# HG changeset patch
# User tyty
# Date 1410807163 14400
# Node ID a292aaf517356ea52541a328f277561ae31db91c
# Parent f4cc06e925309dc933b42c8c6ce2eb2c3af422c3
Uploaded
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/iterative_map.py
--- a/Iterative_mapping/iterative_map.py Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,103 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import sys
-import os
-from read_file import *
-from read_s_file import *
-
-type_input = sys.argv[1]
-seq_file = sys.argv[2]
-ref_file = sys.argv[3]
-shift = sys.argv[4]
-length = sys.argv[5]
-map_type = sys.argv[6]
-output_file = sys.argv[7]
-
-
-if map_type!="default":
- s = ""
- s = s+"-v "+sys.argv[8]
- s = s+" -5 "+sys.argv[9]
- s = s+" -3 "+sys.argv[10]
- s = s+" -k "+sys.argv[11]
- if sys.argv[12]:
- s = s+" -a"
- if int(sys.argv[13])>=1:
- s = s+" -m "+sys.argv[13]
- if sys.argv[14]:
- s = s+" --best --strata "
-
-else:
- s = "-v 3 -a --best --strata "
-
-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+'/'
-
-os.system("bowtie-build -f "+ref_file+" "+syspath+"ref > "+syspath+"log.txt")
-
-os.system("cp "+seq_file+" "+syspath+"seq0.fa")
-
-if type_input == "fasta":
- tp = 'fasta'
-if type_input == "fastq":
- tp = 'fastq'
-
-k = 0
-print(type_input)
-while(True):
- if type_input == "fasta":
- os.system("bowtie "+s+"-f "+syspath+"ref"+" "+syspath+"seq"+str(k)+".fa --quiet -S > "+syspath+"map"+str(k)+".sam")
- if type_input == "fastq":
- os.system("bowtie "+s+"-q "+syspath+"ref"+" "+syspath+"seq"+str(k)+".fa --quiet -S > "+syspath+"map"+str(k)+".sam")
- os.system("samtools view -Sb -F 0xfff "+syspath+"map"+str(k)+".sam > "+syspath+"mapped"+str(k)+".bam 2>"+syspath+"log.txt") #get mapped reads
- os.system("samtools view -Sb -f 0x4 "+syspath+"map"+str(k)+".sam > "+syspath+"umapped"+str(k)+".bam 2>"+syspath+"log.txt") #get unmapped reads
- os.system("samtools view -Sb -f 0x10 "+syspath+"map"+str(k)+".sam > "+syspath+"rmapped"+str(k)+".bam 2>"+syspath+"log.txt") #get reversed mapped reads
- os.system("samtools merge -f "+syspath+"unmapped"+str(k)+".bam "+syspath+"umapped"+str(k)+".bam "+syspath+"rmapped"+str(k)+".bam") #get reversed mapped reads
- os.system("samtools view -h -o "+syspath+"unmapped"+str(k)+".sam "+syspath+"unmapped"+str(k)+".bam") #get reversed mapped reads
- if k>0:
- os.system("samtools view -h -o "+syspath+"mapped"+str(k)+".sam "+syspath+"mapped"+str(k)+".bam") #get reversed mapped reads
- os.system("cut -f 1 "+syspath+"unmapped"+str(k)+".sam > "+syspath+"unmapped"+str(k)+".txt")
- os.system("cut -f 1 "+syspath+"mapped"+str(k)+".sam > "+syspath+"mapped"+str(k)+".txt")
- os.system("python "+syspath+"remove_map.py "+syspath+"unmapped"+str(k)+".txt "+syspath+"mapped"+str(k)+".txt "+syspath+"runmapped"+str(k)+".txt")
- os.system("rm "+syspath+"mapped"+str(k)+".sam")
- os.system("rm "+syspath+"mapped"+str(k)+".txt")
- os.system("rm "+syspath+"unmapped"+str(k)+".txt")
- else:
- os.system("cut -f 1 "+syspath+"unmapped"+str(k)+".sam > "+syspath+"runmapped"+str(k)+".txt")
-
