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rundistribs.py
1053 lines (921 loc) · 44.4 KB
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rundistribs.py
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'''
Created July 1, 2015
'''
import shutil
from SequenceGenerator import *
from BayesExtract import *
from BEASTExtract import *
from my_helper import get_diss_matrix
from make_rMDSscript import make_rMDSscript
import os
import topology_file_splitter
from distribcompare import distribcompare
from LogMapPlotter import LogMapPlotter
import subprocess
from plot_topos import plot_topos
from operator import itemgetter
from plot_orderedlog import plot_orderedlog
def makeSeq(n,tree):
seq_dir = 'c:\\seqgen\\'
seq_tree_dir = 'c:\\seqgen\\' + tree + '\\'
for i in range(1,n+1):
shutil.copyfile(seq_dir + tree + ".txt", seq_dir + tree + str(i) + ".txt")
if not os.path.exists(seq_dir + tree + "\\" + tree + str(i) + ".nex"):
tree_gen = SequenceGenerator(tree + str(i),"c:\\seqgen\\" + tree + str(i) + ".txt")
tree_gen.runseq_gen()
shutil.copyfile(seq_dir + tree + str(i) + ".txt", seq_dir + tree + str(i) + "\\" + tree + str(i) + ".txt")
else:
print("SeqGen already run for tree " + str(i) + " - skipping sequence generation.")
def copyBayes(tree,treehome):
bayes_home = 'c:\\seqgen\\bayesfiles\\'
bayes_dir = treehome + "\\bayes\\"
if not os.path.exists(bayes_dir):
shutil.copytree(bayes_home, bayes_dir)
else:
print("Bayes files already copied for " + tree)
def copyTree(tree,treehome,targetdir):
if not os.path.exists(targetdir + "\\" + tree):
shutil.copyfile(treehome + tree + ".txt",targetdir + tree + ".txt")
shutil.copyfile(treehome + tree + ".nex",targetdir + tree + ".nex")
else:
print("Tree and NEXUS files already copied for " + tree)
def makeBayesScript(tree,treedir):
if not os.path.exists(treedir + "\\" + tree + "-command.nex"):
outfile = open(treedir + tree + "-command.nex",'w')
outfile.write("#NEXUS\n")
outfile.write("\n")
outfile.write("begin mrbayes;\n")
outfile.write("\t" + "set autoclose=yes nowarn=yes;\n")
outfile.write("\t" + "execute " + tree + ".nex;\n")
outfile.write("\t" + "lset nst=6 rates=invgamma;\n")
outfile.write("\t" + "mcmc ngen=5000000 samplefreq=1000;\n")
outfile.write("\t" + "sump;\n")
outfile.write("\t" + "sumt;\n")
outfile.write("\t" + "quit;\n")
outfile.write("end;\n")
outfile.close()
else:
print("Skipping Mr Bayes Driver generation - already done")
def runBayes(tree,treedir):
if not os.path.exists(treedir + "\\bayes\\" + tree + ".nex" + ".mcmc"):
os.chdir(treedir + "\\bayes\\")
command = "mrbayes_x64 " + tree + "-command.nex"
call(command.split())
else:
print("Skipping Mr Bayes MCMC - already done for " + tree + ".")
def makeBayestreeouts(tree, treehome):
if not os.path.exists(treehome + "\\" + tree + "_bayes_treeout.txt"):
os.chdir(treehome)
tree_extract = BayesExtract(tree, treehome + "\\" + tree + ".nex", treehome, 1000)
tree_extract.treeMatch()
trees_file_name = treehome + tree + "_bayes_treeout.txt"
shutil.copyfile(tree + "treeout.txt", trees_file_name)
# Add the base tree in at line one:
infile1 = open(trees_file_name,'r')
infile2 = open(tree + ".txt",'r')
outfile = open(treehome + "temptrees.txt",'w')
outfile.write(infile2.readline()+"\n")
infile2.close()
for line in infile1:
outfile.write(line)
infile1.close()
outfile.close()
shutil.copyfile("temptrees.txt",trees_file_name)
else:
print("Skipping Mr Bayes treeout extraction - already done for " + tree)
def copyGTP(treehome):
gtp_version = "gtp.jar"
if not os.path.exists(treehome + gtp_version):
shutil.copyfile('c:\\seqgen\\jars\\' + gtp_version, treehome + gtp_version)
def findSturmMean(tree, treehome, model,rooted=False):
sturm_version = "SturmMean_130704.jar"
sturm_file = tree + "_sturm.txt"
if not os.path.exists(treehome + "\\" + sturm_file):
shutil.copyfile('c:\\seqgen\\jars\\' + sturm_version, treehome + sturm_version)
os.chdir(treehome)
if (rooted == False):
command = "java -jar " + sturm_version + " -a random -e 0.0001 -u -o " + sturm_file + " " + tree + "_" + model + "_treeout.txt"
elif (rooted == True):
command = "java -jar " + sturm_version + " -a random -e 0.0001 -o " + sturm_file + " " + tree + "_" + model + "_treeout.txt"
call(command.split())
else:
print("Mean already found - skipping SturmMean")
