bio, subprocess, argparse, csv, os, re, time +from Bio import SeqIO + +# Get values for all the required and optional arguments + +parser = argparse.ArgumentParser(description='Frag_length_finder') +parser.add_argument('-i','--input1', help='Forward paired-end fastq file', required=True) +parser.add_argument('-j','--input2', help='Reverse paired-end fastq file', required=True) +parser.add_argument('-p','--pal_finder', help='Output from pal_finder ', required=True) +parser.add_argument('-assembly','--assembly_QC', help='Perform the PandaSeq based QC', nargs='?', const=1, type=int, required=False) +parser.add_argument('-a','--skip_assembly', help='If the assembly has already been run, skip it with -a', nargs='?', const=1, type=int, required=False) +parser.add_argument('-c','--skip_conversion', help='If the fastq to fasta conversion has already been run, skip it with -c', nargs='?', const=1, type=int, required=False) +parser.add_argument('-primers','--filter_by_primer_column', help='Filter pal_finder output to just those loci which have primers designed', nargs='?', const=1, type=int, required=False) +parser.add_argument('-occurrences','--filter_by_occurrences_column', help='Filter pal_finder output to just loci with primers which only occur once in the dataset', nargs='?', const=1, type=int, required=False) +parser.add_argument('-rankmotifs','--filter_and_rank_by_motif_size', help='Filter pal_finder output to just loci which are a perfect repeat unit. Also, rank the loci by motif size (largest first)', nargs='?', const=1, type=int, required=False) +args = vars(parser.parse_args()) + +# parse arguments + +R1_input = args['input1']; +R2_input = args['input2']; +pal_finder_output = args['pal_finder']; +perform_assembly = args['assembly_QC'] +skip_assembly = args['skip_assembly']; +skip_conversion = args['skip_conversion']; +filter_primers = args['filter_by_primer_column']; +filter_occurrences = args['filter_by_occurrences_column']; +filter_rank_motifs = args['filter_and_rank_by_motif_size']; + +# set default values for arguments +if perform_assembly is None: + perform_assembly = 0 +if skip_assembly is None: + skip_assembly = 0 +if skip_conversion is None: + skip_conversion = 0 +if filter_primers is None: + filter_primers = 0 +if filter_occurrences is None: + filter_occurrences = 0 +if filter_rank_motifs is None: + filter_rank_motifs = 0 + +############################################################ +# Function List # +############################################################ +# Reverse complement a sequence +def ReverseComplement1(seq): + seq_dict = {'A':'T','T':'A','G':'C','C':'G'} + return "".join([seq_dict[base] for base in reversed(seq)]) + +# Convert a .fastq to a .fasta, filter to just lines we want and strip MiSeq barcodes +def fastq_to_fasta(file): + file_name = os.path.splitext(os.path.basename(file))[0] + with open(file_name + "_filtered.fasta", "w") as out: + for record in SeqIO.parse(file, "fastq"): + ID = str(record.id) + SEQ = str(record.seq) + if ID in wanted: + out.write(">" + ID + "\n" + SEQ + "\n") + +# strip the miseq barcodes from a fasta file +def strip_barcodes(file): + file_name = os.path.splitext(os.path.basename(file))[0] + with open(file_name + "_adapters_removed.fasta", "w") as out: + for record in SeqIO.parse(file, "fasta"): + match = re.search(r'\S*:', record.id) + if match: + correct = match.group().rstrip(":") + else: + correct = str(record.id) + SEQ = str(record.seq) + if correct in wanted: + out.write(">" + correct + "\n" + SEQ + "\n") + +############################################################ +# MAIN PROGRAM # +############################################################ + +if (perform_assembly == 0 and filter_primers == 0 and filter_occurrences == 0 and filter_rank_motifs == 0): + print "\nNo optional arguments supplied." + print "\nBy default this program does nothing." + print "\nNo files produced and no modifications made." + print "\nFinished.\n" + exit() + +else: + print "\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" + print "Checking supplied filtering parameters:" + print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" + if filter_primers == 1: + print "-primers flag supplied. Filtering pal_finder output on the \"Primers found (1=y,0=n)\" column." + if filter_occurrences == 1: + print "-occurrences flag supplied. Filtering pal_finder output on the \"Occurances of Forward Primer in Reads\" and \"Occurances of Reverse Primer in Reads\" columns." + if filter_rank_motifs == 1: + print "-rankmotifs flag supplied. Filtering pal_finder output on the \"Motifs(bases)\" column to just those with perfect repeats. Ranking output by size of motif (largest first)." + +# index the raw fastq files so that the sequences can be pulled out and added to the filtered output file +R1fastq_sequences_index = SeqIO.index(R1_input,'fastq') +R2fastq_sequences_index = SeqIO.index(R2_input,'fastq') + +# create a set to hold the filtered output +wanted_lines = set() + +# get lines from the pal_finder output which meet filter settings + +# read the pal_finder output file into a csv reader +with open (pal_finder_output) as csvfile_infile: + csv_f = csv.reader(csvfile_infile, delimiter='\t') + header = csv_f.next() + with open(os.path.splitext(os.path.basename(pal_finder_output))[0] + ".filtered", 'w') as csvfile_outfile: + # write the header line for the output file + csvfile_outfile.write('\t'.join(header) + "\tR1_Sequence_ID\tR1_Sequence\tR2_Sequence_ID\tR2_Sequence\n") + for row in csv_f: + # get the sequence ID + seq_ID = row[0] + # get the raw sequence reads and convert to a format that can go into a tsv file + R1_sequence = R1fastq_sequences_index[seq_ID].format("fasta").replace("\n","\t",1).replace("\n","") + R2_sequence = R2fastq_sequences_index[seq_ID].format("fasta").replace("\n","\t",1).replace("\n","") + seq_info = "\t" + R1_sequence + "\t" + R2_sequence + "\n" + # navigate through all different