# HG changeset patch # User tyty # Date 1416344071 18000 # Node ID a1ce42d5258d5e091c6391d7a0de784cef1155f8 # Parent c1f1b552c1b8b2c4c400a0ae047cf87e9e60a878 Uploaded diff -r c1f1b552c1b8 -r a1ce42d5258d predict/.DS_Store Binary file predict/.DS_Store has changed diff -r c1f1b552c1b8 -r a1ce42d5258d predict/._.DS_Store Binary file predict/._.DS_Store has changed diff -r c1f1b552c1b8 -r a1ce42d5258d predict/._predict_RNAs.py Binary file predict/._predict_RNAs.py has changed diff -r c1f1b552c1b8 -r a1ce42d5258d predict/id_list_test.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/id_list_test.txt Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,1 @@ +AT3G05880.1 diff -r c1f1b552c1b8 -r a1ce42d5258d predict/log.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/log.txt Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,3 @@ +a /Users/yintang/Project/galaxy/galaxy-dist/tools/pipeline_programs/predict/output_qicbsuLr/AT3G05880.1.ct +a /Users/yintang/Project/galaxy/galaxy-dist/tools/pipeline_programs/predict/output_qicbsuLr/AT3G05880.1.ps +a /Users/yintang/Project/galaxy/galaxy-dist/tools/pipeline_programs/predict/output_qicbsuLr/AT3G05880.1.tif diff -r c1f1b552c1b8 -r a1ce42d5258d predict/parse_dis_pac.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/parse_dis_pac.py Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,43 @@ +#parse reactivity file into a dictionary + +import sys + +def parse_dist(in_file): + result = [] + distribution = {} + name = [] + f = open(in_file) + for aline in f.readlines(): + line = aline.strip() + dis = line.strip() + dist = dis.split('\t') #split the line and the reactivites or reads are in a list + if len(dist) > 0: + if len(dist) == 1: + if dist[0].strip().find('coverage')==-1: + name.append(line) #add the name in the name list + flag = 1 + t_name = line + else: + distri = [] + for i in range(0, len(dist)): + distri.append(dist[i].strip()) + distribution[t_name] = distri #add the list of reactivities into a dictionary + result.append(name) + result.append(distribution) #Output the dictionary + f.close() + return result + + + + + + + + + + + + + + + diff -r c1f1b552c1b8 -r a1ce42d5258d predict/parse_dis_pac.pyc Binary file predict/parse_dis_pac.pyc has changed diff -r c1f1b552c1b8 -r a1ce42d5258d predict/predict_RNAs.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/predict_RNAs.py Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,91 @@ +#RNA structure prediction & Output and illustrate reactivities + +import sys +from parse_dis_pac import * +from read_file import * +from Bio import SeqIO +import os +from rtts_plot import * +import random +import string + + +id_file = sys.argv[1] +seq_file = sys.argv[2] +output_file = sys.argv[4] + + +flag = 0 +if sys.argv[3]!