# Extract mean tree from file - from my_helper:
trees_mean = tree + "_mn.txt"
if not os.path.exists(trees_mean):
os.chdir(treehome)
sturmMean_output_file = open(sturm_file,'r')
outfile = open(trees_mean,'w')
for line in sturmMean_output_file:
match_tree = re.match(r'(\(.+)',line)
if match_tree:
break
sturmMean_output_file.close()
if match_tree:
outfile.write(match_tree.group(1) + "\n")
outfile.close()
else:
print ("Warning: could not extract tree from the output file " + sturm_file + "; returning empty string")
def extractMrBayesMajorityTree(tree, treehome):
trees_maj = tree + "_bayes_maj.txt"
trees_maj_file = tree + ".nex.con.tre"
os.chdir(treehome)
if not os.path.exists(trees_maj):
# First, get taxa:
infile = open(trees_maj_file,'r')
taxa = []
tree_line = ""
for line in infile:
temp = line.split()
m = re.match('[0-9]+',temp[0]) # check for the labels
if (m):
taxa.append(temp[1].rstrip(',;'))
elif (temp[0] == "tree"):
tree_line = temp[4]
break # once we hit the tree portion of the nexus file, we're done
infile.close()
# Then, extract newick tree from the con_tree probability string:
tree_sub = re.sub(r'\[.*?\]',"",tree_line)
t_with_taxa = []
for i in range(len(taxa)+1):
for j in range(1,len(taxa)+1):
tree_sub = re.sub(str(j)+':',taxa[j-1]+':',tree_sub)
outfile = open(trees_maj,'w')
outfile.write(tree_sub)
outfile.close()
else:
print("Majority tree already extracted from .con.tre - skipping")
def makeBayesMaj(tree, treehome):
os.chdir(treehome + "/bayes/")
treeout = tree + "treeout.txt"
majout = tree + "_bayes_maj_treeout.txt"
maj = tree + "_bayes_maj.txt"
if not os.path.exists(majout):
infile2 = open(maj, 'r')
infile3 = open(treeout, 'r')
outfile = open(majout, 'w')
outfile.write(infile2.readline() + "\n")
infile2.close()
for line in infile3:
outfile.write(line)
infile3.close()
outfile.close()
else:
print("Bayes treeout with mean and majority tree already extracted for " + tree + " - skipping")
def makeBayesMnMaj(tree, treehome):
os.chdir(treehome)
treeout = tree + "_bayes_treeout.txt"
mnmajout = tree + "_bayes_mn_maj_treeout.txt"
mn = tree + "_mn.txt"
maj = tree + "_bayes_maj.txt"
if not os.path.exists(mnmajout):
infile1 = open(mn, 'r')
infile2 = open(maj, 'r')
infile3 = open(treeout, 'r')
outfile = open(mnmajout, 'w')
outfile.write(infile1.readline())
infile1.close()
outfile.write(infile2.readline() + "\n")
infile2.close()
for line in infile3:
outfile.write(line)
infile3.close()
outfile.close()
else:
print("Bayes treeout with mean and majority tree already extracted for " + tree + " - skipping")
def plotMDS(tree, treehome, model, mn=False, maj=False):
os.chdir(treehome)
model_label = "_" + model + "_"
titlest = "All trees with base "
titleend = "under MDS"
if (mn == True and maj == True):
suffix = "_mn_maj_"
titlest = titlest + " mean and majority trees "
elif (mn == True):
suffix = "_mn_"
titlest = titlest + " and mean tree "
else:
suffix = "_"
if not os.path.exists(tree + suffix + "2D.r"):
temp = make_rMDSscript(tree, tree + model_label + "dist_matrix", titlest + titleend, 1, mn, maj)
temp.plot_MDS(2)
command = "rscript " + tree + "_2D.r"
call(command.split())
else:
print ("MDS plots already exist for 2D trees - skipping")
def geoDistanceMatrix(tree, treefile, treehome, model, rooted=False):
gtp_jar = "gtp.jar"
model_label = "_" + model + "_"
tree_distances = tree + model_label + "distances.txt"
#print ("treehome is: " + treehome)
#print ("tree distance file: " + tree_distances)
#print ("treefile is: " + treefile)
if not os.path.exists(tree_distances):
if (rooted==False):
command = "java -jar " + gtp_jar + " -u -o " + tree_distances + " " + treefile
elif (rooted==True):
command = "java -jar " + gtp_jar + " -o " + tree_distances + " " + treefile
call(command.split())
else:
print ("Distance file already exists - skipping running Analysis")
tree_dist_matrix = tree + model_label + "dist_matrix.txt"
if not os.path.exists(tree_dist_matrix):
get_diss_matrix(tree_distances,tree_dist_matrix,"symmetric")
else:
print ("Distance matrix already exists - skipping running Analysis")
def runRAxML(tree, treehome):
rax_path = "c:\\raxml\\"
rax_ver = "raxmlHPC"
raxml_dir = "\\raxml"
data_name = tree
rax_treeout = tree + "_raxml_treeout.txt"
print("Treehome is: " + treehome)