- os.system("rm "+syspath+"unmapped"+str(k)+".bam")
- os.system("rm "+syspath+"umapped"+str(k)+".bam")
- os.system("rm "+syspath+"rmapped"+str(k)+".bam")
- os.system("python "+syspath+"seq_track.py "+syspath+"runmapped"+str(k)+".txt "+syspath+"seq"+str(k)+".fa "+syspath+"unmap_seq"+str(k)+".fa "+tp) #get unmapped sequence
- os.system("python "+syspath+"truncate.py "+syspath+"unmap_seq"+str(k)+".fa "+shift+" "+syspath+"seq"+str(k+1)+".fa "+length) #truncate unmapped sequence
- os.system("rm "+syspath+"seq"+str(k)+".fa") #Remove sequences being mapped
- os.system("rm "+syspath+"map"+str(k)+".sam") #Remove mapping file
- os.system("rm "+syspath+"unmap_seq"+str(k)+".fa") #Remove unmapped sequnce
- os.system("rm "+syspath+"runmapped"+str(k)+".txt")
- os.system("rm "+syspath+"unmapped"+str(k)+".sam")
-
- os.system("wc -l "+syspath+"seq"+str(k+1)+".fa > "+syspath+"count"+str(k+1)+".txt")
- c = read_sp_file(syspath+"count"+str(k+1)+".txt")
- if c[0][0] == '0': #If no reads is in the sequence file, stop
- os.system("rm "+syspath+"count"+str(k+1)+".txt")
- os.system("rm "+syspath+"seq"+str(k+1)+".fa")
- break
- os.system("rm "+syspath+"count"+str(k+1)+".txt")
- k = k+1
-
-ss = ""
-for i in range(0,k+1):
- ss = ss+" "+syspath+"mapped"+str(i)+".bam"
-
-
-os.system("samtools merge -f "+output_file+" "+ss)
-#print("samtools merge mapped_all.bam"+ss)
-os.system("rm "+syspath+"mapped*.bam")
-os.system("rm "+syspath+"ref*")
-
-
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/iterative_map.xml
--- a/Iterative_mapping/iterative_map.xml Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,80 +0,0 @@
-
-
-
- #if $mapping_file.type == "user"
- iterative_map.py $file_format.type $file_format.seq_file $reference_file $shift $length $mapping_file.type $output $mapping_file.param_v $mapping_file.param_five $mapping_file.param_three $mapping_file.param_k $mapping_file.param_a $mapping_file.param_m $mapping_file.param_best
- #else
- iterative_map.py $file_format.type $file_format.seq_file $reference_file $shift $length $mapping_file.type $output
- #end if
-
-
- biopython
- numpy
- samtools
- bowtie
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-**TIPS**:
-
------
-
-**Input**:
-
-* 1. Sequence file type (FASTA/FASTQ)
-* 2. Sequence file (fasta/fastq format) {Default: fastq file}
-* 3. Reference file (e.g. cDNA library [fasta])
-* 4. “Shift” (The length of the sequence that will be trimmed at the 3’end of the reads before each round of mapping)
-* 5. “Length” (The minimum length of the reads for mapping after trimming)
-* [Optional]
-* 1. Bowtie mapping flags (options) [Default: -v 0 -a --best --strata] (-v flag indicates the number of allowed mismatches. use -5/-3 flag to trim nucleotides from 5'/3' end of the reads)
-
------
-
-**Output**:
-
-A bam file with all of the reads that are mapped
-
-
-
-
-
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/map_ex.py
--- a/Iterative_mapping/map_ex.py Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,31 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import sys
