Mercurial > repos > tyty > structurefold
changeset 27:564795252d1a draft
Uploaded
author | tyty |
---|---|
date | Mon, 20 Oct 2014 14:42:09 -0400 |
parents | 8bf6c855353b |
children | cfb6e6e68917 |
files | predict/.DS_Store predict/._.DS_Store predict/._tool_dependencies.xml predict/parse_dis_pac.py predict/parse_dis_pac.pyc predict/predict_RNAs.py predict/predict_RNAs.xml predict/predict_RNAs.xml~ predict/rRNA.txt predict/read_file.py predict/read_file.pyc predict/rtts_plot.py predict/rtts_plot.pyc predict/tool_dependencies.xml predict/tool_dependencies.xml~ reactivity_cal/._.DS_Store reactivity_cal/._tool_dependencies.xml reactivity_cal/dis_f_N1Am_rrna.txt reactivity_cal/dis_f_N1Ap_rrna.txt reactivity_cal/parse_dis_react.py reactivity_cal/parse_dis_react.pyc reactivity_cal/rRNA.txt reactivity_cal/react_cal.py reactivity_cal/react_norm_function.py reactivity_cal/react_norm_function.pyc reactivity_cal/reactivity_calculation.xml reactivity_cal/reactivity_calculation.xml~ reactivity_cal/read_file.py reactivity_cal/tool_dependencies.xml |
diffstat | 29 files changed, 364 insertions(+), 435 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/parse_dis_pac.py Mon Oct 20 14:42:09 2014 -0400 @@ -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 + + + + + + + + + + + + + + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/predict_RNAs.py Mon Oct 20 14:42:09 2014 -0400 @@ -0,0 +1,93 @@ +#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 * + + +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 + +ospath = os.path.realpath(sys.argv[0]) +ost = ospath.split('/') +syspath = "" +for i in range(len(ost)-1): + syspath = syspath+ost[i].strip() + syspath = syspath+'/' + +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)>10: #setup a limit of the number of sequence to be predicted + print("Number of sequences exceeds limitation!") + sys.exit(0) + + +#predict RNA structures +os.system("mkdir "+syspath+"output_f") +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"+" "+syspath+"output_f/"+id_s+".ct") + if flag == 1: + if id_s in react: + f = file(syspath+"constraint.txt",'w') + make_plot(react[id_s],id_s,(syspath+"output_f/")) #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"+" "+syspath+"output_f/"+id_s+".ct") + else: + print(id_s+" not in the data of react!") + os.system("draw "+syspath+"output_f/"+id_s+".ct "+syspath+"output_f/"+id_s+".ps") + else: + print(id_s+" not in the data of sequences!") + +#Remove the unnecessary files +os.system("tar -zcvPf "+output_file+" "+syspath+"output_f/"+"*.* 2>"+syspath+"log.txt") +os.system("rm -f "+syspath+"temp.txt") +os.system("rm -r "+syspath+"output_f") +if flag == 1: + os.system("rm -f "+syspath+"constraint.txt") + # h.close() + + + + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/predict_RNAs.xml Mon Oct 20 14:42:09 2014 -0400 @@ -0,0 +1,59 @@ +<tool id="predict_pipeline" name="RNA structure prediction" version="1.0"> + <description></description> + <command interpreter="python">predict_RNAs.py $rna_list $reference_file $reactivity_file $output </command> + <requirements> + <requirement type="package" version="1.61">biopython</requirement> + <requirement type="package" version="1.7">numpy</requirement> + <requirement type="package" version="1.2">matplotlib</requirement> + </requirements> + <inputs> + <param name="rna_list" type="data" format="txt" label="List of RNA ids to predict"/> + <param name="reference_file" type="data" format="fasta" label="Reference genome/transcriptome"/> + <param