if not os.path.exists(treehome + raxml_dir):
print ("Treehome plus rax is: " + treehome + raxml_dir)
os.chdir(treehome)
#First, convert Nexus files to Phylip format:
command = "convbioseq phylip " + tree + ".nex"
call(command.split())
# Run RAxML:
os.mkdir(treehome + "\\" + raxml_dir)
os.system(rax_path + rax_ver + ' -s ' + treehome + '\\' + data_name + '.phy' + ' -n ' + data_name + ' -m GTRGAMMA -e 0.001 -f a -k -x 27362 -p 96618 -N 1000 -w ' + os.getcwd() + raxml_dir + "\\" )
else:
print("RAxML directory already exists - skipping running RAxML")
def makeRAxMLtreeout(tree, treehome):
outpath = treehome + "\\raxml\\" + tree + "_raxml_treeout.txt"
print ('outpath is: ' + outpath)
if not os.path.exists(outpath):
os.chdir(treehome + "\\raxml\\")
trees_file_name = treehome + "\\raxml\\" + tree + "_raxml_treeout.txt"
raxml_bootstrap = treehome + "\\raxml\\" + "RAxML_bootstrap." + tree
raxml_best = treehome + "\\raxml\\" + "RAxML_bestTree." + tree
# Add the base tree in at line one:
infile1 = open(treehome + "\\" + tree + ".txt",'r')
infile2 = open(raxml_best,'r')
infile3 = open(raxml_bootstrap,'r')
outfile = open(trees_file_name,'w')
outfile.write(infile1.readline()+"\n")
outfile.write(infile2.readline())
infile1.close()
infile2.close()
for line in infile3:
outfile.write(line)
infile3.close()
outfile.close()
findSturmMean(tree, treehome + "\\raxml\\","raxml")
# Add the mean tree to the treeout file:
mn = treehome + "\\raxml\\" + tree + "_mn.txt"
infile4 = open(outpath,'r')
infile5 = open(mn,'r')
outfile2 = open('temp.txt','w')
outfile2.write(infile4.readline())
outfile2.write(infile5.readline())
for line in infile4:
outfile2.write(line)
infile4.close()
infile5.close()
outfile2.close()
shutil.copy('temp.txt',outpath)
else:
print("Skipping RAxML treeout extraction - already done for " + tree)
def makeRAxMLbesttreeout(tree, treehome):
outpath = treehome + "\\raxml\\" + tree + "_raxml_best_treeout.txt"
if not os.path.exists(outpath):
os.chdir(treehome + "\\raxml\\")
trees_file_name = treehome + "\\raxml\\" + tree + "_raxml_best_treeout.txt"
raxml_bootstrap = treehome + "\\raxml\\" + "RAxML_bootstrap." + tree
raxml_best = treehome + "\\raxml\\" + "RAxML_bestTree." + tree
infile2 = open(raxml_best,'r')
infile3 = open(raxml_bootstrap,'r')
outfile = open(trees_file_name,'w')
outfile.write(infile2.readline())
infile2.close()
for line in infile3:
outfile.write(line)
infile3.close()
outfile.close()
else:
print("Skipping RAxML best tree treeout extraction - already done for " + tree)
def prepforBEAUti(tree, treehome):
beast_dir = "\\BEAST\\"
if not os.path.exists(treehome + beast_dir):
os.chdir(treehome)
os.mkdir(treehome + beast_dir)
shutil.copy(treehome + "\\" + tree + ".nex", treehome + beast_dir + tree + ".nex")
shutil.copy(treehome + "\\" + tree + ".xml", treehome + beast_dir + tree + ".xml")
shutil.copy(treehome + "\\" + tree + "_state.xml", treehome + beast_dir + tree + "_state.xml")
else:
print("BEAST directory already exists - skipping for BEAUti prep for " + tree)
def runBEAST(tree, treehome):
beast_dir = "\\BEAST\\"
beast_path = "c:\\BEAST\\lib\\"
beast_ver = "beast.jar"
data_name = tree
beast_rawout = tree + ".trees"
beauti_out = tree + ".xml"
state_file = tree + "_state.xml"
if not os.path.exists(treehome + beast_dir + beast_rawout):
print ("Treehome plus beast is: " + treehome + beast_dir)
os.chdir(treehome + beast_dir)
os.system("java -jar " + beast_path + beast_ver + " -beagle -working -seed 777 -statefile " + state_file + " " + beauti_out)
else:
print("BEAST directory already exists - skipping running BEAST")
def findBEASTbesttree(tree, treehome):
# Tree Annotator
beast_dir = "\\BEAST\\"
beast_path = "c:\\BEAST\\"
treeanno_ver = "treeannotator"
beast_best = tree + "_maj"
beast_rawout = tree + ".trees"
burnin = 25
if not os.path.exists(treehome + beast_dir + beast_best):
out_temp = open(treehome + beast_dir + beast_best,'w')
out_temp.write("")
out_temp.close()
command = beast_path + treeanno_ver + " -burnin " + str(burnin) + " " + treehome + beast_dir + tree + ".trees " + treehome + beast_dir + beast_best
call(command.split())
else:
print("Tree Annotator already run for " + tree + " - skipping")
os.chdir(treehome + beast_dir)
trees_maj = tree + "_maj.txt"
trees_maj_file = beast_best