='None': #input reactivity file if provided + react_file = sys.argv[3] + react = parse_dist(react_file) + react = react[1] + flag = 1 + +syspath = os.getcwd() + +ids = read_t_file(id_file) +sequences = SeqIO.parse(seq_file, 'fasta') + + +seqs = {} +for seq in sequences: + seqs[seq.id] = seq.seq.tostring() + +if len(ids)>100: #setup a limit of the number of sequence to be predicted + print("Number of sequences exceeds limitation!") + sys.exit(0) + + +#predict RNA structures +output_directory = os.path.join(syspath, "output_files/") +os.makedirs(output_directory) +for i in range(len(ids)): + id_s = ids[i][0] + print(id_s) + #Put RNA sequence and reactivities into files + if id_s in seqs: + f = file(syspath+"temp.txt", 'w') + f.write('>'+id_s) + f.write('\n') + f.write(seqs[id_s]) + f.close() + if flag == 0: + os.system("Fold "+syspath+"temp.txt"+" "+output_directory+id_s+".ct") + if flag == 1: + if id_s in react: + f = file(syspath+"constraint.txt",'w') + make_plot(react[id_s],id_s,(output_directory)) #make a plot of the distribution of the reactivites of the input RNA + #h = file(syspath+"output_f/transcript_reactivities.txt", 'w') + #h.write(id_s) + #h.write('\n') + for j in range(0, (len(react[id_s]))): + if react[id_s][j]!='NA': + f.write(str(j+1)) + f.write('\t') + f.write(str(react[id_s][j])) + f.write('\n') + #h.write(str(react[id_s][j])) #Output the reactivities + #h.write('\t') + f.close() + #h.write('\n') + #h.write('\n') + os.system("Fold "+syspath+"temp.txt"+" -sh"+" "+syspath+"constraint.txt"+" "+output_directory+id_s+".ct") + else: + print(id_s+" not in the data of react!") + os.system("draw "+output_directory+id_s+".ct "+output_directory+"/"+id_s+".ps") + else: + print(id_s+" not in the data of sequences!") + +#Remove the unnecessary files +os.system("tar -zcvPf "+output_file+" "+output_directory+"/"+"*.* 2>"+output_directory+"log.txt") +os.system("rm -f "+syspath+"temp.txt") +os.system("rm -r "+output_directory) +if flag == 1: + os.system("rm -f "+syspath+"constraint.txt") + # h.close() + + + + + diff -r c1f1b552c1b8 -r a1ce42d5258d predict/predict_RNAs.