combinations of filter options + # if the primer filter is switched on + if filter_primers == 1: + # check the occurrences of primers field + if row[5] == "1": + # if filter occurrences of primers is switched on + if filter_occurrences == 1: + # check the occurrences of primers field + if (row[15] == "1" and row[16] == "1"): + # if rank by motif is switched on + if filter_rank_motifs == 1: + # check for perfect motifs + if row[1].count('(') == 1: + # all 3 filter switched on - write line out to output + csvfile_outfile.write('\t'.join(row) + seq_info) + + else: + csvfile_outfile.write('\t'.join(row) + seq_info) + elif filter_rank_motifs == 1: + if row[1].count('(') == 1: + csvfile_outfile.write('\t'.join(row) + seq_info) + else: + csvfile_outfile.write('\t'.join(row) + seq_info) + elif filter_occurrences == 1: + if (row[15] == "1" and row[16] == "1"): + if filter_rank_motifs == 1: + if row[1].count('(') == 1: + csvfile_outfile.write('\t'.join(row) + seq_info) + else: + csvfile_outfile.write('\t'.join(row) + seq_info) + elif filter_rank_motifs == 1: + if row[1].count('(') == 1: + csvfile_outfile.write('\t'.join(row) + seq_info) + else: + csvfile_outfile.write('\t'.join(row) + seq_info) + +# if filter_rank_motifs is active, order the file by the size of the motif +if filter_rank_motifs == 1: + rank_motif = [] + ranked_list = [] + # read in the non-ordered file and add every entry to rank_motif list + with open(os.path.splitext(os.path.basename(pal_finder_output))[0] + ".filtered") as csvfile_ranksize: + csv_rank = csv.reader(csvfile_ranksize, delimiter='\t') + header = csv_rank.next() + for line in csv_rank: + rank_motif.append(line) + + # open the file ready to write the ordered list + with open(os.path.splitext(os.path.basename(pal_finder_output))[0] + ".filtered", 'w') as rank_outfile: + rankwriter = csv.writer(rank_outfile, delimiter='\t', lineterminator='\n') + rankwriter.writerow(header) + count = 2 + while count < 10: + for row in rank_motif: + # count size of motif + motif = re.search(r'[ATCG]*',row[1]) + if motif: + the_motif = motif.group() + # rank it and write into ranked_list + if len(the_motif) == count: + ranked_list.insert(0, row) + count = count + 1 + # write out the ordered list, into the .filtered file + for row in ranked_list: + rankwriter.writerow(row) + +print "\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" +print "Checking assembly flags supplied:" +print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" +if perform_assembly == 0: + print "Assembly flag not supplied. Not performing assembly QC.\n" +if perform_assembly == 1: + print "-assembly flag supplied: Performing PandaSeq assembly quality checks." + time.sleep(5) + +# Get readID, F primers, R primers and motifs from the filtered pal_finder output + seqIDs = [] + motif = [] + F_primers = [] + R_primers = [] + with open(os.path.splitext(os.path.basename(pal_finder_output))[0] + ".filtered") as input_csv: + pal_finder_csv = csv.reader(input_csv, delimiter='\t') + header = pal_finder_csv.next() + for row in pal_finder_csv: + seqIDs.append(row[0]) + motif.append(row[1]) + F_primers.append(row[7]) + R_primers.append(row[9]) + +# Get a list of just the unique IDs we want + wanted = set() + for line in seqIDs: + wanted.add(line) + +# Assemble the paired end reads into overlapping contigs using PandaSeq +# (can be skipped with the -a flag if assembly has already been run +# and the appropriate files are in the same directory as the script, +# and named "Assembly.fasta" and "Assembly_adapters_removed.fasta") +# +# I suggest you run this script WITHOUT -a first, and then use the -a flag in +# any subsequent reanalysis + + if skip_assembly == 0: + pandaseq_command = 'pandaseq -A pear -f ' + R1_input + ' -r ' + R2_input + ' -o 25 -t 0.95 -w Assembly.fasta' + subprocess.call(pandaseq_command, shell=True) + strip_barcodes("Assembly.fasta") + print "\nPaired end reads been assembled into overlapping reads." + print "\nFor future analysis, you can skip this assembly step using the -a flag, provided that the assembly.fasta file is intact and in the same location." + else: + print "\n(Skipping the assembly step as you provided the -a flag)" + +# FastQ files need to be converted to fasta. Again, I suggest running this section +# the first time WITHOUT the -c flag and then skipping it later using the -c flag +# Make sure the fasta files are in the same location and do not change the filenames + + if skip_conversion ==0: + fastq_to_fasta(R1_input) + fastq_to_fasta(R2_input) + print "\nThe input fastq files have been converted to the fasta format." + print "\nFor any future analysis, you can skip this conversion step using the -c flag, provided that the fasta files are intact and in the same location." + else: + print "\n(Skipping the fastq -> fasta conversion as you provided the -c flag)" + +# get the files and everything else we will need + assembly_file = "Assembly_adapters_removed.fasta" # Assembled fasta file + R1_fasta = os.path.splitext(os.path.basename(R1_input))[0] + "_filtered.fasta" # filtered R1 reads + R2_fasta = os.path.splitext(os.path.basename(R2_input))[0] + "_filtered.fasta" # filtered R2 reads + outputfilename = os.path.splitext(os.path.basename(R1_input))[0] + +# parse the files with SeqIO + assembly_sequences = SeqIO.parse(assembly_file,'fasta') + R1fasta_sequences = SeqIO.parse(R1_fasta,'fasta') + +# create some empty lists to hold the ID tags we are interested in + assembly_IDs = [] + fasta_IDs = [] + +# populate the above lists with sequence IDs + for sequence in assembly_sequences: + assembly_IDs.append(sequence.id) + for sequence in R1fasta_sequences: + fasta_IDs.append(sequence.id) + +# Index the assembly fasta file + assembly_sequences_index = SeqIO.index(assembly_file,'fasta') + R1fasta_sequences_index = SeqIO.index(R1_fasta,'fasta') + R2fasta_sequences_index = SeqIO.index(R2_fasta,'fasta') + +# prepare the output file + with open (outputfilename + "_pal_finder_assembly_output.txt", 'w') as outputfile: + outputfile.write("readPairID\t Forward Primer\t F Primer Position in Assembled Read\t Reverse Primer\t R Primer Position in Assembled Read\t Predicted Amplicon Size (bp)\t Motifs(bases)\t Assembled Read ID\t Assembled Read Sequence\t Raw Forward Read ID\t Raw Forward Read Sequence\t Raw Reverse Read ID\t Raw Reverse Read Sequence\n") + +# cycle through parameters from the pal_finder output + for x, y, z, a in zip(seqIDs, F_primers, R_primers, motif): + if str(x) in assembly_IDs: + # get the raw sequences ready to go into the output file + assembly_seq = (assembly_sequences_index.get_raw(x).decode()) + # fasta entries need to be converted to single line so they sit nicely in the output + assembly_output = assembly_seq.replace("\n","\t") + R1_fasta_seq = (R1fasta_sequences_index.get_raw(x).decode()) + R1_output = R1_fasta_seq.replace("\n","\t",1).replace("\n","") + #R1_output = R1_output.replace("\n","") + R2_fasta_seq = (R2fasta_sequences_index.get_raw(x).decode()) + R2_output = R2_fasta_seq.replace("\n","\t",1).replace("\n","") + #R2_output = R2_output.replace("\n","") + assembly_no_id = '\n'.join(assembly_seq.split('\n')[1:]) + +# check that both primer sequences can be seen in the assembled contig + if y or ReverseComplement1(y) in assembly_no_id and z or ReverseComplement1(z) in assembly_no_id: + if y in assembly_no_id: + # get the positions of the primers in the assembly to predict fragment length + F_position = assembly_no_id.index(y)+len(y)+1 + if ReverseComplement1(y) in assembly_no_id: + F_position = assembly_no_id.index(ReverseComplement1(y))+len(ReverseComplement1(y))+1 + if z in assembly_no_id: + R_position = assembly_no_id.index(z)+1 + if ReverseComplement1(z) in assembly_no_id: + R_position = assembly_no_id.index(ReverseComplement1(z))+1 + # calculate fragment length + fragment_length = R_position-F_position + +# write everything out into the output file + output = (str(x) + "\t" + y + "\t" + str(F_position) + "\t" + (z) + "\t" + str(R_position) + "\t" + str(fragment_length) + "\t" + a + "\t" + assembly_output + R1_output + "\t" + R2_output + "\n") + outputfile.write(output) + print "\nFinished\n" +else: + if (skip_assembly == 1 or skip_conversion == 1): + print "\nERROR: You cannot supply the -a flag or the -c flag without also supplying the -assembly flag.\n" + print "\nFinished\n" diff -r 771ebe02636f -r b6ccc7dd7b02 pal_finder_wrapper.sh --- a/pal_finder_wrapper.sh Mon Mar 23 07:01:37 2015 -0400 +++ b/pal_finder_wrapper.sh Fri Dec 04 07:43:30 2015 -0500 @@ -26,8 +26,11 @@ # --primer-opt-tm VALUE: optimum melting temperature (Celsius) # --primer-pair-max-diff-tm VALUE: max difference between melting temps of left & right primers # --output_config_file FNAME: write a copy of the config.txt file to FNAME -# --filter_microsats FNAME: run Graeme Fox's Perl script to filter and sort the -# microsatellites from pal_finder and write to FNAME +# --filter_microsats FNAME: write output of filter options FNAME +# -assembly FNAME: run the 'assembly' filter option and write to FNAME +# -primers: run the 'primers' filter option +# -occurrences: run the 'occurrences' filter option +# -rankmotifs: run the 'rankmotifs' filter option # # pal_finder is available from http://sourceforge.net/projects/palfinder/ # @@ -55,9 +58,9 @@ : ${PRIMER3_CORE_EXE:=primer3_core} # # Filter script is in the same directory as this script -PALFINDER_FILTER_PL=$(dirname $0)/pal_finder_filter.pl -if [ ! -f $PALFINDER_FILTER_PL ] ; then - echo No pal_finder_filter.pl script >&2 +PALFINDER_FILTER=$(dirname $0)/pal_finder_filter_and_assembly.py +if [ ! -f $PALFINDER_FILTER ] ; then + echo No $PALFINDER_FILTER script >&2 exit 1 fi # @@ -104,7 +107,9 @@ PRIMER_MIN_TM= PRIMER_PAIR_MAX_DIFF_TM= OUTPUT_CONFIG_FILE= +OUTPUT_ASSEMBLY= FILTERED_MICROSATS= +FILTER_OPTIONS= # # Collect command line arguments if [ $# -lt 2 ] ; then @@ -129,8 +134,8 @@ case "$1" in --primer-prefix) shift - # Convert spaces to underscores in prefix - PRIMER_PREFIX=$(echo $1 | tr " " "_") + # Convert all non-alphanumeric characters to underscores in prefix + PRIMER_PREFIX=$(echo -n $1 | tr -s -c "[:alnum:]" "_") ;; --2merMinReps) shift @@ -208,6 +213,14 @@ shift FILTERED_MICROSATS=$1 ;; + -primers|-occurrences|-rankmotifs) + FILTER_OPTIONS="$FILTER_OPTIONS $1" + ;; + -assembly) + FILTER_OPTIONS="$FILTER_OPTIONS $1" + shift + OUTPUT_ASSEMBLY=$1 + ;; *) echo Unknown option: $1 >&2 exit 1 @@ -309,15 +322,25 @@ exit 1 fi # -# Run the pal_finder_filter.pl script from Graeme Fox -if [ ! -z "$FILTERED_MICROSATS" ] ; then - echo "### Running filtering script ###" - perl $PALFINDER_FILTER_PL Output/PAL_summary.txt 2>&1 +# Sort outputs into a consistent order regardless of Perl version +echo "### Sorting outputs ###" +head -1 Output/PAL_summary.txt > Output/PAL_summary.sorted.txt +if [ "$PLATFORM" == "Illumina" ] ; then + grep -v "^readPairID" Output/PAL_summary.txt | sort -k 1 >> Output/PAL_summary.sorted.txt +else + grep -v "^SequenceID" Output/PAL_summary.txt | sort -k 1 >> Output/PAL_summary.sorted.txt +fi +mv Output/PAL_summary.sorted.txt Output/PAL_summary.txt +# +# Run the filtering & assembly script +if [ ! -z "$FILTERED_MICROSATS" ] || [ ! -z "$OUTPUT_ASSEMBLY" ] ; then + echo "### Running filtering & assembly script ###" + python $PALFINDER_FILTER -i $fastq_r1 -j $fastq_r2 -p Output/PAL_summary.txt $FILTER_OPTIONS 2>&1 if [ $? -ne 0 ] ; then - echo ERROR pal_finder_filter.pl exited with non-zero status >&2 + echo ERROR $PALFINDER_FILTER exited with non-zero status >&2 exit 1 - elif [ ! -f pal_finder_filter_output.txt ] ; then - echo ERROR no output from pal_finder_filter.pl >&2 + elif [ ! -f PAL_summary.filtered ] ; then + echo ERROR no output from $PALFINDER_FILTER >&2 exit 1 fi fi @@ -330,8 +353,14 @@ if [ -f Output/PAL_summary.txt ] ; then /bin/mv Output/PAL_summary.txt $PAL_SUMMARY fi -if [ ! -z "$FILTERED_MICROSATS" ] && [ -f pal_finder_filter_output.txt ] ; then - /bin/mv pal_finder_filter_output.txt $FILTERED_MICROSATS +if [ ! -z "$FILTERED_MICROSATS" ] && [ -f PAL_summary.filtered ] ; then + /bin/mv PAL_summary.filtered $FILTERED_MICROSATS +fi +if [ ! -z "$OUTPUT_ASSEMBLY" ] ; then + assembly=${fastq_r1%.