if not os.path.exists(trees_maj):
# First, get taxa:
infile = open(trees_maj_file,'r')
print ("trees maj file is: " + trees_maj_file)
taxa = []
tree_line = ""
for line in infile:
temp = line.split()
if (len(temp) == 0):
continue
else:
m = re.match('[0-9]+',temp[0]) # check for the labels
if (m):
taxa.append(temp[1].rstrip(',;'))
elif (temp[0] == "tree"):
tree_line = temp[3]
break # once we hit the tree portion of the nexus file, we're done
print ("Taxa is: " + str(taxa))
infile.close()
# Then, extract newick tree from the con_tree probability string:
tree_sub = re.sub(r'\[.*?\]',"",tree_line)
t_with_taxa = []
for i in range(len(taxa)+1):
for j in range(1,len(taxa)+1):
tree_sub = re.sub(str(j)+':',taxa[j-1]+':',tree_sub)
outfile = open(trees_maj,'w')
outfile.write(tree_sub)
outfile.close()
else:
print("Majority tree already extracted from " + tree + ".trees - skipping")
def makeBeastTreeout(tree, treehome):
beast_dir = "//BEAST//"
beast_treeout = tree + "_BEAST_treeout.txt"
if not os.path.exists(treehome + beast_dir + beast_treeout):
temp = BEASTExtract(tree, tree + ".trees", treehome + beast_dir, 1000, 1)
temp.treeMatch()
os.chdir(treehome + beast_dir)
infile1 = open(tree + "treeout.txt",'r')
infile2 = open(treehome + "\\" + tree + ".txt",'r')
outfile = open(beast_treeout,'w')
outfile.write(infile2.readline()+ "\n")
infile2.close()
for line in infile1:
outfile.write(line)
infile1.close()
outfile.close()
else:
print("Beast treeout already extracted from " + tree + ".trees - skipping")
def extractBEASTMaj (tree, treehome):
os.chdir(treehome + "//BEAST//")
treeout = tree + "_BEAST_treeout.txt"
majout = tree + "_BEAST_maj_treeout.txt"
maj = tree + "_maj.txt"
if not os.path.exists(majout):
infile2 = open(maj, 'r')
infile3 = open(treeout, 'r')
outfile = open(majout, 'w')
outfile.write(infile2.readline() + "\n")
infile2.close()
for line in infile3:
outfile.write(line)
infile3.close()
outfile.close()
else:
print("Beast treeout with majority tree already extracted for " + tree + " - skipping")
def extractBEASTMnMaj(tree, treehome):
os.chdir(treehome + "//BEAST//")
treeout = tree + "_BEAST_treeout.txt"
mnmajout = tree + "_BEAST_mn_maj_treeout.txt"
mn = tree + "_mn.txt"
maj = tree + "_maj.txt"
if not os.path.exists(mnmajout):
infile1 = open(mn, 'r')
infile2 = open(maj, 'r')
infile3 = open(treeout, 'r')
outfile = open(mnmajout, 'w')
outfile.write(infile1.readline())
infile1.close()
outfile.write(infile2.readline() + "\n")
infile2.close()
for line in infile3:
outfile.write(line)
infile3.close()
outfile.close()
else:
print("BEAST treeout with mean and majority tree already extracted for " + tree + " - skipping")
def treeout(tree, model, treehome):
if (model == "bayes"):
treeout = tree + "_bayes_maj_treeout.txt"
elif (model == "BEAST"):
shutil.copyfile(treehome + '/BEAST/' + tree + "treeout.txt", treehome + '/BEAST/' + tree + "BEASTtreeout.txt")
treeout = tree + "_BEAST_maj_treeout.txt"
elif (model == "raxml"):
treeout = tree + "_raxml_best_treeout.txt"
elif (model == "phyml"):
treeout = tree + "_phyml_treeout.txt"
return treeout
def createQQplots(tree, treehome, model1, model2,xlow=0,xhigh=1,ylow=0,yhigh=1):
sturm_version = "SturmMean_130704.jar"
analysis_jar = "analysis_140702.jar"
shutil.copyfile('c:\\seqgen\\jars\\' + sturm_version, treehome + "\\" + sturm_version)
shutil.copyfile('c:\\seqgen\\jars\\' + analysis_jar, treehome + "\\" + analysis_jar)
model1out = treeout(tree, model1, treehome)
model2out = treeout(tree, model2, treehome)
shutil.copyfile(treehome + '/' + model1 + '/' + model1out, treehome + '/' + model1out)
shutil.copyfile(treehome + '/' + model2 + '/' + model2out, treehome + '/' + model2out)
t1root = False
t2root = False
if (model1 == "BEAST"):
t1root = True
print "model1 is BEAST"
if (model2 == "BEAST"):
t2root = True
print "model2 is BEAST"
treeplot = distribcompare(tree + "_" + model1 + "_" + model2, model1out, model2out, treehome, t1root, t2root)
treeplot.find_means()
treeplot.find_disttomean()
treeplot.set_dims(xlow,xhigh,ylow,yhigh)
treeplot.qq_plot()
def runPhyML(tree, treehome):
phyml_path = "c:\\phyml\\bin\\"
phyml_ver = "phyml"
phyml_dir = "\\phyml"
phyml_name = tree
print("Treehome is: " + treehome)
if not os.path.exists(treehome + phyml_dir):