-from read_file import *
-from Bio import SeqIO
-
-map_file = sys.argv[1]
-result_file = sys.argv[2]
-
-
-#reads = read_t_file(read_file);
-
-f = open(map_file);
-h = file(result_file, 'w')
-
-for aline in f.readlines():
- tline = aline.strip();
- tl = tline.split('\t');
- if len(tl)>4:
- if int(tl[1].strip())== 0:
- h.write(tline)
- h.write('\n')
-
-
-f.close();
-h.close()
-
-
-
-
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/read_file.py
--- a/Iterative_mapping/read_file.py Mon Sep 15 14:52:20 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 f4cc06e92530 -r a292aaf51735 Iterative_mapping/read_s_file.py
--- a/Iterative_mapping/read_s_file.py Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,22 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import sys
-
-
-
-def read_sp_file(in_file):
- f = open(in_file);
- result = [];
- for aline in f.readlines():
- temp = [];
- tline = aline.strip();
- tl = tline.split(' ');
- for i in range(0, len(tl)):
- if len(tl[i].strip())>0:
- temp.append(tl[i].strip());
- result.append(temp);
- f.close();
- return result;
-
-
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/remove_map.py
--- a/Iterative_mapping/remove_map.py Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,29 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import sys
-from read_file import *
-
-
-unmap_file = sys.argv[1]
-map_file = sys.argv[2]
-result_file = sys.argv[3]
-
-
-unmap = read_t_file(unmap_file)
-mapped = read_t_file(map_file)
-h = file(result_file, 'w')
-
-maps = set()
-for i in range(len(mapped)):
- maps.add(mapped[i][0])
-
-
-for i in range(len(unmap)):
- name = unmap[i][0]
- if name not in maps:
- h.write(name)
- h.write('\n')
-
-
-h.close()
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/seq_track.py
--- a/Iterative_mapping/seq_track.py Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,38 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import sys
-from read_file import *
-from Bio import SeqIO
-
-unmap_file = sys.argv[1]
-reads_file = sys.argv[2]
-result_file = sys.argv[3]
-tp = sys.argv[4]
-
-
-unmap = read_t_file(unmap_file);
-
-h = file(result_file, 'w')
-
-reads = SeqIO.parse(reads_file,tp)
-um = set()
-for i in range(0, len(unmap)):
- id_r = unmap[i][0]
- um.add(id_r)
-
-for read in reads:
- if read.id in um:
- h.write('>')
- h.write(read.id)
- h.write('\n')
- h.write(read.seq.tostring())
- h.write('\n')
-
-
-
-h.close()
-
-
-
-
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/tool_dependencies.xml
--- a/Iterative_mapping/tool_dependencies.xml Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,15 +0,0 @@
-
-
-
-
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-
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/truncate.py
--- a/Iterative_mapping/truncate.py Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,32 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import sys
-from Bio import SeqIO
-
-fasta_file = sys.argv[1]
-shift_in = sys.argv[2]
-result_file = sys.argv[3]
-length = sys.argv[4]