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/predict_RNAs.xml Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,59 @@ + + + predict_RNAs.py $rna_list $reference_file $reactivity_file $output + + biopython + numpy + matplotlib + + + + + + + + + + + + + + + + + + + + + +**TIPS**: + +----- + +**Input**: + +* 1. A file with transcript Ids (Max num. 20), (each ID one line) +* 2. Reference file (fasta) used to map the reads to +* [Optional]: +* 1. A reactivity file with structural reactivity for each nucleotide on the sequence provided + +----- + +**Output**: + +* 1. .ct files with predicted RNA structures [transciptID.ct] +* 2. .ps files which depict the predicted RNA structures [[transciptID.ps] +* [Optional] +* 3. .png files that shows the distribution of the reactivity of each nucleotide on the transcripts of interest. [transciptID.png] +* 4. A .txt file that includes the reactivities of all the nucleotides on the transcripts of interest. [transciptID.txt] + +----- + +**Attention** + +Make sure any of the transcript Ids does not contain "|" or space! + + + + + diff -r c1f1b552c1b8 -r a1ce42d5258d predict/rRNA.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/rRNA.txt Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,8 @@ +>25s rRNA 3375nts +GCGACCCCAGGTCAGGCGGGATTACCCGCTGAGTTTAAGCATATCAATAAGCGGAGGAAAAGAAACTAACAAGGATTCCCTTAGTAACGGCGAGCGAACCGGGAAGAGCCCAGCTTGAAAATCGGACGTCTTCGGCGTTCGAATTGTAGTCTGGAGAAGCGTCCTCAGCGACGGACCGGGCCTAAGTTCCCTGGAAAGGGGCGCCAGAGAGGGTGAGAGCCCGTCGTGCCCGGACCCTGTCGCACCACGAGGCGCTGTCTACGAGTCGGGTTGTTTGGGAATGCAGCCCCAATCGGGCGGTAAATTCCGTCCAAGGCTAAATACGGGCGAGAGACCGATAGCGAACAAGTACCGCGAGGTAAAGATGAAAAGGACTTTGAAAAGAGAGTCAAAGAGTGCTTGAAATTGTCGGGAGGGAAGCGGATGGGGGCCGGCGATGCGTCCTGGTCGGATGCGGAACGGAGCAATCCGGTCCGCCGATCGATTCGGGGCGTGGACCGACGCGGATTACGGTGGCGGCCTAAGCCCGGGCTTTTGATACGCTTGTGGAGACGTCGCTGCCGTGATCGTGGTCTGCAGCACGCGCCTAACGGCGTGCCTCGGCATCAGCGTGCTCCGGGCGTCGGCCTGTGGGCTCCCCATTCGACCCGTCTTGAAACACGGACCAAGGAGTCTGACATGTGTGCGAGTCAACGGGTGAGTAAACCCGTAAGGCGCAAGGAAGCTGATTGGCGGGATCCTCGCGGGTGCACCGCCGACCGACCTTGATCTTCTGAGAAGGGTTCGAGTGTGAGCATGCCTGTCGGGACCCGAAAGATGGTGAACTATGCCTGAGCGGGGTAAAGCCAGAGGAAACTCTGGTGGAAGCCCGCAGCGATACTGACGTGCAAATCGTTCGTCTGACTTGGGTATAGGGGCGAAAGACTAATCGAACCATCTAGTAGCTGGTTCCCTCCGAAGTTTCCCTCAGGATAGCTGGAGCTCGGACGCGAGTTCTATCGGGTAAAGCCAATGATTAGAGGCATTGGGGGCGCAACGCCTCGACCTATTCTCAAACTTTAAATAGGTAGGACGTGTCGGCTGCTTTGTTGAGCCGTCACACGGAATCGAGAGCTCCAAGTGGGCCATTTTTGGTAAGCAGAACTGGCGATGCGGGATGAACCGGAAGCCGGGTTACGGTGCCCAACTGCGCGCTAACCTAGAACCCACAAAGGGTGTTGGTCGATTAAGACAGCAGGACGGTGGTCATGGAAGTCGAAATCCGCTAAGGAGTGTGTAACAACTCACCTGCCGAATCAACTAGCCCCGAAAATGGATGGCGCTTAAGCGCGACCTATACCCGGCCGTCGGGGCAAGAGCCAGGCCTCGATGAGTAGGAGGGCGCGGCGGTCGCTGCAAAACCTAGGGCGCGAGGCGCGGAGCGGCCGTCGGTGCAGATCTTGGTGGTAGTAGCAAATATTCAAATGAGAACTTTGAAGGCCGAAGAGGGGAAAGGTTCCATGTGAACGGCACTTGCACATGGGTTAGTCGATCCTAAGAGTCGGGGGAAACCCGTCTGATAGCGCTTAAGCGAACTTCGAAAGGGGATCCGGTTAAAATTCCGGAACCGGGACGTGGCGGTTGACGGCAACGTTAGGGAGTCCGGAGACGTCGGCGGGGGCCTCGGGAAGAGTTATCTTTTCTGTTTAACAGCCTGCCCACCCTGGAAACGGCTCAGCCGGAGGTAGGGTCCAGCGGCTGGAAGAGCACCGCACGTCGCGTGGTGTCCGGTGCGCCCCCGGGCGCCCTTGAAAATCCGGAGGACCGAGTGCCGCTCACGCCCGGTCGTACTCATAACCGCATCAGGTCTCCAAGGTGAACAGCCTCTGGTCGATGGAACAATGTAGGCAAGGGAAGTCGGCAAAATGGATCCGTAACTTCGGGAAAAGGATTGGCTCTGAGGGCTGGGCTCGGGGGTCCCAGTTCCGAACCCGTCGGCTGTCAGCGGACTGCTCGAGCTGCTTCCGCGGCGAGAGCGGGTCGCCGGCTGCCGGCCGGGGGACGACTGGGAACGGCTCTCTCGGGAGCTTTCCCCGGGCGTCGAACAGTCAGCTCAGAACTGGTACGGACAAGGGGAATCCGACTGTTTAATTAAAACAAAGCATTGCGATGGTCCCTGCGGATGCTAACGCAATGTGATTTCTGCCCAGTGCTCTGAATGTCAAAGTGAAGAAATTCAACCAAGCGCGGGTAAACGGCGGGAGTAACTATGACTCTCTTAAGGTAGCCAAATGCCTCGTCATCTAATTAGTGACGCGCATGAATGGATTAACGAGATTCCCACTGTCCCTGTCTACTATCCAGCGAAACCACAGCCAAGGGAACGGGCTTGGCAGAATCAGCGGGGAAAGAAGACCCTGTTGAGCTTGACTCTAGTCCGACTTTGTGAAATGACTTGAGAGGTGTAGGATAAGTGGGAGCTTCGGCGCAAGTGAAATACCACTACTTTTAACGTTATTTTACTTACTCCGTGAATCGGAGGCCGGGGTACAACCCCTGTTTTTGGTCCCAAGGCTCGCTTCGGCGGGTCGATCCGGGCGGAGGACATTGTCAGGTGGGGAGTTTGGCTGGGGCGGCACATCTGTTAAAAGATAACGCAGGTGTCCTAAGATGAGCTCAACGAGAACAGAAATCTCGTGTGGAACAAAAGGGTAAAAGCTCGTTTGATTCTGATTTTCAGTACGAATACGAACCGTGAAAGCGTGGCCTATCGATCCTTTAGACTTCGGAATTTGAAGCTAGAGGTGTCAGAAAAGTTACCACAGGGATAACTGGCTTGTGGCAGCCAAGCGTTCATAGCGACGTTGCTTTTTGATCCTTCGATGTCGGCTCTTCCTATCATTGTGAAGCAGAATTCACCAAGTGTTGGATTGTTCACCCACCAATAGGGAACGTGAGCTGGGTTTAGACCGTCGTGAGACAGGTTAGTTTTACCCTACTGATGCCCGCGTCGCGATAGTAATTCAACCTAGTACGAGAGGAACCGTTGATTCGCACAATTGGTCATCGCGCTTGGTTGAAAAGCCAGTGGCGCGAAGCTACCGTGCGCTGGATTATGACTGAACGCCTCTAAGTCAGAATCCGGGCTAGAAGCGACGCATGCGCCCGCCGCCCGATTGCCGACCCTCAGTAGGAGCTTAGGCTCCAAAGGCACGTGTCGTTGGCTAAGTCCGTTCGGCGGAACGGTCGTTCGGACCGCCTTGAATTATAATTACCACCGAGCGGCGGGTAGAATCCTTTGCAGACGACTTAAATACGCGACGGGGTATTGTAAGTGGCAGAGTGGCCTTGCTGCCACGATCCACTGAGATTCAGCCCTTTGTCGCTAAGATTCGA +>gi|20197903:2706-4513 Arabidopsis thaliana chromosome 2 BAC F23H14 genomic sequence, complete sequence +TACCTGGTTGATCCTGCCAGTAGTCATATGCTTGTCTCAAAGATTAAGCCATGCATGTGTAAGTATGAACGAATTCAGACTGTGAAACTGCGAATGGCTCATTAAATCAGTTATAGTTTGTTTGATGGTAACTACTACTCGGATAACCGTAGTAATTCTAGAGCTAATACGTGCAACAAACCCCGACTTATGGAAGGGACGCATTTATTAGATAAAAGGTCGACGCGGGCTCTGCCCGTTGCTCTGATGATTCATGATAACTCGACGGATCGCATGGCCTCTGTGCTGGCGACGCATCATTCAAATTTCTGCCCTATCAACTTTCGATGGTAGGATAGTGGCCTACCATGGTGGTAACGGGTGACGGAGAATTAGGGTTCGATTCCGGAGAGGGAGCCTGAGAAACGGCTACCACATCCAAGGAAGGCAGCAGGCGCGCAAATTACCCAATCCTGACACGGGGAGGTAGTGACAATAAATAACAATACTGGGCTCTTTCGAGTCTGGTAATTGGAATGAGTACAATCTAAATCCCTTAACGAGGATCCATTGGAGGGCAAGTCTGGTGCCAGCAGCCGCGGTAATTCCAGCTCCAATAGCGTATATTTAAGTTGTTGCAGTTAAAAAGCTCGTAGTTGAACCTTGGGATGGGTCGGCCGGTCCGCCTTTGGTGTGCATTGGTCGGCTTGTCCCTTCGGTCGGCGATACGCTCCTGGTCTTAATTGGCCGGGTCGTGCCTCCGGCGCTGTTACTTTGAAGAAATTAGAGTGCTCAAAGCAAGCCTACGCTCTGGATACATTAGCATGGGATAACATCATAGGATTTCGATCCTATTGTGTTGGCCTTCGGGATCGGAGTAATGATTAACAGGGACAGTCGGGGGCATTCGTATTTCATAGTCAGAGGTGAAATTCTTGGATTTATGAAAGACGAACAACTGCGAAAGCATTTGCCAAGGATGTTTTCATTAATCAAGAACGAAAGTTGGGGGCTCGAAGACGATCAGATACCGTCCTAGTCTCAACCATAAACGATGCCGACCAGGGATCAGCGGATGTTGCTTATAGGACTCCGCTGGCACCTTATGAGAAATCAAAGTTTTTGGGTTCCGGGGGGAGTATGGTCGCAAGGCTGAAACTTAAAGGAATTGACGGAAGGGCACCACCAGGAGTGGAGCCTGCGGCTTAATTTGACTCAACACGGGGAAACTTACCAGGTCCAGACATAGTAAGGATTGACAGACTGAGAGCTCTTTCTTGATTCTATGGGTGGTGGTGCATGGCCGTTCTTAGTTGGTGGAGCGATTTGTCTGGTTAATTCCGTTAATGAACGAGACCTCAGCCTGCTAACTAGCTACGTGGAGGCATCCCTTCACGGCCGGCTTCTTAGAGGGACTATGGCCGTTTAGGCCAAGGAAGTTTGAGGCAATAACAGGTCTGTGATGCCCTTAGATGTTCTGGGCCGCACGCGCGCTACACTGATGTATTCAACGAGTTCACACCTTGGCCGACAGGCCCGGGTAATCTTTGAAATTTCATCGTGATGGGGATAGATCATTGCAATTGTTGGTCTTCAACGAGGAATTCCTAGTAAGCGCGAGTCATCAGCTCGCGTTGACTACGTCCCTGCCCTTTGTACACACCGCCCGTCGCTCCTACCGATTGAATGATCCGGTGAAGTGTTCGGATCGCGGCGACGTGGGTGGTTCGCCGCCCGCGACGTCGCGAGAAGTCCACTAAACCTTATCATTTAGAGGAAGGAGAAGTCGTAACAAGGTTTCCGTAGGTGAACCTGCGGAAGGATCATTG +>Arabidopsis thaliana 1 +GGATGCGATCATACCAGCACTAATGCACCGGATCCCATCAGAACTCCGCAGTTAAGCGTGCTTGGGCGAGAGTAGTACTAGGATGGGTGACCTCCTGGGAAGTCCTCGTGTTGCATCCCTC +>gi|186498419|ref|NR_022453.1| Arabidopsis thaliana (AT2G01020) rRNA +AAAACGACTCTCGGCAACGGATATCTCGGCTCTCGCATCGATGAAGAACGTAGCGAAATGCGATACTTGGTGTGAATTGCAGAATCCCGTGAACCATCGAGTCTTTGAACGCAAGTTGCGCCCCAAGCCTTCTGGCCGAGGGCACGTCTGCCTGGGTGTCACAA \ No newline at end of file diff -r c1f1b552c1b8 -r a1ce42d5258d predict/read_file.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/read_file.py Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,21 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- + +import sys + + + +def read_t_file(in_file): + f = open(in_file); + result = []; + for aline in f.readlines(): + temp = []; + tline = aline.strip(); + tl = tline.split('\t'); + for i in range(0, len(tl)): + temp.append(tl[i].strip()); + result.append(temp); + f.close(); + return result; + + diff -r c1f1b552c1b8 -r a1ce42d5258d predict/read_file.pyc Binary file predict/read_file.pyc has changed diff -r c1f1b552c1b8 -r a1ce42d5258d predict/rtts_plot.py --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/rtts_plot.py Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,57 @@ +#!