name="reactivity_file" type="data" optional = "true" label="Reactivity"/> + + </inputs> + <outputs> + <data name="output" format=".tgz"/> + </outputs> + <tests> + <test> + <param name="rna_list" value="id_list_test.txt" /> + <param name="reference_file" value="cdna.txt" /> + <param name="reactivity_file" value="mRNA_react_test2.txt" /> + <output name="output" file="structures.out" /> + </test> + </tests> + <help> + + +**TIPS**: + +----- + +**Input**: + +* 1. A file with transcript Ids (Max num. 20), (each ID one line) +* 2. Reference file (fasta) used to map the reads +* [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! + + + + </help> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/predict_RNAs.xml~ Mon Oct 20 14:42:09 2014 -0400 @@ -0,0 +1,63 @@ +<tool id="predict_pipeline" name="RNA structure prediction" version="1.0"> + <description></description> + <command interpreter="python">predict_RNAs.py $rna_list $reference_file $reactivity_file $output </command> + <requirements> + <requirement type="package" version="1.61">biopython</requirement> + <requirement type="package" version="1.7">numpy</requirement> + </requirements> + <inputs> + <param name="rna_list" type="data" format="txt" label="List of RNA ids to predict"/> + <param name="reference_file" type="data" format="fasta" label="Reference genome/transcriptome"/> + <param name="reactivity_file" type="data" optional = "true" label="Reactivity"/> +<!--- + <conditional name="reactivity"> + <param name="choose" type="select" label="Reactivity files exists?"> + <option value="N">No</option> + <option value="Y">Yes</option> + </param> + <when value="Y"> + <param name="reactivity_file" type="data" optional = "true" label="Reactivity"/> + </when> + <when value="N"/> + </conditional> + +--> + </inputs> + <outputs> + <data name="output" format=".tgz"/> + </outputs> + + <help> + + +**TIPS**: + +----- + +**Input**: + +* 1. A file with transcript Ids (Max num. 20), (each ID one line) +* 2. Reference file (fasta) used to map the reads +* [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! + + + + </help> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/rRNA.txt Mon Oct 20 14:42:09 2014 -0400 @@ -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
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/read_file.py Mon Oct 20 14:42:09 2014 -0400 @@ -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; + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/rtts_plot.py Mon Oct 20 14:42:09 2014 -0400 @@ -0,0 +1,56 @@ +#!/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('DMS 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 + ax.set_xticks(np.arange(0,N,intervel*tail)) + print(np.arange(0,N,intervel*tail)) + ax.set_xticklabels(np.arange(0,N,intervel*tail)) + + ax.set_title(id_s+" reactivity distribution") + savefig(path+id_s+'.tif') + + + + + + + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/tool_dependencies.xml Mon Oct 20 14:42:09 2014 -0400 @@ -0,0 +1,12 @@ +<?xml version="1.0"?> +<tool_dependency> + <package name="biopython" version="1.61"> + <repository changeset_revision="ae9dda584395" name="package_biopython_1_61" owner="biopython" prior_installation_required="True" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> + <package name="numpy" version="1.7"> + <repository changeset_revision="ef12a3a11d5b" name="package_numpy_1_7" owner="iuc" prior_installation_required="False" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> + <package name="matplotlib" version="1.2"> + <repository changeset_revision="fe60617380df" name="package_matplotlib_1_2" owner="iuc" prior_installation_required="False" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> +</tool_dependency>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/predict/tool_dependencies.xml~ Mon Oct 20 14:42:09 2014 -0400 @@ -0,0 +1,9 @@ +<?xml version="1.0"?