-
-shift = int(shift_in)
-
-fasta_sequences = SeqIO.parse(open(fasta_file),'fasta');
-h = file(result_file,'w')
-for seq in fasta_sequences:
- nuc = seq.id;
- sequence = seq.seq.tostring();
- if (len(sequence)-shift)>=int(length):
- h.write('>'+nuc)
- h.write('\n')
- h.write(sequence[0:(len(sequence)-shift)])
- h.write('\n')
-
-
-
-
-h.close()
-
-
-
-
diff -r f4cc06e92530 -r a292aaf51735 Iterative_mapping/unmap.py
--- a/Iterative_mapping/unmap.py Mon Sep 15 14:52:20 2014 -0400
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,31 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import sys
-from read_file import *
-from Bio import SeqIO
-
-map_file = sys.argv[1]
-result_file = sys.argv[2]
-
-
-#reads = read_t_file(read_file);
-
-f = open(map_file);
-h = file(result_file, 'w')
-
-for aline in f.readlines():
- tline = aline.strip();
- tl = tline.split('\t');
- if len(tl)>4:
- if int(tl[1].strip()) != 0:
- h.write(tl[0].strip());
- h.write('\n');
-
-
-f.close();
-h.close()
-
-
-
-
diff -r f4cc06e92530 -r a292aaf51735 predict/.DS_Store
Binary file predict/.DS_Store has changed
diff -r f4cc06e92530 -r a292aaf51735 predict/parse_dis_pac.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/parse_dis_pac.py Mon Sep 15 14:52:43 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
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff -r f4cc06e92530 -r a292aaf51735 predict/predict_RNAs.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/predict_RNAs.py Mon Sep 15 14:52:43 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/"+"*.*")
+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 f4cc06e92530 -r a292aaf51735 predict/predict_RNAs.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/predict_RNAs.xml Mon Sep 15 14:52:43 2014 -0400
@@ -0,0 +1,63 @@
+
+
+ predict_RNAs.py $rna_list $reference_file $reactivity_file $output
+
+ biopython
+ numpy
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+**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 f4cc06e92530 -r a292aaf51735 predict/rRNA.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/rRNA.txt Mon Sep 15 14:52:43 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
diff -r f4cc06e92530 -r a292aaf51735 predict/rRNA_react.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/rRNA_react.txt Mon Sep 15 14:52:43 2014 -0400
@@ -0,0 +1,8 @@
+gi|186498419|ref|NR_022453.1|
+0.0349942738544 0.219596062195 0.0958706408233 0.194395004716 0.165304592733 NA 0.649363521545 0.004703371147 NA 0.0 NA 0.0 NA NA 0.226052814765 0.145104959196 0.235114323931 0.590973505942 NA NA 0.671823965086 NA 0.600180467352 NA 0.0 NA 0.67204697444 NA NA 0.0 NA 0.0 NA 0.0 NA 0.0 0.0905633447413 NA 0.0844580185128 NA 0.0 NA NA 0.387056722073 0.063190678881 NA 0.302648296659 0.123623615737 0.0 NA NA 0.288529445998 NA 0.0 NA 0.272682267617 1.18142319227 0.222698183429 NA NA 0.0 NA 0.308507027145 NA 0.0 0.0 NA NA NA NA NA NA NA NA 1.09905990052 0.331081493258 NA NA NA 0.0 0.316741455 NA 0.152869347497 0.358830282006 NA 0.172524825658 0.0232297542077 