print ("Treehome plus phyml is: " + treehome + phyml_dir)
os.chdir(treehome)
#First, convert Nexus files to Phylip format:
command = "convbioseq phylip " + tree + ".nex"
call(command.split())
#Run PhyML:
os.mkdir(treehome + "\\" + phyml_dir)
shutil.copy(treehome + "\\" + tree + ".phy",treehome + phyml_dir + "\\" + tree + ".phy")
os.chdir(treehome + phyml_dir)
os.system(phyml_path + phyml_ver + ' -i ' + tree + ".phy -b 1000 -c 4 -a e -m GTR -v e")
else:
print("PhyML directory already exists - skipping running PhyML")
def makePhyMLtreeout(tree, treehome):
os.chdir(treehome + "\\phyml")
infile1 = open(tree + ".phy" + "_phyml_tree.txt",'r')
best_tree = re.sub(r'([0-9]+:)',":",infile1.readline())
infile2 = open(tree + ".phy" + "_phyml_boot_trees.txt",'r')
outfile = open(tree + "_phyml_treeout.txt",'w')
outfile.write(best_tree)
infile1.close()
for line in infile2:
outfile.write(line)
infile2.close()
outfile.close()
def orderByLogMap(tree, treehome, model):
# Assumes you've already done the log map to generate 'all coordinates':
all_coords_file = tree + "_" + model + "_allcoords.txt"
ordered_coords_file = tree + "_" + model + "_ordered_allcoords.txt"
ordered_trees_file = tree + "_" + model + "_ordered_treeout.txt"
os.chdir(treehome + "/" + model + "/")
infile1 = open(all_coords_file,'r')
coords_y = []
coords = []
for line in infile1:
coords.append(line.rstrip("/n"))
temp = line.split(" ")
coords_y.append(temp[1])
infile1.close()
# Sort the coordinates, keeping track of their index:
coords_ordered = sorted((e,i) for i,e in enumerate(coords_y))
# Import trees
trees_raw = []
infile2 = open(treehome + "/" + model + "/" + treeout(tree,model,treehome),'r')
for line in infile2:
temp = line.rstrip("\n")
trees_raw.append(temp)
infile2.close()
# Sort the trees by the coordinates for use in MDS:
trees_sorted = [None] * 1001
#print("Trees_raw length is: " + str(len(trees_raw)) + " for model " + model)
#print("Coords_ordered length is: " + str(len(coords_ordered)) + " for model " + model)
for i in range(len(trees_raw)):
trees_sorted[i] = trees_raw[coords_ordered[i][1]]
coords_sorted = [None] * 1001
# Sort the coordinates for logmap:
for i in range(len(coords)):
coords_sorted[i] = coords[coords_ordered[i][1]]
outcoords = open(ordered_coords_file,'w')
for i in range(len(coords_sorted)):
if (coords_sorted[i] != None):
outcoords.write(coords_sorted[i])
outcoords.close()
outtrees = open(ordered_trees_file,'w')
for i in range(len(trees_sorted)):
if (trees_sorted[i] != None):
outtrees.write(trees_sorted[i] + "\n")
outtrees.close()
def convertRootedCoords(tree, treecoordsdir):
coordsfiles = os.listdir(treecoordsdir)
os.chdir(treecoordsdir)
os.mkdir("origcoords")
for coords_file_name in coordsfiles:
shutil.copy(coords_file_name, treecoordsdir + "/origcoords/" + coords_file_name)
for coords_file_name in coordsfiles:
infile = open(coords_file_name,'r')
outfile = open('tempcoords.txt','w')
for line in infile:
coordholder = line.rstrip("\n").split(" ")
# Add the second and third coordinates together to 'fix' the split lengths
# due to BEAST (or another model) auto-rooting the output trees
coordsum = float(coordholder[1]) + float(coordholder[2])
coordholder[1] = str(coordsum)
coordtemp = ""
for i in range(len(coordholder)):
coordtemp = coordtemp + coordholder[i] + " "
outfile.write(coordtemp + "\n")
infile.close()
outfile.close()
shutil.copy('tempcoords.txt',treecoordsdir + coords_file_name)
os.remove('tempcoords.txt')
def lognormcoords(tree, treehome, model):
coordsdir = treehome + "/" + model + "/coords/"
coordsfiles = os.listdir(coordsdir)
topodir = treehome + "/" + model + "/split_by_topology"
topofiles = os.listdir(topodir)
if __name__ == '__main__':
#tree = "onetenth"
#tree = "ctwotenth"
tree = "largeleaves"
treedir = "c:/seqgen/" + tree
'''
model = 'BEAST'
modeldir = '/BEAST/'
#for i in range(1,2):
# convertRootedCoords(tree + str(i), treedir + str(i) + modeldir + 'coords/')
# Make the Sequences
makeSeq(10,tree)
treedir = 'c:\\seqgen\\' + tree
model = "bayes"
bayesdir = "\\bayes\\"
### Section: Mr Bayes###
# Move Mr. Bayes files and the sequence files to the appropriate directory
for i in range(1,11):
copyBayes(tree + str(i), treedir + str(i))
copyTree(tree + str(i), treedir + str(i) + "\\",treedir + str(i) + "\\bayes\\")