> +<tool_dependency> + <package name="biopython" version="1.61"> + <repository changeset_revision="ae9dda584395" name="package_biopython_1_61" owner="biopython" prior_installation_required="True" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> + <package name="numpy" version="1.7"> + <repository changeset_revision="ef12a3a11d5b" name="package_numpy_1_7" owner="iuc" prior_installation_required="False" toolshed="http://toolshed.g2.bx.psu.edu" /> + </package> +</tool_dependency>
--- a/reactivity_cal/dis_f_N1Am_rrna.txt Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,12 +0,0 @@ -gi|186498419|ref|NR_022453.1| -146241 38142 180120 134243 5639 6848 2492 1596 695 104 1741 160 1505 3009 210 1349 2366 197 353 97 3173 453 4575 656 218 3344 196 19655 540 360 303 351 1377 300 2479 445 3882 2244 293 272 3155 540 218 1849 1902 292 1037 15050 641 989 470 770 949 177 907 927 748 2819 796 490 117 237 272 723 994 173 162 157 86 147 65 296 86 342 115 1694 380 83 205 159 332 357 255 1017 697 80 599 217 474 673 246 170 327 468 47 818 403 25 100 57 84 527 158 349 409 220 94 111 177 27 207 64 770 309 108 92 47 63 17 6 25 10 33 4 117 35 64 27 1 69 42 43 163 12 9 133 81 44 213 125 136 106 26 1349 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -coverage:3826.28048781 -25s -881535 25444 3717 6666 4105 1066 5312 343 7553 1085 1543 5253 1667 4505 459 1269 413 1261 730 607 10420 1646 3144 15184 1253 844 238 933 1794 175 404 2754 1743 7660 4387 6957 6100 2702 2614 1344 34079 3185 11237 6583 14826 17602 9766 3553 2416 1976 1029 924 1317 493 2836 2337 7838 5981 4087 7747 4284 3160 1343 5529 7297 2897 1831 9203 24331 4407 27066 6161 1895 2462 9713 1400 500 535 2222 2026 2424 6289 6223 9688 4505 5981 11264 1102 514 2659 945 2177 4547 2493 3746 1433 2051 6678 3942 2867 3626 2142 2436 9252 5393 2318 3421 1770 3056 5925 598 13029 3780 4258 22078 9323 25339 10247 42891 7507 23054 20111 3098 1782 418 28408 873 3285 15629 4864 8369 23169 1872 5569 7312 3476 2407 9044 29647 4041 17941 5740 24376 140713 22800 9594 21798 14222 23929 13867 3985 8217 5057 5324 16195 13884 10203 186562 14369 2116 967 15121 3910 2528 19370 3819 4080 134820 2777 1441 13904 1835 779 318 10123 5901 1159 989 279 5817 4101 2100 5160 21152 11194 3346 5936 5458 1245 1072 646 3531 3013 7250 6407 10119 15469 2266 578 462 3143 507 1729 2757 4586 110 23 20 0 2 187 4 1 0 1 11 2431 788 424 226 1770 949 1003 12533 2294 1752 615 629 549 299 517 518 329 3892 2430 599 3623 558 2222 2591 751 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315 428 739 473 709 233 264 97 119 400 271 498 489 170 65 509 505 8 145 979 125 206 128 232 64 1530 91 130 839 91 100 227 85 89 219 39 27 100 300 344 1329 1666 1800 141 135 48 47 26 67 752 1616 608 361 657 520 484 1332 704 1705 160 151 61 164 92 156 153 118 113 45 22 1134 18 46 92 47 29 60 23 4 179 32 936 133 2 191 370 51 19 51 46 70 226 47 251 123 36 308 45 37 328 11 19 0 25 29 133 189 171 2865 183 53 84 43 2 17 13 35 3 101 46 288 151 21 402 259 24 100 98 210 2 9 19 2 26 1 23 56 52 192 58 28 41 4 0 11 74 235 191 15 19 62 35 4 0 14 1 45 56 225 10 156 236 13 4 13 7 160 10 200 74 76 3377 294 2508 3920 701635 17382 4008 16108 3395 387 274 