/usr/bin/env python +#Make a plot of reactivity distribution + +import sys +import numpy as np +import matplotlib +from pylab import * +import math + +#Convert the reactivities (Make NA to 0) +def convert_react(a): + r = [] + for i in range(len(a)): + if a[i]!='NA': + r.append(float(a[i])) + else: + r.append(float(0)) + return r + + +#Make a plot of the distribution +def make_plot(ar,id_s,path): + N = len(ar) + a = convert_react(ar) + w = 1 + ind = np.arange(N) + + fig = figure() + fig, ax = subplots() + ax.bar(ind+w, a, width = w, color = 'r',edgecolor = 'r') + ax.set_ylabel('Structural Reactivity') + ax.set_xlabel('Nucleotide Index') + + + mag = int(math.log(N,10))-1 + tail = 10**mag + + intervel = int(math.ceil(float(N)/tail/5)) + print(N) + print(intervel) + tl = [] + k = 0 + upmax = int(math.ceil(float(N)/intervel/tail)*intervel*tail)+1 + ax.set_xticks(np.arange(0,upmax,intervel*tail)) + print(np.arange(0,upmax,intervel*tail)) + ax.set_xticklabels(np.arange(0,upmax,intervel*tail)) + + ax.set_title(id_s+" reactivity distribution") + savefig(path+id_s+'.tif') + + + + + + + + diff -r c1f1b552c1b8 -r a1ce42d5258d predict/rtts_plot.pyc Binary file predict/rtts_plot.pyc has changed diff -r c1f1b552c1b8 -r a1ce42d5258d predict/test_reactivity.txt --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/test_reactivity.txt Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,2 @@ +AT3G05880.1 +0.943887685769 0.421815158787 NA 1.01455360981 NA NA NA NA 0.503726666615 NA 0.562759466181 0.53286496306 NA 0.452307806554 NA NA NA NA 0.234006609126 NA 0.356521303582 0.3345952334 NA 0.938455477986 0.961629159648 0.58445845106 0.277563382428 NA NA NA 0.381285618597 0.510385809404 0.263300197836 0.351983737127 NA 0.478451311944 NA 0.0 NA NA 0.249061701962 NA 0.602014314955 0.768409570219 0.479108914417 0.609654847688 0.395147907741 NA NA 0.316409963987 NA NA 1.01642560569 0.178529288881 1.1258499175 NA 0.102264245055 NA 0.588862283199 0.675885983569 NA NA NA 0.0 NA NA NA NA 0.8152009763 NA 0.730574123452 NA NA 0.196012732449 NA NA 0.748188202713 NA 0.0 NA 0.925269643553 0.0 0.506395998703 NA 0.511028818599 0.354285255052 NA 1.01563235674 NA NA NA 0.602118316823 0.486534824365 NA 0.266635693932 0.176995791343 0.887089878761 0.654802870139 NA 0.24940376078 NA NA NA NA NA 0.835049477972 NA NA NA 0.230188979227 NA 0.145932219541 0.510982455489 NA 0.70545494854 NA NA NA NA NA NA NA NA 0.0 NA NA NA NA NA NA NA 0.0607994838688 NA NA NA NA NA NA NA 0.0 NA 0.510982455489 NA NA NA NA NA NA NA NA NA NA NA NA 0.805809423851 0.214474701586 NA 0.320112197187 NA 0.886851602907 0.0 NA NA NA NA