# Generate Mr. Bayes command scripts
for i in range(1,11):
makeBayesScript(tree + str(i), treedir + str(i) + "\\bayes\\")
# Run Mr. Bayes MCMC:
#for i in range(1,11):
# runBayes(tree + str(i), treedir + str(i))
# Extract trees:
for i in range(1,11):
makeBayestreeouts(tree + str(i), treedir + str(i) + "\\bayes\\")
findSturmMean(tree + str(i), treedir + str(i) + "\\bayes\\","bayes")
extractMrBayesMajorityTree(tree + str(i), treedir + str(i) + "\\bayes\\")
makeBayesMnMaj(tree + str(i), treedir + str(i) + "\\bayes\\")
# Find geodesic distances:
for i in range(1,11):
#print("Target path is: " + treedir + str(i) + "\\bayes\\")
copyGTP(treedir + str(i) + "\\bayes\\")
# Base + all trees
geoDistanceMatrix(tree + str(i), tree + str(i) + "_" + model + "_treeout.txt", treedir + str(i) + bayesdir, model)
# Base + mean and maj
geoDistanceMatrix(tree + str(i), tree + str(i) + "_" + model + "_" + "mn_maj_treeout.txt" , treedir + str(i) + bayesdir, model)
# Section: RAxML
# Run RAxML
for i in range (1,11):
runRAxML(tree + str(i), treedir + str(i))
makeRAxMLtreeout(tree + str(i), treedir + str(i))
findSturmMean(tree + str(i), treedir + str(i) + "\\raxml\\","raxml")
# Find geodesic distances:
model = "raxml"
raxdir = "\\raxml\\"
for i in range(1,11):
print("Target path is: " + treedir + str(i) + raxdir)
copyGTP(treedir + str(i) + raxdir)
# Base + best + all bootstrap trees
geoDistanceMatrix(tree + str(i), tree + str(i) + "_" + model + "_" + "treeout.txt" , treedir + str(i) + raxdir, model)
# BEAST section
# Prep for BEAUti - need to figure out command line way to do this
# Run BEAST routines:
for i in range(1,11):
model = "BEAST"
prepforBEAUti(tree + str(i), treedir + str(i))
runBEAST(tree + str(i), treedir+ str(i))
findBEASTbesttree(tree+ str(i), treedir + str(i))
makeBeastTreeout(tree + str(i), treedir + str(i))
findSturmMean(tree + str(i), treedir + str(i) + "\\BEAST\\","BEAST",rooted=True)
extractBEASTMnMaj(tree + str(i), treedir + str(i))
# Find geodesic distances:
beast_dir = "\\BEAST\\"
for i in range(1,11):
copyGTP(treedir + str(i) + beast_dir)
# Base + mean + majority + other 1000 trees
geoDistanceMatrix(tree + str(i), tree + str(i) + "_" + model + "_" + "treeout.txt" , treedir + str(i) + beast_dir, model,rooted=True)
#PhyML
for i in range(1,11):
runPhyML(tree + str(i), treedir + str(i))
makePhyMLtreeout(tree + str(i), treedir + str(i))
findSturmMean(tree + str(i), treedir + str(i) + "\\phyml\\","phyml")
# Find geodesic distances:
model = "phyml"
phyml_dir = "\\phyml\\"
print("Target path is: " + treedir + str(i) + phyml_dir)
copyGTP(treedir + str(i) + phyml_dir)
# Base + best + all bootstrap trees
geoDistanceMatrix(tree + str(i), tree + str(i) + "_" + model + "_" + "treeout.txt" , treedir + str(i) + phyml_dir, model)
### Plotting Section
models = ["bayes","raxml","BEAST","phyml"]
#for j in range(len(models)):
# model = models[j]
# for i in range(1,11):
# treedir = "c:/seqgen/" + tree
# model_dir = "/" + model + "/"
# topo_dir = "split_by_topology/"
# if os.path.exists(treedir + str(i) + model_dir + topo_dir):
# shutil.rmtree(treedir + str(i) + model_dir + topo_dir)
# Adding coloring:
# Need:
# 1) Logmap ordered trees
# 1)a) Plot logmap ordered trees
# 2) Feed trees into distance file
# 3) Create new distance matrix
# 4) Run MDS
#models = ["bayes","raxml","BEAST","phyml"]
models = ["bayes","raxml"]
models = ['BEAST']
for j in range(len(models)):
model = models[j]
treedir = 'c:/seqgen/' + tree
for i in range (1,2):
analysis_version = "analysis_140702.jar"
treedir = 'c:/seqgen/' + tree
model_dir = '/' + model + '/'
makeBayesMaj(tree + str(i), treedir + str(i))
makeRAxMLbesttreeout(tree + str(i), treedir + str(i))
topo_dir = treedir + str(i) + model_dir + 'split_by_topology'
topo_prefix = topo_dir + "/topo.txt"
centre_dir = treedir + str(i) + model_dir + 'centres'
centre_prefix = centre_dir + "/centre_"
trees_topo_file_name = treedir + str(i) + model_dir + tree + str(i) + "_" + model + "_tree_topo.txt"
trees_file_name = treeout(tree + str(i), model, treedir + str(i))
#print ("trees file is: " + trees_file_name)
all_topos_coords_centre1 = tree + str(i) + "_" + model + "_allcoords.txt"
if not os.path.exists(treedir + str(i) + model_dir + all_topos_coords_centre1):