1543 742 163 2534 764 204 1105 673 467 1137 628 318 286 5461 203 12872 442 805 613 182 473 1075 172 500 492 403 4364 532 7276 4864 240 535 202 498 310 1165 2788 1473 6240 2749 1484 6599 311 1998 1414 2399 1160 2224 851 3635 514 156 960 757 3193 1210 519 376 693 572 0 0 0 0 0 2 0 0 3 1 237 5 712 406 367 54 215 2451 2120 13909 1135 1526 485 377 795 935 100 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194 503 6541 1403 6636 860 1169 3860 938 3076 1174 608 709 3117 1851 270 687 708 1813 5048 2130 1318 652 476 1684 6117 1627 2989 766 1736 7241 3872 2282 1703 851 1320 1963 1841 575 147 16 0 0 0 0 0 0 1 15 99 89643 5883 1671 2969 1064 710 7147 505 215 7254 1012 1856 3127 2333 1853 1271 959 5795 5912 952 2700 6021 1959 4209 2842 2506 13855 3762 3321 1732 31128 2827 1291 1431 3650 997 170 8627 951 5781 495 314 3554 102 630 643 386 942 897 1418 581 3460 1630 2323 2373 1278 904 627 169 1157 127 1038 1646 715 4994 544 8701 535 1083 2287 626 3386 3746 420 1112 3243 288 1256 309 190 920 1437 194 6532 1729 674 643 265 177 250 1130 155 5891 3418 2612 1696 1619 1869 985 706 1629 2682 1991 2234 771 4649 440 1587 1559 719 437 490 1133 88 739 1767 538 991 196 913 812 198 5311 1290 1080 395 1879 324 662 484 395 1410 1587 526 1268 219 1381 625 2733 935 853 4610 199 492 452 132 504 377 4520 1193 4787 3028 197 827 929 431 352 423 420 844 445 476 3419 335 867 1654 2721 652 1305 857 618 388 682 16131 8438 2014 3340 715 940 324 1054 1353 1387 584 761 237 511 1895 204 1340 8353 4498 2056 5609 8653 908 12519 883 4480 39771 941 4475 432 264 2588 669 507 276 370 512 553 5417 965 12947 1546 1042 394 4780 5063 4441 12265 1156 3809 4986 2651 1057 2359 415 630 1161 618 1769 3594 3054 798 1153 1204 1411 515 1372 2945 5705 4063 7862 53609 4064 21774 24325 1750 3532 486 4491 754 532 535 949 1874 684 2732 2257 7631 13668 443 9914 9458 2248 1342 949 949 485 372 1779 2176 5474 5065 7304 2403 10023 3567 22185 2920 87159 31 0 0 1 0 2 48 4555 1854 1127 2614 585 17990 768 299 9449 1107 1953 7179 12336 3232 2854 576 1670 965 1755 985 31331 1199 1026 7084 395 801 532 3625 4148 1864 8345 4157 1994 6956 22918 6714 4236 10599 1538 5603 785 679 3979 822 785 6173 944 2095 4165 2027 3125 7796 1618 718 2343 484 1183 1296 1567 20771 616 728 980 820 208 546 2744 272 923 499 2348 3783 11308 6232 1271 1847 24 2 0 0 0 0 0 0 0 0 0 0 89 351 300 288 535 110 626 156 786 1092 50 298 121 2875 159 782 3165 173 1966 1142 1261 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16097 14430 19838 3836 1915 20476 5640 2057 19218 17512 9583 19429 14930 4053 2368 36692 28478 17960 12763 3211 15723 17455 4262 15836 5574 17075 2971 1549 11262 1816 2481 3031 1711 2245 3302 2239 5581 5436 898 3189 6402 7369 19431 10181 13982 19518 19378 6052 3397 7060 48792 49466 166394 16294 11481 7588 2631 9634 818 7222 8071 5098 50033 3363 2907 3316 2831 28201 23752 15257 6539 31273 20417 8330 18882 2784 7312 11264 5719 37305 11156 34369 28532 7521 2088 5106 136216 6760 3184 8826 4505 17420 89725 5786 9835 47563 42284 228449 23151 10905 9629 2291 852 539 21600 1595 1643 83308 3168 9230 1691 5252 3309 1515 5225 4626 1267 7645 10913 3289 11718 160149 96128 20051 4231 10627 21149 6156 9864 8341 10069 2123 20394 14350 9726 19497 27938 98863 14126 12365 11455 5934 8883 3699 2200 1856 2930 29028 20229 4265 13036 10997 123690 13292 23786 7293 26281 10459 4324 80443 74236 29597 4360 3106 7668 2936 50151 6032 8456 41215 30315 72582 22633 82098 56991 7444 11502 18815 3986 51306 4799 3007 3601 2699 32496 8227 8523 51338 3731 23833 383982 16734 