def haploRNA3D(templateInput, fastaFile, cycles, path, chain='A'):
"""
Creates a tertiary structure for each unique sequence in a Fasta file
using the methods from the module moderna. This function returns three
files for each sequences: (1) a fasta file comparing the target sequence with
the sequence of the template pdb structure, (2) a pdb file of the homologous
structure with no refinement, and (3) a pdb file of the homologous structure
with refinement.
Results are showed in a folder named 'haploRNA3D_month_day_hour_min'.
This folder is located in Home.
Module required:
- argparse
- subprocess
- time
- expanduser (from os.path)
Usage: <template> <fasta file> <cycles refinement> <path> <chain (default='A')>
"""
print 'Loading template...'
template = load_template(templateInput, str(chain))
clean_structure(template)
seqTemplate = str(get_sequence(template))
print 'Loading Fasta file...'
records = openFasta(fastaFile)
nameLst, seqLst = getNameSeq(records)
for index in range(len(nameLst)):
seqLst[index] = replaceBase(seqLst[index], seqTemplate)
if str(path).endswith('/'):
nameDir = str(path)+'haploRNA3D_'+time.ctime().replace(' ','_').replace(':','_')[4:16]
else:
nameDir = str(path)+'/'+'haploRNA3D_'+time.ctime().replace(' ','_').replace(':','_')[4:16]
subprocess.check_call(['mkdir', nameDir])
muscle = locate('muscle')
print 'Refining the models...'
refinementScript = locate('refine_model_mmtk.py')
secondStruct = open(nameDir+'/Secondary_Structure.fasta', 'w')
for elm in range(len(seqLst)):
print 'Refining', elm+1, 'of', len(seqLst)
seqTargTempl(seqLst[elm], seqTemplate, nameLst[elm], nameDir)
model(muscle, nameDir, nameLst[elm], templateInput, chain)
currentTemplate = load_template(nameDir+'/'+nameLst[elm][:10])
try:
subprocess.check_call(['python', refinementScript, '-m',
nameDir+'/'+nameLst[elm][:10], '-y',
str(cycles), '-o', nameDir+'/'+nameLst[elm][:11]+'_refined.pdb', '-t'])
except:
subprocess.check_call(['python', refinementScript, '-m',
nameDir+'/'+nameLst[elm][:10], '-y',
str(cycles), '-r', '2-'+str(len(currentTemplate)),
'-o', nameDir+'/'+nameLst[elm][:11]+'_refined.pdb', '-t'])
newmodel = load_model(nameDir+'/'+nameLst[elm][:11]+'_refined.pdb')
newmodelStruc = get_secstruc(newmodel)
newmodelSeqen = str(get_sequence(newmodel))
secondStruct.write('>'+nameLst[elm][:11]+'\n'+newmodelSeqen+'\n'+newmodelStruc+'\n')
secondStruct.close()
print 'Done!'
def haploRNA2D(inFile, title, repeats, siglevel, bootstrap, trc=False):
"""
Creates a secondary structure for each unique sequence and a
consensus too. All the process involves the MFE along covariance
analysis. It also creates Fasta-like files summarizing the
results.
Results are showed in a folder named 'haploRNA2D_month_day_hour_min'.
This folder will be available in Home.
Module required:
- time
- expanduser (from os.path)
Usage: <Fasta file> <title> <repeats> <significance level> <bootstrap> <transcription (default=False)>
"""
print 'Reading file...'
records = GBcode(inFile) # this step change the file to Bio.SeqIO format and also take only the GenBank code as reference
equLen_file(records)
if trc == True:
print 'Transcribing sequences...'
records = transcribe(records)
fas2clus(inFile) # make a clustal file to be used by the consensus function
consensusLst = consensusRNA(inFile+'cl')
if consensusLst:
consensusFile = True
lenSeq = len(consensusLst[0])-1
consensuStr = consensusLst[1][0:lenSeq]
else:
consensusFile = False
print 'Warning! No consensus structure defined!'
lenSeq = len(str(records[0].seq))
nameDir = expanduser('~')+'/'+'haploRNA2D_'+time.ctime().replace(' ','_').replace(':','_')[4:16]
print 'Making folder...'
subprocess.check_call(['mkdir', nameDir]) # make a folder inside the home folder as nameDir shows
VarnaLocate = locate('VARNA') # search and save the path where the application VARNA is located into the variable 'VarnaLocate'
if consensusFile:
print 'Building RNA secondary structure...'
ConsensusFasta = open(nameDir+'/'+'Consensus_Structure', 'w')
ConsensusFasta.write('>Consensus secondary structure\n'+consensuStr)
ConsensusFasta.close()
secFigFile(VarnaLocate, consensuStr, nameDir, 'Consensus_Secondary_Structure')
print 'Calculating random covariances...'
