# HG changeset patch
# User tyty
# Date 1413830620 14400
# Node ID 003096bd038cd56002be15a5878fcd1b72b1c3fc
# Parent cfb6e6e68917e12234e1643f877d1fd7fd6ee4cf
Deleted selected files
diff -r cfb6e6e68917 -r 003096bd038c Iterative_mapping/.DS_Store
Binary file Iterative_mapping/.DS_Store has changed
diff -r cfb6e6e68917 -r 003096bd038c get_reads/.DS_Store
Binary file get_reads/.DS_Store has changed
diff -r cfb6e6e68917 -r 003096bd038c predict/.DS_Store
Binary file predict/.DS_Store has changed
diff -r cfb6e6e68917 -r 003096bd038c predict/._.DS_Store
Binary file predict/._.DS_Store has changed
diff -r cfb6e6e68917 -r 003096bd038c predict/._tool_dependencies.xml
Binary file predict/._tool_dependencies.xml has changed
diff -r cfb6e6e68917 -r 003096bd038c predict/parse_dis_pac.py
--- a/predict/parse_dis_pac.py Mon Oct 20 14:42:42 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,43 +0,0 @@
-#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
-
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diff -r cfb6e6e68917 -r 003096bd038c predict/parse_dis_pac.pyc
Binary file predict/parse_dis_pac.pyc has changed
diff -r cfb6e6e68917 -r 003096bd038c predict/predict_RNAs.py
--- a/predict/predict_RNAs.py Mon Oct 20 14:42:42 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,93 +0,0 @@
-#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()
-
-
-
-
-
diff -r cfb6e6e68917 -r 003096bd038c predict/predict_RNAs.xml
--- a/predict/predict_RNAs.xml Mon Oct 20 14:42:42 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,59 +0,0 @@
-
-
- predict_RNAs.py $rna_list $reference_file $reactivity_file $output
-
- biopython
- numpy
- matplotlib
-
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-**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!
-
-
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-
-
diff -r cfb6e6e68917 -r 003096bd038c predict/predict_RNAs.xml~
--- a/predict/predict_RNAs.xml~ Mon Oct 20 14:42:42 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,63 +0,0 @@
-
-
- predict_RNAs.py $rna_list $reference_file $reactivity_file $output
-
- biopython
- numpy
-
-
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-
-
-**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!
-
-
-
-
-
diff -r cfb6e6e68917 -r 003096bd038c predict/rRNA.txt
--- a/predict/rRNA.txt Mon Oct 20 14:42:42 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
diff -r cfb6e6e68917 -r 003096bd038c predict/read_file.py
--- a/predict/read_file.py Mon Oct 20 14:42:42 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;
-
-
diff -r cfb6e6e68917 -r 003096bd038c predict/read_file.pyc
Binary file predict/read_file.pyc has changed
diff -r cfb6e6e68917 -r 003096bd038c predict/rtts_plot.py
--- a/predict/rtts_plot.py Mon Oct 20 14:42:42 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,56 +0,0 @@
-#!/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')
-
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diff -r cfb6e6e68917 -r 003096bd038c predict/rtts_plot.pyc
Binary file predict/rtts_plot.pyc has changed
diff -r cfb6e6e68917 -r 003096bd038c predict/tool_dependencies.xml
--- a/predict/tool_dependencies.xml Mon Oct 20 14:42:42 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,12 +0,0 @@
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diff -r cfb6e6e68917 -r 003096bd038c predict/tool_dependencies.xml~
--- a/predict/tool_dependencies.xml~ Mon Oct 20 14:42:42 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
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