54704 181869 15780 44891 8843 61934 8722 3511 9541 2014 2082 9791 12879 1256 1769 16492 23018 25711 3425 5757 7748 6637 8538 2421 1180 2306 3558 2511 6676 15736 2895 16995 12150 784 15694 19837 2235 2291 6787 14289 13577 33423 7455 104407 25193 11741 76444 149786 13133 19339 38730 9696 10093 11742 2843 2973 16682 8778 4261 3432 9341 2088 3519 5195 2142 3650 23502 21304 29334 11102 24475 3829 8448 25057 29207 4072 4295 15963 7557 13441 16457 6903 7517 18114 2888 15355 2912 9314 10223 7355 6996 23929 34758 32336 23582 18784 13062 4052 11500 5164 4390 4450 43219 15862 13078 12019 32352 11400 10789 7759 44295 10190 3755 43157 4945 3789 27000 728401 15353 25752 37886 6521 5833 10411 4997 13530 17532 19474 11376 13583 5615 59799 19137 5037 2415 10195 20867 7197 43957 40619 11990 3397 65413 14393 17403 45882 12444 17080 25725 6268 53375 26086 21210 13030 129383 28084 5386 30859 1007498 36810 9120 149119 20793 14276 9005 28255 24819 10532 6806 1929 2209 3994 923 4758 1557 5077 62586 3615 4418 25161 37477 29847 26458 4883 1416 16824 23999 7771 24194 18853 15112 7284 9706 25453 5458 1093 20049 5547 1700 13748 5212 7528 10561 2127 30562 9086 10290 22396 13044 7444 39588 38983 13299 10989 29106 3213 2719 7463 12171 1211 5657 907 946 25627 3807 2467 8638 3158 2323 1169 8655 20054 1144 2165 1022 473 515 318 9968 1982 1785 1586 645 932 1326 18572 6003 23624 24494 5382 4548 1073 2357 145 748 93 132 194 310 543 519 435 90 4330 484 165 904 623 1328 564 238 536 221 273 205 600 900 308 221 1905 591 606 861 459 142 100 18 42 102 37 51 143 25 28 49 15 80 85 30 219 395 310 209 208 2609 58 17 91 62 113 104 170 238 117 203 99 25 65 33 650 499 93 524 459 207 420 1906 39597 754 479 1113 1080 101 56 540 249 224 131 465 759 185 233 72 27 138 32 13 211 60 50 402 134 122 149 95 32 86 45 34 117 55 57 138 80 13 328 510 195 680 1400 373 2025 336 525 103 352 946 3106 48146 65443 4484 25973 1591 6249 333 394 949 267 1063 365 1543 2689 578 477 144 2523 847 129 3781 777 386 968 721 2034 314 9986 7600 6795 2312 2609 3265 3657 1206 1537 34719 81640 1937 1853 3224 4988 714 3826 2129 1135 1260 2243 2459 1314 1287 3252 1490 5798 1287 33839 828802 15071 6467 17694 11929 2470 5783 499 5132 4324 4576 4040 1232 2842 2115 1433 15255 2204 1353 4861 1205 444 2760 1524 838 8666 3804 902 55166 2046 981 760 1848 1086 590 13977 5962 3093 1474 4197 3879 1882 1310 1314 3970 1193 448 1349 1551 886 2579 855 2295 13815 6410 5875 1631 2855 2952 549 8320 6165 4995 9738 15798 9726 13766 3409 3604 1852 4391 4035 19978 1370 11897 15640 4216 4196 5271 98189 3141 6442 2689 1344 10728 1082 1077 9202 4433 4742 3403 2571 684 4671 4971 2838 4010 8424 12091 3648 2359 5308 6442 1811 1627 19424 12480 4202 2763 1678 1400 6800 7776 10122 9578 190337 91025 34402 23174 2379 8401 3013 1489 10760 1976 1679 3867 13143 2621 11394 3139 1164 4008 23586 6376 9367 8775 6496 5845 9468 6204 465 3811 43823 12209 3920 20046 8528 2284 1178 3011 1706 18792 25150 38254 9642 7318 9454 4337 5776 1202 7027 18078 11395 1937 29155 13898 14404 135641 161207 7066 4404 11155 8655 6772 18892 24799 128909 26431 30188 46143 3328 87384 25884 8823 8085 3989 4756 7137 3970 8207 14751 3275 1486 3042 5599 2671 4629 21374 10866 7013 34532 9214 2570 12047 5339 2723 5135 3375 1212 1891 2006 9614 2371 3466 30358 5952 3412 2603 3365 2028 5615 444 6723 21353 4983 25946 6977 8179 2315 24559 2797 6644 7684 13108 9082 26909 3560 15175 27961 3236 5753 15358 9662 43960 13939 28670 208831 16478 275147 37432 3074 4436 1782 536 352 1036 1415 2556 21366 5609 8805 32111 1025 