*}_pal_finder_assembly_output.txt + if [ -f "$assembly" ] ; then + /bin/mv $assembly "$OUTPUT_ASSEMBLY" + fi fi if [ ! -z "$OUTPUT_CONFIG_FILE" ] && [ -f config.txt ] ; then /bin/mv config.txt $OUTPUT_CONFIG_FILE diff -r 771ebe02636f -r b6ccc7dd7b02 pal_finder_wrapper.xml --- a/pal_finder_wrapper.xml Mon Mar 23 07:01:37 2015 -0400 +++ b/pal_finder_wrapper.xml Fri Dec 04 07:43:30 2015 -0500 @@ -1,17 +1,28 @@ - - Find microsatellite repeat elements sequencing reads and design PCR primers to amplify them + + Find microsatellite repeat elements from sequencing reads and design PCR primers to amplify them + + perl + pal_finder + primer3_core + biopython + pandaseq + pal_finder_wrapper.sh #if str( $platform.platform_type ) == "illumina" - $platform.input_fastq_r1 $platform.input_fastq_r2 + #set $paired_input_type = $platform.paired_input_type_conditional.paired_input_type + #if $paired_input_type == "pair_of_files" + "$platform.paired_input_type_conditional.input_fastq_r1" + "$platform.paired_input_type_conditional.input_fastq_r2" + #else + "$platform.paired_input_type_conditional.input_fastq_pair.forward" + "$platform.paired_input_type_conditional.input_fastq_pair.reverse" + #end if #else - --454 $platform.input_fasta + --454 "$platform.input_fasta" #end if $output_microsat_summary $output_pal_summary - #if str( $platform.platform_type ) == "illumina" and $platform.filter_microsats - --filter_microsats $output_filtered_microsats - #end if #if $keep_config_file - --output_config_file $output_config_file + --output_config_file "$output_config_file" #end if --primer-prefix "$primer_prefix" --2merMinReps $min_2mer_repeats @@ -35,12 +46,18 @@ #if str( $mispriming.mispriming_options ) == "custom" --primer-mispriming-library $mispriming.mispriming_library #end if + #if str( $platform.platform_type ) == "illumina" + #if $platform.filters + #for $filter in str($platform.filters).split(',') + $filter + --filter_microsats "$output_filtered_microsats" + #end for + #end if + #if str( $platform.assembly ) == '-assembly' + $platform.assembly "$output_assembly" + #end if + #end if - - perl - pal_finder - primer3_core - @@ -49,11 +66,33 @@ - - - + + + + + + + + + + + + + + + + + + + @@ -117,12 +156,15 @@ help="Can be used to run pal_finder outside of Galaxy" /> - - - - platform['platform_type'] == 'illumina' and platform['filter_microsats'] + + + platform['platform_type'] == 'illumina' and platform['filters'] is not None - + + + platform['assembly'] is True + + keep_config_file is True @@ -132,24 +174,77 @@ - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + - @@ -163,9 +258,15 @@ directly from raw 454 or Illumina paired-end sequencing reads. It then designs PCR primers to amplify these repeat loci (Potentially Amplifiable Loci: PAL). -Optionally for Illumina data, the output from pal_finder can also be filtered to -remove any motifs without primer sequences, and with non-perfect microsatellites. -The microsatellites are then ranked by motif size (largest to smallest). +Optionally for Illumina data, one or more filters can be applied to the output from +pal_finder to: + + * Only include loci with designed primers + * Exclude loci where the primer sequences occur more than once in the reads + * Only include loci with 'perfect' motifs (and rank by motif size,largest to + smallest) + * Use PANDAseq to assemble paired-end reads and confirm primer sequences are + present in high-quality assembly Pal_finder runs the primer3_core program; information on the settings used in primer3_core can be found in the Primer3 manual at @@ -199,12 +300,12 @@ The paper is available at http://purl.com/STEVEROZEN/papers/rozen-and-skaletsky-2000-primer3.pdf -The filtering and sorting of the pal_finder output for Illumina data is performed -using a Perl script written by Graeme Fox at the University of Manchester, and which -is included with this tool. +The filtering and assembly of the pal_finder output for Illumina data is performed +using a Python utility written by Graeme Fox at the University of Manchester, and which +is included with this tool; this utility uses the BioPython and PANDAseq packages. Please kindly acknowledge both this Galaxy tool, the pal_finder and primer3 packages, and -the utility script if you use it in your work. +the utility script and its dependencies if you use it in your work. 10.1371/journal.pone.0030953 @Article{pmid10547847, - Author="Rozen, S. and Skaletsky, H. ", + Author="Rozen, S. and Skaletsky, H. ", Title="{{P}rimer3 on the {W}{W}{W} for general users and for biologist programmers}", Journal="Methods Mol. Biol.", Year="2000", @@ -222,5 +323,7 @@ Pages="365--386", URL="{http://purl.com/STEVEROZEN/papers/rozen-and-skaletsky-2000-primer3.pdf}" } + 10.1093/bioinformatics/btp163 + 10.1186/1471-2105-13-31 diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_assembly.out --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/illuminaPE_assembly.out Fri Dec 04 07:43:30 2015 -0500 @@ -0,0 +1,2 @@ +readPairID Forward Primer F Primer Position in Assembled Read Reverse Primer R Primer Position in Assembled Read Predicted Amplicon Size (bp) Motifs(bases) Assembled Read ID Assembled Read Sequence Raw Forward Read ID Raw Forward Read Sequence Raw Reverse Read ID Raw Reverse Read Sequence +ILLUMINA-545855:49:FC61RLR:2:1:19063:1614 1 1 0 AT(14) AT(14) AT(14) AT(14) >ILLUMINA-545855:49:FC61RLR:2:1:19063:1614 TATATATATATATACACATATATATATATATTTTTTACATTATTTCACTTCGCCCAAACTAGAGAGTCTAACAAAGTACAACCCAGCATATTAAAGTTCATCTCAGTTTTGTTCTGAAATGAGAAAAAAATATATATATATATGTTTATATATATATATA >ILLUMINA-545855:49:FC61RLR:2:1:19063:1614 TATATATATATATACACATATATATATATATTTTTTACATTATTTCACTTCGCCCAAACTAGAGAGTCTAACAAAGTACAACCCAGCATATTAAAGTTCATCTCAGTTTTGTTCTG >ILLUMINA-545855:49:FC61RLR:2:1:19063:1614 TATATATATATATAAACATATATATATATATTTTTTTCTCATTTCAGAACAAAAGTGAGATGAACTTTAATATGGTGGGGTGTATTTTGAGAGACTCTCTAGTTTGGGAGGAGTGA diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_assembly_after_filters.out --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/illuminaPE_assembly_after_filters.out Fri Dec 04 07:43:30 2015 -0500 @@ -0,0 +1,1 @@ +readPairID Forward Primer F Primer Position in Assembled Read Reverse Primer R Primer Position in Assembled Read Predicted Amplicon Size (bp) Motifs(bases) Assembled Read ID Assembled Read Sequence Raw Forward Read ID Raw Forward Read Sequence Raw Reverse Read ID Raw Reverse Read Sequence diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_filtered_microsats.out --- a/test-data/illuminaPE_filtered_microsats.out Mon Mar 23 07:01:37 2015 -0400 +++ b/test-data/illuminaPE_filtered_microsats.out Fri Dec 04 07:43:30 2015 -0500 @@ -1,4 +1,4 @@ -readPairID Motifs(bases) Bases in all Motifs Possible Extended Possible Spanning Primers found (1=y,0=n) F Primer Name Forward Primer R Primer Name Reverse Primer Amplicon Motifs Number motif bases in amplicon Primers on sep reads Extend with primers Spand with primers Occurances of Forward Primer in Reads Occurances of Reverse Primer in Reads Occurances of Amplifiable Primer Pair in Reads Occurances of Amplifiable Primer Pair in PALs -ILLUMINA-545855_0049_FC61RLR:2:1:8157:1636#0 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 -ILLUMINA-545855_0049_FC61RLR:2:1:10979:1695#0 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 -ILLUMINA-545855_0049_FC61RLR:2:1:1978:1220#0 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 +readPairID Motifs(bases) Bases in all Motifs Possible Extended Possible Spanning Primers found (1=y,0=n) F Primer Name Forward Primer R Primer Name Reverse Primer Amplicon Motifs Number motif bases in amplicon Primers on sep reads Extend with primers Spand with primers Occurances of Forward Primer in Reads Occurances of Reverse Primer in Reads Occurances of Amplifiable Primer Pair in Reads Occurances of Amplifiable Primer Pair in PALs R1_Sequence_ID R1_Sequence R2_Sequence_ID R2_Sequence +ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 1:N:0:TCCTGA TACTAGTCTAATAATTGCAGGCAGCTGAACTAGATAGGTCCTAAAGTACAGTGGGGAGGCTGGTGTGTGTGTGTGCATGGGATTGTCAGCCTTACCATCAGTCCTGATTTGTAGGT >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 2:N:0:TCCTGA TAAACAACCAAATGAAACCATCTTTTCTACACAGCTCAAGTAGCCCTACATACAACACAAGCCACCTACAAATCAGGACTGATGGTAAGGCTGACAATCCAATCCACCACAACAAC +ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 1:N:0:TCCTGA TCATAAGAATGAGCAGTAAACAAAGGCAAAGGGGAGATAACACACACACACAAAATAAAAAAACATCAATTTCTAATACACGCCTTTATTATAAAGAAATAAATCACTGAAAAACA >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 2:N:0:TCCTGA TCCTCTGACTAGGCAACAACAGCTTTTTTGCTCCTGGGCAGAGGTGTTCCGAGTGTATATTTTTTATAATTACGGCGCGCATTGGAAATTGATGTTATTTTATTTTGCGTGTGTGT +ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 1:N:0:TCCTGA TACTGTTTAGAATAGACTGTTCTCCCACTATATTTTGCATTGGTGCATACTCAGCTTTAGTAATAAGTGTGATTCTGGTAGAGAGAGAGAGAGATACCAACCTCTTCTTCCCACTA >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 2:N:0:TCCTGA TACTGTTTAGAAAGCCTGTTCCAGAACTTGATCACTGTCACAGAAAATCTTTCTTACTATCCAGACTGAAGCTACCCTGGTGCAGCTTTGTGCTGTTACCTTGAGTCATGTCATCA diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_filtered_microsats_assembly.out --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/illuminaPE_filtered_microsats_assembly.out Fri Dec 04 07:43:30 2015 -0500 @@ -0,0 +1,11 @@ +readPairID Motifs(bases) Bases in all Motifs Possible Extended Possible Spanning Primers found (1=y,0=n) F Primer Name Forward Primer R Primer Name Reverse Primer Amplicon Motifs Number motif bases in amplicon Primers on sep reads Extend with primers Spand with primers Occurances of Forward Primer in Reads Occurances of Reverse Primer in Reads Occurances of Amplifiable Primer Pair in Reads Occurances of Amplifiable Primer Pair in PALs +ILLUMINA-545855:0049:FC61RLR:2:1:1978:1220 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 +ILLUMINA-545855:0049:FC61RLR:2:1:5879:1238 AT(12) 12 0 +ILLUMINA-545855:0049:FC61RLR:2:1:17449:1584 AC(36) 36 0 +ILLUMINA-545855:0049:FC61RLR:2:1:8157:1636 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 +ILLUMINA-545855:0049:FC61RLR:2:1:8044:1926 AT(12) 12 0 +ILLUMINA-545855:0049:FC61RLR:2:1:5626:1554 AT(14) AC(16) AC(16) AT(12) 58 0 +ILLUMINA-545855:0049:FC61RLR:2:1:10979:1695 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 +ILLUMINA-545855:0049:FC61RLR:2:1:19063:1614 AT(14) AT(14) AT(14) AT(14) 56 0 +ILLUMINA-545855:0049:FC61RLR:2:1:6204:1090 TC(12) 12 0 +ILLUMINA-545855:0049:FC61RLR:2:1:8899:1514 AC(12) AC(12) 24 1 test_2 TCTTTATCTAAACACATCCTGAAATACC test_1 AAACGCAATTATTTTGAGATGTCC AC(12) AC(12) 24 1 1 2 1 1 diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_filtered_microsats_occurrences.out --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/illuminaPE_filtered_microsats_occurrences.out Fri Dec 04 07:43:30 2015 -0500 @@ -0,0 +1,4 @@ +readPairID Motifs(bases) Bases in all Motifs Possible Extended Possible Spanning Primers found (1=y,0=n) F Primer Name Forward Primer R Primer Name Reverse Primer Amplicon Motifs Number motif bases in amplicon Primers on sep reads Extend with primers Spand with primers Occurances of Forward Primer in Reads Occurances of Reverse Primer in Reads Occurances of Amplifiable Primer Pair in Reads Occurances of Amplifiable Primer Pair in PALs R1_Sequence_ID R1_Sequence R2_Sequence_ID R2_Sequence +ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 1:N:0:TCCTGA TACTGTTTAGAATAGACTGTTCTCCCACTATATTTTGCATTGGTGCATACTCAGCTTTAGTAATAAGTGTGATTCTGGTAGAGAGAGAGAGAGATACCAACCTCTTCTTCCCACTA >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 2:N:0:TCCTGA TACTGTTTAGAAAGCCTGTTCCAGAACTTGATCACTGTCACAGAAAATCTTTCTTACTATCCAGACTGAAGCTACCCTGGTGCAGCTTTGTGCTGTTACCTTGAGTCATGTCATCA +ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 1:N:0:TCCTGA TCATAAGAATGAGCAGTAAACAAAGGCAAAGGGGAGATAACACACACACACAAAATAAAAAAACATCAATTTCTAATACACGCCTTTATTATAAAGAAATAAATCACTGAAAAACA >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 2:N:0:TCCTGA TCCTCTGACTAGGCAACAACAGCTTTTTTGCTCCTGGGCAGAGGTGTTCCGAGTGTATATTTTTTATAATTACGGCGCGCATTGGAAATTGATGTTATTTTATTTTGCGTGTGTGT +ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 1:N:0:TCCTGA TACTAGTCTAATAATTGCAGGCAGCTGAACTAGATAGGTCCTAAAGTACAGTGGGGAGGCTGGTGTGTGTGTGTGCATGGGATTGTCAGCCTTACCATCAGTCCTGATTTGTAGGT >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 2:N:0:TCCTGA TAAACAACCAAATGAAACCATCTTTTCTACACAGCTCAAGTAGCCCTACATACAACACAAGCCACCTACAAATCAGGACTGATGGTAAGGCTGACAATCCAATCCACCACAACAAC diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_filtered_microsats_primers.out --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/illuminaPE_filtered_microsats_primers.out Fri Dec 04 07:43:30 2015 -0500 @@ -0,0 +1,5 @@ +readPairID Motifs(bases) Bases in all Motifs Possible Extended Possible Spanning Primers found (1=y,0=n) F Primer Name Forward Primer R Primer Name Reverse Primer Amplicon Motifs Number motif bases in amplicon Primers on sep reads Extend with primers Spand with primers Occurances of Forward Primer in Reads Occurances of Reverse Primer in Reads Occurances of Amplifiable Primer Pair in Reads Occurances of Amplifiable Primer Pair in PALs R1_Sequence_ID R1_Sequence R2_Sequence_ID R2_Sequence +ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 1:N:0:TCCTGA TACTGTTTAGAATAGACTGTTCTCCCACTATATTTTGCATTGGTGCATACTCAGCTTTAGTAATAAGTGTGATTCTGGTAGAGAGAGAGAGAGATACCAACCTCTTCTTCCCACTA >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 2:N:0:TCCTGA TACTGTTTAGAAAGCCTGTTCCAGAACTTGATCACTGTCACAGAAAATCTTTCTTACTATCCAGACTGAAGCTACCCTGGTGCAGCTTTGTGCTGTTACCTTGAGTCATGTCATCA +ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 1:N:0:TCCTGA TCATAAGAATGAGCAGTAAACAAAGGCAAAGGGGAGATAACACACACACACAAAATAAAAAAACATCAATTTCTAATACACGCCTTTATTATAAAGAAATAAATCACTGAAAAACA >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 2:N:0:TCCTGA TCCTCTGACTAGGCAACAACAGCTTTTTTGCTCCTGGGCAGAGGTGTTCCGAGTGTATATTTTTTATAATTACGGCGCGCATTGGAAATTGATGTTATTTTATTTTGCGTGTGTGT +ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 1:N:0:TCCTGA TACTAGTCTAATAATTGCAGGCAGCTGAACTAGATAGGTCCTAAAGTACAGTGGGGAGGCTGGTGTGTGTGTGTGCATGGGATTGTCAGCCTTACCATCAGTCCTGATTTGTAGGT >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 2:N:0:TCCTGA TAAACAACCAAATGAAACCATCTTTTCTACACAGCTCAAGTAGCCCTACATACAACACAAGCCACCTACAAATCAGGACTGATGGTAAGGCTGACAATCCAATCCACCACAACAAC +ILLUMINA-545855:49:FC61RLR:2:1:8899:1514 AC(12) AC(12) 24 1 test_2 TCTTTATCTAAACACATCCTGAAATACC test_1 AAACGCAATTATTTTGAGATGTCC AC(12) AC(12) 24 1 1 2 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:8899:1514 1:N:0:TCCTGA TCTTTATCTAAACACATCCTGAAATACCATCTGTTACACACACACACAGCAGTGGAAGTATAAAAAAAAATCTGGACATCTCAAAATAATTGCGTTTCTGAAGTGTTACATTTTTC >ILLUMINA-545855:49:FC61RLR:2:1:8899:1514 2:N:0:TCCTGA TATCATTGAAATTTTTATAAAAACTGTGAAGAGAAAAATGTAACACTTCAGAAACGCAATTATTTTGAGATGTCCAGATTTTTTTTTATACTTCCACTGCTGTGTGTGTGTGTAAC diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_filtered_microsats_rankmotifs.out --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/illuminaPE_filtered_microsats_rankmotifs.out Fri Dec 04 07:43:30 2015 -0500 @@ -0,0 +1,8 @@ +readPairID Motifs(bases) Bases in all Motifs Possible Extended Possible Spanning Primers found (1=y,0=n) F Primer Name Forward Primer R Primer Name Reverse Primer Amplicon Motifs Number motif bases in amplicon Primers on sep reads Extend with primers Spand with primers Occurances of Forward Primer in Reads Occurances of Reverse Primer in Reads Occurances of Amplifiable Primer Pair in Reads Occurances of Amplifiable Primer Pair in PALs R1_Sequence_ID R1_Sequence R2_Sequence_ID R2_Sequence +ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 1:N:0:TCCTGA TACTAGTCTAATAATTGCAGGCAGCTGAACTAGATAGGTCCTAAAGTACAGTGGGGAGGCTGGTGTGTGTGTGTGCATGGGATTGTCAGCCTTACCATCAGTCCTGATTTGTAGGT >ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 2:N:0:TCCTGA TAAACAACCAAATGAAACCATCTTTTCTACACAGCTCAAGTAGCCCTACATACAACACAAGCCACCTACAAATCAGGACTGATGGTAAGGCTGACAATCCAATCCACCACAACAAC +ILLUMINA-545855:49:FC61RLR:2:1:8044:1926 AT(12) 12 0 >ILLUMINA-545855:49:FC61RLR:2:1:8044:1926 1:N:0:TCCTGA TAGATTTTTTTTTTTATATATATATAAATATAGATGTACATATATTTATATAAATATAAAAGCACAGCATCCTCCTGTCTCTCCTCCTGATTTATTATGGTTAAAGCTTGTGACAG >ILLUMINA-545855:49:FC61RLR:2:1:8044:1926 2:N:0:TCCTGA TCAGGCAAGGTCACTGCCACCACTGGGGAGTGCCTGTTTCTGAAGGGCCCAGCCAACTCTGTCACAAGCTTTAACCATAATAAATCAGGAGGAGAGACAGGAGGATGCTGTGCTTT +ILLUMINA-545855:49:FC61RLR:2:1:6204:1090 TC(12) 12 0 >ILLUMINA-545855:49:FC61RLR:2:1:6204:1090 1:N:0:TCCTGA TGCTTTGGTTCTAAGAGAAAAACAATTATTATAAATGTTTATAATTGATGATAAGCATTTTTGTACAAAGCCAAGACCATTCTGAATGAAGCACCCAAAAAGCCCGGAGGCAACAA >ILLUMINA-545855:49:FC61RLR:2:1:6204:1090 2:N:0:TCCTGA TGCTTTGGTTCTAAGAGAAAAACAAGTGATGCACAAGCAATTCCTCGCCACCACCCAACTGATGCCCAGCCACCCCCCCAAGCAGTGAAAGAGAGAGAGAGATGAACCCCCTTCAA +ILLUMINA-545855:49:FC61RLR:2:1:5879:1238 AT(12) 12 0 >ILLUMINA-545855:49:FC61RLR:2:1:5879:1238 1:N:0:TCCTGA TCCCCACCCTGTCATGGTTCTATGTTTTTGTTTTTGTTTTTGTTTTTATGGTTTCCGTATTCCACATTAAAACCTTATGTAACGTACGGGCCAATAAATAGTTACTCGCCATATCC >ILLUMINA-545855:49:FC61RLR:2:1:5879:1238 2:N:0:TCCTGA TCCCCACCCTGTCATGGTTCTATGTATATATATATAGCCATGTGTGTGGTACCAGGGATAGGTACCTGGGATTGGGGCAGTGACACTTTAGTGCCCCGTACACTACATGATGTTTT +ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 1:N:0:TCCTGA TCATAAGAATGAGCAGTAAACAAAGGCAAAGGGGAGATAACACACACACACAAAATAAAAAAACATCAATTTCTAATACACGCCTTTATTATAAAGAAATAAATCACTGAAAAACA >ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 2:N:0:TCCTGA TCCTCTGACTAGGCAACAACAGCTTTTTTGCTCCTGGGCAGAGGTGTTCCGAGTGTATATTTTTTATAATTACGGCGCGCATTGGAAATTGATGTTATTTTATTTTGCGTGTGTGT +ILLUMINA-545855:49:FC61RLR:2:1:17449:1584 AC(36) 36 0 >ILLUMINA-545855:49:FC61RLR:2:1:17449:1584 1:N:0:TCCTGA TCGTAGCATGTGTATGCTTTGGGGTTTCATGCTGTTGATTCATAACTGCTGCTGGCTGTAGACTGAACCTTCTGGGTAGGAGGAATATGCTTAGACAAGCACACCAGTCAGCCCGA >ILLUMINA-545855:49:FC61RLR:2:1:17449:1584 2:N:0:TCCTGA TCTGTGTGTGAGCACACACACACACACACACACACACACACACACACATGCAGGTACTTGCTCTGCCACCCCTGGCGGGCTGCGTGGTGTGCCTGACGACGTATTCTAATCCTACA +ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 1:N:0:TCCTGA TACTGTTTAGAATAGACTGTTCTCCCACTATATTTTGCATTGGTGCATACTCAGCTTTAGTAATAAGTGTGATTCTGGTAGAGAGAGAGAGAGATACCAACCTCTTCTTCCCACTA >ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 2:N:0:TCCTGA TACTGTTTAGAAAGCCTGTTCCAGAACTTGATCACTGTCACAGAAAATCTTTCTTACTATCCAGACTGAAGCTACCCTGGTGCAGCTTTGTGCTGTTACCTTGAGTCATGTCATCA diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_microsats.out --- a/test-data/illuminaPE_microsats.out Mon Mar 23 07:01:37 2015 -0400 +++ b/test-data/illuminaPE_microsats.out Fri Dec 04 07:43:30 2015 -0500 @@ -1,11 +1,11 @@ readPairID Motifs(bases) Bases in all Motifs Possible Extended Possible Spanning Primers found (1=y,0=n) F Primer Name Forward Primer R Primer Name Reverse Primer Amplicon Motifs Number motif bases in amplicon Primers on sep reads Extend with primers Spand with primers Occurances of Forward Primer in Reads Occurances of Reverse Primer in Reads Occurances of Amplifiable Primer Pair in Reads Occurances of Amplifiable Primer Pair in PALs -ILLUMINA-545855_0049_FC61RLR:2:1:8044:1926#0 AT(12) 12 0 -ILLUMINA-545855_0049_FC61RLR:2:1:1978:1220#0 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 -ILLUMINA-545855_0049_FC61RLR:2:1:5879:1238#0 AT(12) 12 0 -ILLUMINA-545855_0049_FC61RLR:2:1:8899:1514#0 AC(12) AC(12) 24 1 test_2 TCTTTATCTAAACACATCCTGAAATACC test_1 AAACGCAATTATTTTGAGATGTCC AC(12) AC(12) 24 1 1 2 1 1 -ILLUMINA-545855_0049_FC61RLR:2:1:10979:1695#0 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 -ILLUMINA-545855_0049_FC61RLR:2:1:5626:1554#0 AT(14) AC(16) AC(16) AT(12) 58 0 -ILLUMINA-545855_0049_FC61RLR:2:1:8157:1636#0 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 -ILLUMINA-545855_0049_FC61RLR:2:1:19063:1614#0 AT(14) AT(14) AT(14) AT(14) 56 0 -ILLUMINA-545855_0049_FC61RLR:2:1:17449:1584#0 AC(36) 36 0 -ILLUMINA-545855_0049_FC61RLR:2:1:6204:1090#0 TC(12) 12 0 +ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 TC(14) 14 1 test_7 TTCTCCCACTATATTTTGCATTGG test_8 TCCAGACTGAAGCTACCCTGG TC(14) 14 1 1 1 1 1 +ILLUMINA-545855:49:FC61RLR:2:1:17449:1584 AC(36) 36 0 +ILLUMINA-545855:49:FC61RLR:2:1:19063:1614 AT(14) AT(14) AT(14) AT(14) 56 0 +ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 AC(12) 12 1 test_3 GCAGTAAACAAAGGCAAAGGG test_4 CCTGGGCAGAGGTGTTCC AC(12) 12 1 1 1 1 1 +ILLUMINA-545855:49:FC61RLR:2:1:5626:1554 AT(14) AC(16) AC(16) AT(12) 58 0 +ILLUMINA-545855:49:FC61RLR:2:1:5879:1238 AT(12) 12 0 +ILLUMINA-545855:49:FC61RLR:2:1:6204:1090 TC(12) 12 0 +ILLUMINA-545855:49:FC61RLR:2:1:8044:1926 AT(12) 12 0 +ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 AC(12) 12 1 test_5 AAGTACAGTGGGGAGGCTGG test_6 TTTTCTACACAGCTCAAGTAGCCC AC(12) 12 1 1 1 1 1 +ILLUMINA-545855:49:FC61RLR:2:1:8899:1514 AC(12) AC(12) 24 1 test_2 TCTTTATCTAAACACATCCTGAAATACC test_1 AAACGCAATTATTTTGAGATGTCC AC(12) AC(12) 24 1 1 2 1 1 diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_r1.fq --- a/test-data/illuminaPE_r1.fq Mon Mar 23 07:01:37 2015 -0400 +++ b/test-data/illuminaPE_r1.fq Fri Dec 04 07:43:30 2015 -0500 @@ -1,40 +1,40 @@ -@ILLUMINA-545855_0049_FC61RLR:2:1:10979:1695#0/1 +@ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 1:N:0:TCCTGA TACTGTTTAGAATAGACTGTTCTCCCACTATATTTTGCATTGGTGCATACTCAGCTTTAGTAATAAGTGTGATTCTGGTAGAGAGAGAGAGAGATACCAACCTCTTCTTCCCACTA + -hhhhhghhhfgghhcfghhhhhhghhhhhhhhhhhhgfhhhhgfhhhhggghggfghhggdgghfgfcgcgggffgdf`gfcfdgdfdfafbdcaccfddecddbfcdfcdcdcdW -@ILLUMINA-545855_0049_FC61RLR:2:1:17449:1584#0/1 +IIIIIHIIIGHHIIDGHIIIIIIHIIIIIIIIIIIIHGIIIIHGIIIIHHHIHHGHIIHHEHHIGHGDHDHHHGGHEGAHGDGEHEGEGBGCEDBDDGEEFDEECGDEGDEDEDE8 +@ILLUMINA-545855:49:FC61RLR:2:1:17449:1584 1:N:0:TCCTGA TCGTAGCATGTGTATGCTTTGGGGTTTCATGCTGTTGATTCATAACTGCTGCTGGCTGTAGACTGAACCTTCTGGGTAGGAGGAATATGCTTAGACAAGCACACCAGTCAGCCCGA + -hhhhhhhhhhghhhhhfhhhhehhhhhhfhhhhfahgahhhghhhhghhgggdgeggedegdedhbgdffcacaccM\^^[`_^^^aaaacaaa^_bddd_aaa_a[VQ^Z_BBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:19063:1614#0/1 +IIIIIIIIIIHIIIIIGIIIIFIIIIIIGIIIIGBIHBIIIHIIIIHIIHHHEHFHHFEFHEFEICHEGGDBDBDD.=??EEEBDGDD;BD8DDBBDDBGHGHHHHEFE=DBCDEEEBEBEGHGAFH@E +@ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 1:N:0:TCCTGA TCATAAGAATGAGCAGTAAACAAAGGCAAAGGGGAGATAACACACACACACAAAATAAAAAAACATCAATTTCTAATACACGCCTTTATTATAAAGAAATAAATCACTGAAAAACA + -cccccacaccaV^aaaTaa]P^[^WW]ccc^SGURUVZ]^Q[PUS\Z]W[Occc]]`U`^]ZZU]JU]][]SLWSWSWWWE_c__cc[cZc]]^[XccZUccb[ccZ[WW_BBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:5626:1554#0/1 +DDDDDBDBDDB7?BBB5BB>1?DDD?4(6367;>?2<164=;>8<0DDD>>A6A?>;;6>+6>><>4-8484888&@D@@DD>?<9DD;6DDC=B=@@??A9;B@@@@###################################################################### +@ILLUMINA-545855:49:FC61RLR:2:1:5879:1238 1:N:0:TCCTGA TCCCCACCCTGTCATGGTTCTATGTTTTTGTTTTTGTTTTTGTTTTTATGGTTTCCGTATTCCACATTAAAACCTTATGTAACGTACGGGCCAATAAATAGTTACTCGCCATATCC + -BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:6204:1090#0/1 +#################################################################################################################### +@ILLUMINA-545855:49:FC61RLR:2:1:6204:1090 1:N:0:TCCTGA TGCTTTGGTTCTAAGAGAAAAACAATTATTATAAATGTTTATAATTGATGATAAGCATTTTTGTACAAAGCCAAGACCATTCTGAATGAAGCACCCAAAAAGCCCGGAGGCAACAA + -BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:8044:1926#0/1 +#################################################################################################################### +@ILLUMINA-545855:49:FC61RLR:2:1:8044:1926 1:N:0:TCCTGA TAGATTTTTTTTTTTATATATATATAAATATAGATGTACATATATTTATATAAATATAAAAGCACAGCATCCTCCTGTCTCTCCTCCTGATTTATTATGGTTAAAGCTTGTGACAG + -gggggggggggggggegefegdeeceXQ\_\]ZZZ\gggfggggggggggggggggfgggeggggegecggggggggggggggggfggffggggggggggdggggfdgggded]da -@ILLUMINA-545855_0049_FC61RLR:2:1:8157:1636#0/1 +HHHHHHHHHHHHHHHFHFGFHEFFDF92=@=>;;;=HHHGHHHHHHHHHHHHHHHHGHHHFHHHHFHFDHHHHHHHHHHHHHHHHGHHGGHHHHHHHHHHEHHHHGEHHHEFE>EB +@ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 1:N:0:TCCTGA TACTAGTCTAATAATTGCAGGCAGCTGAACTAGATAGGTCCTAAAGTACAGTGGGGAGGCTGGTGTGTGTGTGTGCATGGGATTGTCAGCCTTACCATCAGTCCTGATTTGTAGGT + -gggggggggggggegggggfggggggfggggfgggggg]ggffffeeggggfgfggeggggffafcb`b]bacaccbefdc_acca_aaaadbbc_[bb]b\^X\\_bdba\aaaW -@ILLUMINA-545855_0049_FC61RLR:2:1:8899:1514#0/1 +HHHHHHHHHHHHHFHHHHHGHHHHHHGHHHHGHHHHHH>HHGGGGFFHHHHGHGHHFHHHHGGBGDCAC>CBDBDDCFGED@BDDB@BBBBECCD@C=?9==@CECB=BBB8 +@ILLUMINA-545855:49:FC61RLR:2:1:8899:1514 1:N:0:TCCTGA TCTTTATCTAAACACATCCTGAAATACCATCTGTTACACACACACACAGCAGTGGAAGTATAAAAAAAAATCTGGACATCTCAAAATAATTGCGTTTCTGAAGTGTTACATTTTTC + -hhhhhghhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhfhhhhhfhhhhhhhhhhhhhhggfhhhhghgggghgggggggfgggggfegdgdggggggghh] +IIIIIHIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIIGIIIIIGIIIIIIIIIIIIIIHHGIIIIHIHHHHIHHHHHHHGHHHHHGFHEHEHHHHHHHII> diff -r 771ebe02636f -r b6ccc7dd7b02 test-data/illuminaPE_r2.fq --- a/test-data/illuminaPE_r2.fq Mon Mar 23 07:01:37 2015 -0400 +++ b/test-data/illuminaPE_r2.fq Fri Dec 04 07:43:30 2015 -0500 @@ -1,40 +1,40 @@ -@ILLUMINA-545855_0049_FC61RLR:2:1:10979:1695#0/2 +@ILLUMINA-545855:49:FC61RLR:2:1:10979:1695 2:N:0:TCCTGA TACTGTTTAGAAAGCCTGTTCCAGAACTTGATCACTGTCACAGAAAATCTTTCTTACTATCCAGACTGAAGCTACCCTGGTGCAGCTTTGTGCTGTTACCTTGAGTCATGTCATCA + -hhhhhghhhhhghhhhghghhhhhhhghhhghhhghgfhhhhhhgdgggggggghhghhgeggdgghfggfgfhgfggef`fhdggfdfgaehecagggfcegacagffefcWda_ -@ILLUMINA-545855_0049_FC61RLR:2:1:17449:1584#0/2 +IIIIIHIIIIIHIIIIHIHIIIIIIIHIIIHIIIHIHGIIIIIIHEHHHHHHHHIIHIIHFHHEHHIGHHGHGIHGHHFGAGIEHHGEGHBFIFDBHHHGDFHBDBHGGFGD8EB@ +@ILLUMINA-545855:49:FC61RLR:2:1:17449:1584 2:N:0:TCCTGA TCTGTGTGTGAGCACACACACACACACACACACACACACACACACACATGCAGGTACTTGCTCTGCCACCCCTGGCGGGCTGCGTGGTGTGCCTGACGACGTATTCTAATCCTACA + -fffff^bcbdbdaded`ffafdcfcff]cffccccaffffffedcafaR_BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:19063:1614#0/2 +GGGGG?CDCECEBEFEAGGBGEDGDGG>DGGDDDDBGGGGGGFEDBGB3@################################################################## +@ILLUMINA-545855:49:FC61RLR:2:1:19063:1614 2:N:0:TCCTGA TATATATATATATAAACATATATATATATATTTTTTTCTCATTTCAGAACAAAAGTGAGATGAACTTTAATATGGTGGGGTGTATTTTGAGAGACTCTCTAGTTTGGGAGGAGTGA + -ccccccccccccYc_cJccccccccccccUccccc]`_YT]_BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:1978:1220#0/2 +DDDDDDDDDDDD:D@D+DDDDDDDDDDDD6DDDDD>A@:5>@########################################################################## +@ILLUMINA-545855:49:FC61RLR:2:1:1978:1220 2:N:0:TCCTGA TCCTCTGACTAGGCAACAACAGCTTTTTTGCTCCTGGGCAGAGGTGTTCCGAGTGTATATTTTTTATAATTACGGCGCGCATTGGAAATTGATGTTATTTTATTTTGCGTGTGTGT + -a^N^BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:5626:1554#0/2 +B?/?################################################################################################################ +@ILLUMINA-545855:49:FC61RLR:2:1:5626:1554 2:N:0:TCCTGA TCTAATATTATATATATCTGTGTGTGTATATATATATATACACACACACACACACATTGACATAAAAGCGAAATATAAACATTAGCAGCTGGGGCTAAAATAAAAGCAGGAAGGTT + -hhhhhhhhhhhhhhhhhhhhhhgggghghhghhghghghghhhhhghhfgQeWdQd\URUY^aa[^\\K`JL\\[W``dQ`BBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:5879:1238#0/2 +IIIIIIIIIIIIIIIIIIIIIIHHHHIHIIHIIHIHIHIHIIIIIHIIGH2F8E2E=636:?BBBEC>@B@DCBBBECBBBA>B<;BA@A@###### +@ILLUMINA-545855:49:FC61RLR:2:1:6204:1090 2:N:0:TCCTGA TGCTTTGGTTCTAAGAGAAAAACAAGTGATGCACAAGCAATTCCTCGCCACCACCCAACTGATGCCCAGCCACCCCCCCAAGCAGTGAAAGAGAGAGAGAGATGAACCCCCTTCAA + -gggcagggdefggggdgegdgccccc_ggdggddgdeedddfcdffffdfda]dab]______aa_edaeaaa_`]```[Z]`]ZR]\^^]]aa]^]_^P^]YXI_BBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:8044:1926#0/2 +HHHDBHHHEFGHHHHEHFHEHDDDDD@HHEHHEEHEFFEEEGDEGGGGEGEB>EBC>@@@@@@BB@FEBFBBB@A>AAA<;>A>;3>=??>>BB>?>@?1?>:9*@########## +@ILLUMINA-545855:49:FC61RLR:2:1:8044:1926 2:N:0:TCCTGA TCAGGCAAGGTCACTGCCACCACTGGGGAGTGCCTGTTTCTGAAGGGCCCAGCCAACTCTGTCACAAGCTTTAACCATAATAAATCAGGAGGAGAGACAGGAGGATGCTGTGCTTT + -hhhhhhhhhhghhhhhhhhhhhhhhfhhhhehhhhhfgghhhhhffdhgfgfgggffbggbffffffgfgfdfdfdfffcfadbbaffdcfaZW^aaaac`ab_YR\\Z\Y[ROYU -@ILLUMINA-545855_0049_FC61RLR:2:1:8157:1636#0/2 +IIIIIIIIIIHIIIIIIIIIIIIIIGIIIIFIIIIIGHHIIIIIGGEIHGHGHHHGGCHHCGGGGGGHGHGEGEGEGGGDGBECCBGGEDGB;8?BBBBDABC@:3==;=:<30:6 +@ILLUMINA-545855:49:FC61RLR:2:1:8157:1636 2:N:0:TCCTGA TAAACAACCAAATGAAACCATCTTTTCTACACAGCTCAAGTAGCCCTACATACAACACAAGCCACCTACAAATCAGGACTGATGGTAAGGCTGACAATCCAATCCACCACAACAAC + -geggggggggggggcgfggcggggggggggggggggggfffggfgggggggggggfggggg_gggegfgeggdggggggcgaedaageecgd]degadecBBBBBBBBBBBBBBBB -@ILLUMINA-545855_0049_FC61RLR:2:1:8899:1514#0/2 +HFHHHHHHHHHHHHDHGHHDHHHHHHHHHHHHHHHHHHGGGHHGHHHHHHHHHHHGHHHHH@HHHFHGHFHHEHHHHHHDHBFEBBHFFDHE>EFHBEFD################ +@ILLUMINA-545855:49:FC61RLR:2:1:8899:1514 2:N:0:TCCTGA TATCATTGAAATTTTTATAAAAACTGTGAAGAGAAAAATGTAACACTTCAGAAACGCAATTATTTTGAGATGTCCAGATTTTTTTTTATACTTCCACTGCTGTGTGTGTGTGTAAC + -hfJfffhhhhhhhhhhchhhhhhfgghhghhhhhdfghghghhghhhhhhhhhhhhhhghhchhhhhdchhhchgfgehhhhhhhhhgheeagfhfaffgacaedfdfbfdhdcda +IG+GGGIIIIIIIIIIDIIIIIIGHHIIHIIIIIEGHIHIHIIHIIIIIIIIIIIIIIHIIDIIIIIEDIIIDIHGHFIIIIIIIIIHIFFBHGIGBGGHBDBFEGEGCGEIEDEB diff -r 771ebe02636f -r b6ccc7dd7b02 tool_dependencies.xml --- a/tool_dependencies.xml Mon Mar 23 07:01:37 2015 -0400 +++ b/tool_dependencies.xml Fri Dec 04 07:43:30 2015 -0500 @@ -64,4 +64,39 @@ primer3_core + + + + pip install --install-option "--prefix=$INSTALL_DIR" https://pypi.python.org/packages/source/b/biopython/biopython-1.65.tar.gz + + $INSTALL_DIR/lib/python2.7/site-packages + $INSTALL_DIR/lib64/python2.7/site-packages + + + + BioPython 1.65 + + + + + https://github.com/neufeld/pandaseq/archive/v2.8.1.tar.gz + ./autogen.sh + ./configure --prefix=$INSTALL_DIR + make + make install + + $INSTALL_DIR/bin + $INSTALL_DIR/lib + + + + PANDASeq 2.8.1 + + PANDASEQ is a program to align Illumina reads, optionally + with PCR primers embedded in the sequence, and reconstruct + an overlapping sequence. + + https://github.com/neufeld/pandaseq + +