MijLst, CijLst = [], []
for a in range(repeats):
seq2Tpl = (randomSeq(len(records), 'RNA'), randomSeq(len(records), 'RNA')) # make a 2-tuple of random sequences
MijLst.append(Mij(seq2Tpl[0],seq2Tpl[1],2)) # compute and store the Mij value of the two random sequences
CijLst.append(Cij(seq2Tpl[0],seq2Tpl[1])) # compute and store the Cij value of the two random sequences
print 'Calculating real covariances...'
Mijc = searchXijc(kernelXij(MijLst), siglevel, -0.5, 2.0)[0] # here is defined the Mij critical value
Cijc = searchXijc(kernelXij(CijLst), siglevel, -0.5, 0.75)[0] # here is defined the Cij critical value
transposeRecords = transpose(records) # here, the alignment matrix is transposed and...
dicMij, dicCij = dictXij(transposeRecords, 'Mij'), dictXij(transposeRecords, 'Cij') # ... its Mij and Cij values are calculated here
print 'Saving Hinton diagrams...'
hintonDiag(dicMij, nameDir+'/Mij Hintong', 'Hinton diagram for Mij values', 2)
hintonDiag(dicMij, nameDir+'/Cij Hintong', 'Hinton diagram for Cij values', 1.5)
print 'Saving png KDE images for each array...'
dicMijVal = dicMij.values()
dicCijVal = dicCij.values()
variables = [MijLst, CijLst, dicMijVal, dicCijVal]
for a in range(len(variables)):
varName = retrieve_varName(variables[a])[0]
fig_plot(variables[a], -1, 3, nameDir+'/'+varName, varName)
print 'Saving svg Logos images for the alignment...'
info_content_file(records, title, nameDir+'/Logos')
print 'Searching significative values and best partner...'
dicMij, dicCij = signXij(dicMij, Mijc), signXij(dicCij, Cijc) # here are saved only those Mij and Cij whose value is greater than the critical value
dicMijSign, dicCijSign = dicMij.copy(), dicCij.copy()
dicMij, dicCij = bestPartner(dicMij), bestPartner(dicCij) # only those pair positions with higgest values are saved
print 'Building the constraint pattern...'
constraint = []
for a in dicMij: # 'a' is a 2-tuple which point what positions are basepaired
if a in dicCij: # this means: if 'a' is in both dicMij and dicCij...
constraint.append(a) # ... store 'a' in constraint
print 'Creating files...'
nameFasta, seqFasta = haplotypes(records)
makeFasta(nameDir+'/Haplotypes_Fasta', nameFasta, seqFasta)
conStruct = constrStruc(lenSeq, constraint) # makes the secondary structure pattern for constraint
haploStruct = []
for a in seqFasta:
resultHaploStruct = secondStruct(conStruct, a)
haploStruct.append(resultHaploStruct)
makeFasta(nameDir+'/Haplotype_Structures_Fasta', nameFasta, haploStruct)
others = open(nameDir+'/Other_Results', 'w')
others.write('Critical value for Mij:\n'+str(Mijc)+'\n'+
'Critical value for Cij:\n'+str(Cijc)+'\n'+
'Significative values for Mij:\n'+str(dicMijSign)+'\n'+
'Significative values for Cij:\n'+str(dicCijSign)+'\n'+
'Mij values after "bestPartner":\n'+str(dicMij)+'\n'+
'Cij values after "bestPartner":\n'+str(dicCij)+'\n'+
'Final constraint basepairs:\n'+str(constraint)+'\n'+
'Consensus constraint:\n'+conStruct+'\n')
if not consensusFile:
others.write('No consensus structure defined!')
others.close()
print 'Saving phylogenetic tree of secondary structures...'
treeNJ = dendroNJ(nameDir+'/Haplotype_Structures_Fasta', replicate=bootstrap)
saveNJMatrix = open(nameDir+'/NJMatrix','w')
saveNJMatrix.write(treeNJ)
saveNJMatrix.close()
saveTree(treeNJ, nameDir+'/Phylo_Secondary_Structure', ladderize=True)
print 'Making png secondary structures for each haplo-sequence...'
for a in range(len(nameFasta)):
print 'Making',a+1,'of', len(nameFasta)
if '(' in haploStruct[a]:
secFigFile(VarnaLocate, haploStruct[a], nameDir, nameFasta[a], seqFasta[a])
else:
print nameFasta[a], 'has no a RNA secondary structure'
print 'Done!'