NA NA 0.173824155265 NA 0.499351609605 NA NA 0.119452482914 0.0 NA NA NA NA 0.985352919102 NA 0.0 0.0 NA 0.925509063242 NA 0.54084940725 0.0 NA 0.622064968928 0.285526636999 0.373974554632 NA NA NA 0.0 NA NA NA 0.0 0.369187155673 NA 0.644843692277 0.0 0.0 0.0 0.0 0.155248951804 0.0 NA NA 0.0 NA NA NA 0.0 0.0 0.0464264694222 0.0 NA 0.0 NA 0.250790026642 NA 0.11120052998 0.0299680537584 NA 0.0723351276735 0.0 NA 0.069968383925 NA 0.394969636508 0.0 NA NA NA 0.270970925021 0.0436999866019 0.0 0.172881011784 NA 1.24794080936 NA NA NA NA 0.0 0.0 NA NA 0.241516034212 NA NA NA NA NA 0.19903265234 NA 0.289893769912 0.835049477972 NA 0.83678872047 NA 0.769301566905 NA NA NA NA NA NA 0.486001309495 1.00671172955 NA NA 0.392970275151 NA NA 0.369187155673 0.0330308799953 NA 0.0 NA NA NA NA 0.322006332632 NA NA NA NA NA 1.10146992643 NA NA NA 0.602394928175 0.052285391313 NA 0.0 0.474447727012 NA 0.258266798648 NA NA NA NA NA NA 0.173824155265 NA NA NA NA NA 0.435796833817 0.341824194398 0.0 NA NA 0.971161850563 0.0 NA NA NA 0.594354216766 0.0 NA NA 0.0 0.0666024493389 NA 0.36331086056 0.0 NA 0.838839492047 0.078362328999 0.54084940725 NA NA NA NA NA NA NA NA NA NA NA 0.0 0.0 NA NA NA NA NA 0.454308208169 NA 0.0 NA 0.0 0.653920441757 0.369187155673 NA NA NA NA NA NA NA NA NA NA 0.0 NA 0.0 NA 0.0 0.0 0.602118316823 0.0 NA 0.0 0.0 NA 0.0 NA 0.0 NA 0.0 NA NA NA NA NA NA NA NA NA NA 0.0 0.0 NA NA NA NA NA NA NA NA 0.0 0.0 NA 0.0 NA NA NA NA NA NA 0.0 0.0 0.0 0.0 0.0 NA 0.0 NA 0.0 NA NA NA NA NA NA NA NA 0.0 NA NA 0.0 0.0 0.465862322301 0.0 NA 0.0 0.0 0.0 NA NA NA NA 0.0 0.0 0.0 NA NA NA NA NA NA NA NA 0.0 0.0 NA NA NA NA NA NA NA 0.0 NA 0.0 0.0 0.0 0.0 NA NA 0.0 0.0 0.0 0.0 0.0 0.0 0.0 NA NA 0.0 0.0 0.0 0.0 0.0 NA diff -r c1f1b552c1b8 -r a1ce42d5258d predict/test_reference.fa --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/test_reference.fa Tue Nov 18 15:54:31 2014 -0500 @@ -0,0 +1,8 @@ +>AT3G05880.1 | Symbols: RCI2A | Low temperature and salt responsive protein family | chr3:1755497-1756540 REVERSE LENGTH=495 +AAGCTTTTATAATATTTTCTCAGAAACTTTCAAAGAGCTTAGAAAAATGAGTACAGCTACTTTCGTTGATATTATTATCG +CCATCCTCTTGCCTCCACTCGGTGTCTTTCTCAGATTTGGTTGCGGGGTTGAGTTTTGGATATGTTTGGTTTTGACGCTA +CTTGGGTATATTCCTGGGATCATATACGCCATTTATGTCCTCACCAAATGATTTACCATCTATCATCATCTCCTTGAACA +GCTGTTCCGTCGTGTTCTCCTATCTTTGTGACTGATTCAGCGTTTCTTTTTCTTTCATCAGAGTTTTTATGTTTCAAGTA +ATTTAATTAATCATCACTGTTGTGTTTGCATTGTTATATAAATGTTGTGTTGATATAAAAGAAGAGAGCGTTGGTTTGTA +CTTTGTGTGAAGATTTTTTAAAAATATAGTTGGTTTATTACAATAAATTGGAAATTGTGTTGCCTTGGTGGATCACAGGA +CCACCATTAACCATT