830 1367 477 2793 3119 8611 10826 3384 28549 21014 6481 9057 11687 5277 9019 15543 10283 27900 7132 4644 16608 2018 7261 6962 979 1551 2580 1025 9650 6228 1202 1888 2288 2266 8281 11051 5152 776 6184 6588 1243 11157 2088 1143 1834 3611 10885 7167 16069 1712 2014 709 563 509 343 1480 626 1128 3365 329 5016 2783 345 220 1965 14235 4296 5956 2167 887 1004 456 74 810 994 254 825 255 394 125 31 151 35 868 519 2423 435 80 919 675 18 1111 56 52 59 14 411 133 337 198 19 27 240 9 53 543 15 33 6 10 23 46 36 22 205 72 34 175 166 274 120 228 251 173 562 24 821 202 140 46 30 2102 39 16 40 22 24 0 172 191 512 370 1253 727 423 874 10347 3877 3532 3094 1517 4942 848 334 965 910 546 1048 774 276 104 112 559 997 136 190 61 66 85 20 35 6 489 2961 58 128 29 98 51 3 13 389 51 11 5 12 9 0 68 45 88 29 110 14 72 44 1 3 3 1 0 4 2 1 101 11 0 4 0 59 10 275 38 7 29 272 47 20 0 17 13 8 10 0 122 799 32 17 25 3 10 35 2 149 21 81 19 5 0 31 167 22 4 114 64 12 24 0 44 61 38 37 19 61 19 164 673 51 6 203 88 44 8 0 6 2 4 0 7 12 0 2 5 16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -coverage:14437.7997788
--- a/reactivity_cal/parse_dis_react.py Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,51 +0,0 @@ -#!/usr/bin/env python -# -*- coding: utf-8 -*- -import sys - -def parse_dist(in_file): - result = [] - distribution = {} - name = [] - f = open(in_file) - flag = 0 - for aline in f.readlines(): - line = aline.strip() - dis = line.strip() - dist = dis.split('\t') - if len(dist) > 0: - if len(dist) == 1: - if dist[0].strip().find('coverage')==-1: - if flag == 0: - name.append(line) - flag = 1 - t_name = line - else: - distribution[t_name] = 'null' - name.append(line) - flag = 1 - t_name = line - else: - distri = [] - for i in range(0, len(dist)): - distri.append(dist[i].strip()) - distribution[t_name] = distri - flag = 0 - result.append(name) - result.append(distribution) - f.close() - return result - - - - - - - - - - - - - - -
--- a/reactivity_cal/rRNA.txt Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,8 +0,0 @@ ->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
--- a/reactivity_cal/react_cal.py Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,136 +0,0 @@ -#!/usr/bin/env python -# -*- coding: utf-8 -*- -import sys -from Bio import SeqIO -import math -from parse_dis_react import * -from react_norm_function import * -import os - - -dist_file1 = sys.argv[1] #plus library -dist_file2 = sys.argv[2] #minus library -seq_file = sys.argv[3] #Reference library(genome/cDNA) -nt_spec = sys.argv[4] #only show reactivity for AC or ATCG -flag_in = sys.argv[5] # perform 2-8% normalization (1) or not (0) -threshold = sys.argv[6] #Threshold to cap the reactivities -output_file = sys.argv[7] - - -distri_p = parse_dist(dist_file1) -distri_m = parse_dist(dist_file2) -threshold = float(threshold) - - -ospath = os.path.realpath(sys.argv[0]) -ost = ospath.split('/') -syspath = "" -for i in range(len(ost)-1): - syspath = syspath+ost[i].strip() - syspath = syspath+'/' - -h = file(syspath+"react.txt",'w') -flag_in = int(flag_in) - -seqs = SeqIO.parse(open(seq_file),'fasta'); -nt_s = set() -for i in range(len(nt_spec)): - nt_s.add(nt_spec[i]) - -flag = 0 -trans = [] -distri_p = distri_p[1] -distri_m = distri_m[1] - -#thres = int(threshold) - - -transcripts = {} -for seq in seqs: - n = seq.id - trans.append(n) - transcripts[n] = seq.seq.tostring() - - -#print(distri_p) - - -for i in range(0, len(trans)): - h.write(trans[i]) - h.write('\n') - for j in range(len(distri_p[trans[i]])): - distri_p[trans[i]][j] = math.log((int(distri_p[trans[i]][j])+1),math.e) - for j in range(len(distri_m[trans[i]])): - distri_m[trans[i]][j] = math.log((int(distri_m[trans[i]][j])+1),math.e) - s_p = sum(distri_p[trans[i]]) - s_m = sum(distri_m[trans[i]]) - length = len(distri_p[trans[i]]) - if s_p!