0.397612802938 NA NA NA 0.591410529537 0.531312624449 0.0105725487651 0.0 0.544371401206 NA 0.764412925075 NA 1.31480559071 NA NA 0.338476420086 NA NA NA NA 0.315926121887 0.0 0.0 NA 0.0 0.708180867703 1.4961467391 NA NA NA NA 0.664465128059 NA 0.0 0.0 0.562535200045 0.476678390556 2.19691885985 0.524311802546 NA 1.61857603596 0.0 NA NA 0.0 NA NA NA 0.0 0.0 NA 1.46994373288 NA NA NA 0.0 0.0 0.0 NA NA 0.0 NA NA 0.0 0.0 NA NA NA NA NA NA NA 0.0 0.0 0.0 0.0
+25s
+NA 0.445057897744 NA 0.0 0.0 0.0 0.616883939924 0.0 0.0544377002455 NA NA NA 0.0 0.274299815387 NA NA 0.0161734735511 NA NA NA 0.113806481313 NA NA 0.0 0.0 0.0 0.0 NA 0.0902360616756 NA NA 0.0259497293124 NA NA NA NA 0.0 0.0 NA 0.0 0.128445973988 NA 0.0 NA 0.0 0.0 0.0561933770321 NA 0.0 0.292152642133 NA 0.0 NA NA 0.0 NA NA 0.0 0.0 0.0 0.0 NA 0.0 0.0 0.0 0.0 NA 0.0 0.0 0.0 1.05193677381 0.112019960608 NA NA 0.0 NA NA 0.0 0.0 0.0 NA NA 0.454696508183 NA NA 0.0 0.0 0.0541585126648 NA NA 0.0 NA 0.0 NA 0.0 NA 0.0 0.0 0.0 0.00805821063273 NA NA NA 0.0 0.160579429597 NA 0.0212575846522 NA 0.0 0.0 0.0 0.0 NA 0.544027973389 NA NA NA 0.425230790667 0.733207830254 0.0 0.0 NA 0.0 NA NA 0.0 0.0 NA NA 0.0 NA NA 0.236885996269 NA NA 0.0 NA NA NA 0.0 NA 0.00917986657696 0.903567358643 NA NA NA NA 0.358438939384 NA NA 0.0 NA NA NA 0.378435644084 NA 0.565879841924 0.255131654267 NA 0.570022482976 NA NA 0.38092251132 0.0 NA 0.0 0.456921019156 NA 0.34916390672 NA 0.401409258122 0.0396326598324 NA NA 0.807425004098 0.00846128317379 0.0394311220708 NA NA NA 0.21059141834 0.239063190705 NA 0.0979608844846 0.0 NA NA NA 0.0474692522788 0.0 0.0 NA NA NA 0.656707278731 0.0 0.0761444662556 NA NA NA NA 0.391726941792 NA 0.0 0.0 1.30489991374 NA 0.945708714773 NA 0.72781357993 NA NA NA NA NA 0.0 NA 0.0 NA 0.0 0.132493170615 0.34803155101 NA NA 0.129549012388 NA NA NA 0.0 0.0 0.29614477645 NA NA 0.704763040047 0.56956988712 0.0 0.0600574362663 NA NA NA 0.362742350085 NA 0.56405635138 0.645775512364 0.896823517909 0.0 0.0540423619053 0.52126275377 NA 0.315047770556 NA NA 0.0 NA 0.0 NA NA NA 0.0 NA 0.156974005797 0.0 NA 0.0 NA NA 0.0 NA NA NA NA NA NA NA NA NA NA NA NA 0.531410545675 1.18326261838 NA NA 0.0152722862549 0.127338939497 NA 0.0353599494945 0.0 0.0142090682171 0.679734480705 0.0 0.263031834225 NA 0.985375666218 NA NA NA 0.0972886961604 NA NA NA 0.847064861501 0.968544261356 0.639603497573 NA NA 0.366911053247 0.0 NA NA 0.0 0.0925945255189 0.842712849319 0.788198195629 NA NA 0.0 NA 0.207548618929 0.343212298205 0.0 NA 0.0 0.832367460529 NA NA NA 0.0 NA 0.181366734314 NA 0.0 NA 0.496484060853 0.0 0.0 NA 0.0 NA 0.0 NA 0.0 NA 0.887394863232 0.0 0.0 0.294131087652 0.0 NA NA 0.0 0.0 0.0 NA 0.304310857899 NA 0.260357268467 NA NA NA 0.955488223116 1.26688198445 0.875229842333 NA 0.0 NA NA 1.63278092007 0.514088552204 0.408365845387 0.652619391573 NA NA 0.667954630332 0.0 NA NA NA NA 1.01245281715 0.908098734184 0.834658046014 0.374243366292 NA 0.296597361408 NA 0.521754407574 NA NA 0.412732837452 0.826636773533 0.0 0.325315528841 NA 0.0 NA NA NA 0.0 NA NA