= 0 and s_m!= 0: - r = [] - for j in range(0, len(distri_p[trans[i]])): - f_p = (float(distri_p[trans[i]][j]))/float(s_p)*length - f_m = (float(distri_m[trans[i]][j]))/float(s_m)*length - raw_react = f_p-f_m - r.append(max(0, raw_react)) - - if s_p!= 0 and s_m!= 0: - for k in range(1,(len(r)-1)): - if transcripts[trans[i]][k-1] in nt_s: - h.write(str(r[k])) - h.write('\t') - else: - h.write('NA') - h.write('\t') - k = k+1 - if transcripts[trans[i]][k-1] in nt_s: - h.write(str(r[k])) - h.write('\n') - else: - h.write('NA') - h.write('\n') - - -h.close() - -if flag_in: - react_norm((syspath+"react.txt"),output_file, threshold) -else: - h_o = file(output_file, 'w') - f_i = open(syspath+"react.txt") - for aline in f_i.readlines(): - h_o.write(aline.strip()) - h_o.write('\n') -os.system("rm -f "+syspath+"react.txt") - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
--- a/reactivity_cal/react_norm_function.py Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,82 +0,0 @@ -#!/usr/bin/env python -# -*- coding: utf-8 -*- -import sys -from Bio import SeqIO -import math -from parse_dis_react import * - -def cap(a,value): - if a>=value: - return value - else: - return a - -def react_norm(react_file, result_file, capped_value): - print("Normalizing.....") - react1 = parse_dist(react_file) - react = react1[1] - h = file(result_file, 'w') - - capped = int(capped_value) - - all_react = [] - - - for t in react: - if react[t]!='null': - for i in range(len(react[t])): - if react[t][i]!='NA': - all_react.append(float(react[t][i])) - - - all_react.sort(reverse = True) - - - eight = all_react[int(len(all_react)*0.02):int(len(all_react)*0.1)] - meight = sum(eight)/len(eight) - - for t in react: - h.write(t) - h.write('\n') - if react[t]!='null': - for i in range((len(react[t])-1)): - if react[t][i]!='NA': - h.write(str(cap((float(react[t][i])/meight),capped))) - else: - h.write('NA') - h.write('\t') - if react[t][i+1]!='NA': - h.write(str(cap((float(react[t][i+1])/meight),capped))) - else: - h.write('NA') - h.write('\n') - - h.close() - - - - - - - - - - - - - - - - - - - - - - - - - - - -
--- a/reactivity_cal/reactivity_calculation.xml Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,60 +0,0 @@ -<tool id="react_cal_pipeline" name="Reactivity calculation" version="1.0"> - <description></description> - <command interpreter="python">react_cal.py $dist_file1 $dist_file2 $seq_file $nt_spec $flag_in $threshold $output </command> - <requirements> - <requirement type="package" version="1.61">biopython</requirement> - <requirement type="package" version="1.7">numpy</requirement> - </requirements> - <inputs> - <param name="dist_file1" type="data" format="txt" label="RTSC file for (+) library"/> - <param name="dist_file2" type="data" format="txt" label="RTSC file for (-) library"/> - <param name="seq_file" type="data" format="fasta" label="Reference library"/> - <param name="nt_spec" type="select" label="Nucleotide specificity"> - <option value="AC">AC</option> - <option value="ATCG">AUCG</option> - </param> - <param name="flag_in" type="boolean" checked="true" truevalue = "1" falsevalue = "0" label="Normalization is performed if checked"/> - <param name="threshold" type="float" value = "7" optional = "true" label="Value to cap the reactivities"/> - </inputs> - <outputs> - <data name="output" format="txt"/> - </outputs> - <tests> - <test> - <param name="dist_file1" value="dis_f_N1Ap_rrna.txt" /> - <param name="dist_file2" value="dis_f_N1Am_rrna.txt" /> - <param name="seq_file" value="rRNA.txt" /> - <param name="nt_spec" value="AC" /> - <param name="flag_in" value="1" /> - <param name="threshold" value="7" /> - <output name="output" file="DMS_reactivities.out" /> - - </test> - </tests> - - <help> - - -**TIPS**: - ------ - -**Input**: - -* 1. RTSC files (Output of II) for (+) and (-) library -* 2. Reference file (fasta) used to map the reads -* 3. Nucleotide Specificity (Type of nucleotide to have reactivity, e.g. AC for DMS and ACTG for SHAPE) -* [Optional]: -* 1. A threshold to cap the structural reactivities. {Default: 7} -* 2. Flag that determines whether to perform 2%-8% normalization {Default: yes} - ------ - -**Output**: - -A text file with structural reactivity for each nucleotide (Reactivity file) - - - - </help> -</tool>
--- a/reactivity_cal/reactivity_calculation.xml~ Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,44 +0,0 @@ -<tool id="react_cal_pipeline" name="Reactivity calculation" version="1.0"> - <description></description> - <command interpreter="python">react_cal.py $dist_file1 $dist_file2 $seq_file $nt_spec $flag_in $threshold $output </command> - <requirements> - <requirement type="package" version="1.61">biopython</requirement> - </requirements> - <inputs> - <param name="dist_file1" type="data" format="txt" label="RTSC file for (+) library"/> - <param name="dist_file2" type="data" format="txt" label="RTSC file for (-) library"/> - <param name="seq_file" type="data" format="fasta" label="Reference library"/> - <param name="nt_spec" type="text" value = "AC" label="Nucleotide specificity"/> - <param name="flag_in" type="boolean" checked="true" truevalue = "1" falsevalue = "0" label="Normalization is performed if checked"/> - <param name="threshold" type="float" value = "7" label="Value to cap the reactivities"/> - </inputs> - <outputs> - <data name="output" format="txt"/> - </outputs> - - <help> - - -**TIPS**: - ------ - -**Input**: - -* 1. RTSC files (Output of II) for (+) and (-) library -* 2. Reference file (fasta) used to map the reads -* 3. Nucleotide Specificity (Type of nucleotide to have reactivity, e.g. AC for DMS and ACTG for SHAPE) -* [Optional]: -* 1. A threshold to cap the structural reactivities. {Default: 7} -* 2. Flag that determines whether to perform 2%-8% normalization {Default: yes} - ------ - -**Output**: - -A text file with structural reactivity for each nucleotide (Reactivity file) - - - - </help> -</tool>
--- a/reactivity_cal/read_file.py Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,21 +0,0 @@ -#!/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; - -
--- a/reactivity_cal/tool_dependencies.xml Mon Oct 20 14:41:56 2014 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,9 +0,0 @@ -<?xml version="1.0"?> -<tool_dependency> - <package name="biopython" version="1.61"> - <repository changeset_revision="ae9dda584395" name="package_biopython_1_61" owner="biopython" prior_installation_required="True" toolshed="http://toolshed.g2.bx.psu.edu" /> - </package> - <package name="numpy" version="1.7"> - <repository changeset_revision="ef12a3a11d5b" name="package_numpy_1_7" owner="iuc" prior_installation_required="False" toolshed="http://toolshed.g2.bx.psu.edu" /> - </package> -</tool_dependency>