NA 0.297045398287 0.119693277826 0.0 NA NA NA NA 0.0 NA NA NA 0.413444210292 NA NA NA 0.0 0.614760267946 NA 0.0 NA NA 0.0 NA NA NA NA NA NA 0.0203387523684 0.0 NA NA 0.662888317611 NA 0.810411698898 NA NA 0.0 NA NA 0.0 0.0 NA NA NA NA 0.0388212343243 NA NA 0.648759772383 NA NA 0.0 NA NA 0.303717184162 0.0 0.0 NA NA 0.535165912151 NA 0.597271148946 0.362095296283 0.0858411830887 NA 0.143598296218 0.0381308456186 NA NA NA 0.0215817669597 1.40687529297 NA 0.0 0.0 NA 0.0303834231878 NA 0.216921517271 NA 0.0 NA NA 0.0 NA NA NA NA 0.0 NA NA NA NA 0.0 1.06699879852 0.0 NA 0.0 0.252863258544 NA 0.0 NA NA 0.292213631555 NA NA 0.249414499458 0.0 NA NA NA NA NA 0.473128266176 NA NA 0.591834136228 0.327887954759 NA 0.73713903679 0.688145314485 NA 0.753552501186 0.0 0.0 NA NA NA 0.0445763726679 NA NA NA NA NA 0.484668453557 NA 0.972325323458 0.204039342759 NA 0.026875539766 NA NA NA NA NA NA 1.27487785668 NA 1.01701187793 0.282312329051 NA NA 0.137105964441 NA 0.0 NA NA 0.0 0.0 NA NA NA 0.0 NA 1.28138528782 NA NA NA NA NA 0.380108239113 NA NA 0.0 0.0 NA 0.0 0.0 0.0 NA 0.0 NA 0.0 0.110639273201 NA 0.156758986775 0.232110678863 0.256643329142 NA NA 1.25139241899 NA NA NA 0.844770381547 0.168404091838 NA 0.227649354233 NA NA 0.101789989504 0.365846871061 NA 0.0 0.0 NA 0.0 NA NA NA 0.369098007488 NA 1.20446170804 0.0 NA NA NA 0.0 NA NA 0.749456424764 NA NA 0.0 0.0 NA NA NA NA NA NA 0.614882956175 NA 0.0 0.0 0.0 0.880504978446 0.0 NA NA 0.461424354396 NA 0.610311556777 0.0 0.0 0.0 NA NA 0.0 NA NA NA 0.0 0.0 0.0 0.0 0.0 0.0 NA NA 0.0 0.503920101526 0.0 0.249077057033 0.0 NA NA 0.0 NA NA 0.0 NA NA 0.0 0.0 0.0 NA NA NA NA NA NA 0.0 NA 0.152786269974 NA NA 0.0 1.47121659957 1.06909650565 0.700144661674 NA NA NA NA NA 0.350911905592 NA NA 0.312682673566 1.6894131616 1.01938882717 0.404565875038 1.51974693619 1.12623464472 NA NA 1.37154283401 1.2688958914 NA NA 0.26040033479 NA 0.600549521307 0.539166211903 0.333588872611 NA NA 0.506909443298 1.41856307216 NA 0.0 NA NA 0.0 NA NA NA NA 0.132579540803 NA NA NA 0.0 NA 0.0 0.221359920289 NA 0.0345263309576 NA 0.432527467916 NA NA NA NA NA 0.0 0.900492034843 0.119809739847 0.725470179848 NA 0.30434074559 0.889141767065 NA 0.101279262275 0.567410860836 0.0 NA 0.261404253614 0.0 0.0 NA NA NA 1.24681193361 NA 0.684881579094 NA NA 1.17264517378 NA NA 1.08565570148 NA 1.13223364991 0.553855213729 NA NA NA NA NA 0.132071626699 NA 0.485748763644 NA NA NA NA NA 0.0 NA 0.0 0.0 NA NA 0.359498260565 0.240057267542 NA NA NA 0.0504800340658 NA NA NA 0.0 0.0 0.0 0.197420570382 NA 0.0137503922192 0.552197932985 0.00654157195938 NA 0.554028257933 NA NA NA NA NA 0.0115936188099 0.0 0.0 NA 0.0 NA NA 0.331852524525 0.0 NA NA 0.224970334328 NA 0.348557316092 NA NA NA NA NA 1.09270921566 1.22259027297 0.602107735616 NA 0.155315571382 0.0 0.0 NA 0.317736158732 NA NA 0.401170148918 0.0 0.609158426745 0.0 NA 0.239006446129 NA NA NA NA NA NA 0.404763847023 1.46883204568 NA 0.0 0.0 0.0 NA 0.0 0.3617221521 NA 0.278893870402 NA 0.850989559775 NA 0.410969919324 0.393388305487 NA NA 1.0090276252 0.802590372932 NA NA NA 0.937695050443 1.6304479889 1.43736635079 0.792504827655 NA 0.212438225392 NA NA NA 0.825240261064 NA NA 0.519076933164 NA NA 0.182490592056 0.0 NA NA NA NA NA NA 0.525494638628 NA 0.0424499960303 NA NA NA NA 0.0 NA 0.382662671779 1.03662578195 0.478051534735 NA 0.900318367021 0.0 NA 0.0283154099686 0.302896986365 NA 0.0457690881864 NA 0.359568906648 0.101968582452 0.0 0.0 0.419460405434 NA 0.0 NA 0.0 NA NA 0.259228552941 NA 0.0 NA NA NA NA NA 0.0 0.257818736114 0.0 NA 0.0 0.0766320737715 NA 0.131365657118 0.0329649802112 NA NA NA NA 0.0 0.157019453832 0.0 NA 0.0452289137179 0.355878493915 NA NA 0.0 NA 0.0 NA 0.0 NA NA NA 0.0 NA 0.0 NA 0.0 NA NA 0.721547552016 0.0 NA 0.0 NA 0.0506067078662 NA NA NA 0.0 NA 0.0 NA 0.0 NA NA NA NA 0.240751379674 0.296570626543 0.228497209418 NA 0.0 0.0 0.202045599166 0.403533950241 NA NA 0.0277353113723 NA NA 0.0661029025382 NA 0.20681965929 NA NA 0.199947408468 0.215123796802 NA NA NA NA NA NA NA 0.822633165225 NA 0.0 0.0 0.0 0.0 NA 0.0 0.0 NA 0.0 NA 0.0635676990266 0.0 0.0 NA 0.243936204533 NA NA 0.0 NA 0.0 0.0767961818183 0.0 0.0 0.0 NA NA NA 0.0 0.0 0.489262555503 NA 0.0 NA NA NA 0.0 NA NA 0.263720493712 0.186243556243 NA NA NA NA 0.0 NA NA 0.0 NA NA 0.0 NA NA NA NA NA NA NA 0.0212100286931 NA 0.0 0.0 NA NA 0.0 0.0 0.0 0.191781514732 0.323808925525 NA NA 0.0 0.0 NA 0.0 NA 0.0942877016485 NA 0.0 NA 0.0 NA 0.0 0.0 0.0 0.0 NA NA NA NA NA 0.0 0.0 0.0 NA NA NA NA NA NA NA NA 0.0 0.0515659980884 NA 0.0 0.0 NA 0.0 0.0728981237199 0.0 NA NA NA 0.0 NA 0.0497386479542 NA NA 0.344131947399 NA NA NA 0.0 NA NA 0.0 0.0 0.0 0.0 NA NA 0.832992398226 0.0 NA 0.297655103355 0.0 NA NA NA NA NA 0.0 0.0 NA NA NA NA 0.0 0.0 0.0 0.0 0.0 0.0 NA NA 0.0 NA 0.0 NA 0.0 NA 0.0 0.563992297514 0.0746194468951 0.239855394121 NA 0.0 NA 0.0413315152918 0.0789091146893 0.0 0.450063900032 0.0 0.0187354091156 0.0 0.805138725071 0.377808848639 0.0 NA NA NA NA NA NA NA NA NA NA 0.422221172566 NA 0.083850305445 NA NA 1.69187275574 0.797712628988 NA 0.254165673967 0.389917879097 1.29764224015 NA 0.146198168789 1.08772896875 NA NA 0.25177095078 0.132249177723 NA NA NA NA NA NA 0.0 0.513332504368 NA NA NA 1.35016047735 0.918964696424 NA NA 0.638955628195 NA 0.796127761392 0.674153030358 0.279244384849 NA 0.374262073004 0.141562990812 NA 0.0 NA 0.695289932334 0.549909312314 NA NA 0.242268748968 NA 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diff -r f4cc06e92530 -r a292aaf51735 predict/read_file.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/read_file.py Mon Sep 15 14:52:43 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;
+
+
diff -r f4cc06e92530 -r a292aaf51735 predict/rtts_plot.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/rtts_plot.py Mon Sep 15 14:52:43 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')
+
+
+
+
+
+
+
+
diff -r f4cc06e92530 -r a292aaf51735 predict/tool_dependencies.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/predict/tool_dependencies.xml Mon Sep 15 14:52:43 2014 -0400
@@ -0,0 +1,9 @@
+
+
+
+
+
+
+
+
+