os.chdir(treedir + str(i) + model_dir)
if (model == 'BEAST'):
command = 'java -jar ' + analysis_version + ' -a log_map -o ' + all_topos_coords_centre1 + ' -f ' + centre_prefix + "1" + ' ' + treedir + str(i) + model_dir + trees_file_name
else:
command = 'java -jar ' + analysis_version + ' -u -a log_map -o ' + all_topos_coords_centre1 + ' -f ' + centre_prefix + "1" + ' ' + treedir + str(i) + model_dir + trees_file_name
print(command + "\n")
subprocess.call(command.split())
orderByLogMap(tree + str(i), treedir + str(i), model)
plotit = plot_orderedlog(tree + str(i), treedir + str(i), model)
plotit.makeScript()
plotit.makePlots()
trees_ordered_file = tree + str(i) + "_" + model + "_ordered_treeout.txt"
if (model == "BEAST"):
os.chdir(treedir + str(i) + model_dir)
geoDistanceMatrix(tree + str(i), trees_ordered_file, treedir + str(i) + model_dir, model, True)
else:
os.chdir(treedir + str(i) + model_dir)
geoDistanceMatrix(tree + str(i), trees_ordered_file, treedir + str(i) + model_dir, model, False)
dist_matrix_file = tree + str(i) + "_" + model + "_" + "dist_matrix.txt"
colMDS = make_rMDSscript(tree + str(i), treedir + str(i) + model_dir, dist_matrix_file, "Colored relative to Logmap order", aspect_ratio=1)
colMDS.plot_MDS(2)
colMDS.plot_MDS(3)
colMDS.run_MDSplots(2)
colMDS.run_MDSplots(3)
if not os.path.exists(trees_topo_file_name):
os.chdir(treedir + str(i) + model_dir)
command = "java -jar " + analysis_version + " -a topology_count -o " + trees_topo_file_name + " " + trees_file_name
subprocess.call(command.split())
else:
print "File %s already exists - skipping generating topology info about all means \n" % trees_topo_file_name
if not os.path.exists(topo_dir):
os.mkdir(topo_dir)
topology_file_splitter.makeFiles(trees_file_name,trees_topo_file_name,topo_prefix)
else:
print "Directory %s already exists - skipping splitting the means by topology \n" % topo_dir
centre_dir = treedir + str(i) + model_dir + 'centres'
centre_prefix = centre_dir + "/centre_"
topology_num = 0
if not os.path.exists(centre_dir):
os.mkdir(centre_dir)
f = open(trees_topo_file_name)
topNum = 0
# Extract the number of topologies from the topology file
for line in f:
tempStr = line
if (tempStr[0:3] != "Raw"):
continue
else:
trimStr = tempStr.lstrip("Raw topology counts: ").split()
topNum = len(trimStr)
topology_num = topNum
break
f.close()
for n in xrange(1,topNum+1):
testout = centre_prefix + str(n)
tree_file_name = topo_dir + '/topo' + str(n) + '.txt'
f = open(tree_file_name,'r')
temptree = f.readline()
if (temptree == "(((E:.1,D:.1):.1,C:.11):.01,B:.1,A:.1);\n"):
temptree = "(((E:0.1,D:0.1):0.1,C:0.11):0.01,B:0.1,A:0.01);\n"
if (model == "BEAST" and temptree != "(((E:0.1,D:0.1):0.1,C:0.11):0.01,B:0.1,A:0.01);\n"):
m = re.match(r'(.*?\):)[0-9]+[.][0-9]+(.*?\):)[0-9]+[.][0-9]+(.*?\):)[0-9]+[.][0-9]+(.+;)',temptree)
else:
m = re.match(r'(.*?\):)[0-9]+[.][0-9]+(.*?\):)[0-9]+[.][0-9]+(.+;)',temptree)
if not m:
print("Error: can't change interior edges lengths")
exit
if (model == "BEAST" and temptree != "(((E:0.1,D:0.1):0.1,C:0.11):0.01,B:0.1,A:0.01);\n"):
temptree = m.group(1) + '0.000000001' + m.group(2) + '0.000000001' + m.group(3) + '0.000000001' + m.group(4)
else:
temptree = m.group(1) + '0.000000001' + m.group(2) + '0.000000001' + m.group(3)
out = open(centre_prefix + str(n),'w')
out.write(temptree + '\n')
out.close()
f.close()
coords_dir = treedir + str(i) + model_dir + 'coords'
coords_prefix = coords_dir + "/coords_"
if not os.path.exists(coords_dir):
os.mkdir(coords_dir)
for topo_file_name in os.listdir(topo_dir):
# get the number at the end of the file name
match_file_name = re.match(r'topo([0-9]+).txt',topo_file_name)
z = int(match_file_name.group(1))
if (model == "BEAST"):
command = 'java -jar ' + treedir + str(i) + "/" + analysis_version + ' -a log_map -o ' + coords_prefix + str(z) + '.txt -f ' + centre_prefix + str(z) + ' ' + topo_dir +'/' +topo_file_name
else:
command = 'java -jar ' + treedir + str(i) + "/" +analysis_version + ' -u -a log_map -o ' + coords_prefix + str(z) + '.txt -f ' + centre_prefix + str(z) + ' ' + topo_dir +'/' +topo_file_name
subprocess.call(command.split())
if (model == "BEAST"):
convertRootedCoords(tree + str(i), treedir + str(i) + model_dir + 'coords/')
else:
print "Directory %s already exists - skipping computing the log map coordinates \n" % coords_dir
all_topos_coords_centre1 = tree + str(i) + "_allcoords.txt"
if not os.path.exists(all_topos_coords_centre1):
command = 'java -jar ' + analysis_version + ' -u -a log_map -o ' + all_topos_coords_centre1 + ' -f ' + centre_prefix + "1" + ' ' + trees_file_name
subprocess.call(command.split())
plots_dir = treedir + str(i) + model_dir + 'quadrant_plots'
treedir_full = treedir + str(i) + model_dir
if not os.path.exists(plots_dir):
os.mkdir(plots_dir)
plotit = plot_topos(tree + str(i), treedir_full, model, topology_num)
plotit.makeScript()
plotit.makePlots()
else:
print ("Plots for quadrants already made - skipping for " + tree + str(i))
#if not os.path.exists(treedir + str(i) + 'quadrant_plots/' + tree + str(i) + '_' + model + '_' + "logplots.R"):
#orderByLogMap(tree + str(i), treedir + str(i), model)
#plotlog = plot_orderedlog(tree + str(i), treedir_full, model)
#plotlog.makeScript()
#plotlog.makePlots()
for j in range(len(models)):
model = models[j]
for i in range(1,2):
treedir = "c:/seqgen/" + tree
model_dir = "/" + model + "/"
dist_matrix_file = tree + str(i) + "_" + model + "_" + "dist_matrix.txt"
# MDS (2D):
if not os.path.exists(treedir + str(i) + model_dir + tree + str(i) + "_2D.r"):
temp = make_rMDSscript(tree + str(i), treedir + str(i) + model_dir, dist_matrix_file, model + ": sequence # " + str(i) + " under MDS", aspect_ratio=1, mean=False, majority=False)
temp.plot_MDS()
os.chdir(treedir + str(i) + model_dir)
command = 'C:\\Rstuff\\R-3.2.0\\bin\\Rscript.exe ' + treedir + str(i) + model_dir + tree + str(i) + "_2D.r"
call(command.split())
else:
print("R script and plots already made for " + tree + str(i) + " under model " + model + " - skipping")
# MDS (3D):
if not os.path.exists(treedir + str(i) + model_dir + tree + str(i) + "_3D.r"):
temp = make_rMDSscript(tree + str(i), treedir + str(i) + model_dir, dist_matrix_file, model + ": sequence # " + str(i) + " under MDS", aspect_ratio=1, mean=False, majority=False)
temp.plot_MDS(3)
os.chdir(treedir + str(i) + model_dir)
command = 'C:\\Rstuff\\R-3.2.0\\bin\\Rscript.exe ' + treedir + str(i) + model_dir + tree + str(i) + "_3D.r"
call(command.split())
else:
print("R script and plots already made for " + tree + str(i) + " under model " + model + " - skipping")
# Logmap:#
analysis_jar = "analysis_140702.jar"
shutil.copyfile('c:\\seqgen\\jars\\' + analysis_jar, treedir + str(i) + model_dir + analysis_jar)
#models = ["bayes","raxml","BEAST","phyml"]
for j in range(len(models)):
model = models[j]
for i in range (1,2):
analysis_version = "analysis_140702.jar"
treedir = 'c:/seqgen/' + tree
model_dir = '/' + model + '/'
topo_dir = treedir + str(i) + model_dir + 'split_by_topology'
trees_file_name = treedir + str(i) + model_dir + tree + str(i) + "_" + model + "_" + "treeout.txt"
trees_topo_file_name = treedir + str(i) + model_dir + tree + str(i) + "_" + model + "_tree_topo.txt"
topo_prefix = topo_dir + "/topo.txt"
if not os.path.exists(trees_topo_file_name):
os.chdir(treedir + str(i) + model_dir)
command = "java -jar " + analysis_version + " -a topology_count -o " + trees_topo_file_name + " " + trees_file_name
subprocess.call(command.split())
else:
print "File %s already exists - skipping generating topology info about all means \n" % trees_topo_file_name
if not os.path.exists(topo_dir):
os.mkdir(topo_dir)
topology_file_splitter.makeFiles(trees_file_name,trees_topo_file_name,topo_prefix)
else:
print "Directory %s already exists - skipping splitting the means by topology \n" % topo_dir
centre_dir = treedir + str(i) + model_dir + 'centres'
centre_prefix = centre_dir + "/centre_"
topology_num = 0
if not os.path.exists(centre_dir):
os.mkdir(centre_dir)
f = open(trees_topo_file_name)
topNum = 0
# Extract the number of topologies from the topology file
for line in f:
tempStr = line
if (tempStr[0:3] != "Raw"):
continue
else:
trimStr = tempStr.lstrip("Raw topology counts: ").split()
topNum = len(trimStr)
topology_num = topNum
break
f.close()
for n in xrange(1,topNum+1):
testout = centre_prefix + str(n)
tree_file_name = topo_dir + '/topo' + str(n) + '.txt'
f = open(tree_file_name,'r')
temptree = f.readline()
if (temptree == "(((E:.1,D:.1):.1,C:.11):.01,B:.1,A:.1);\n"):
temptree = "(((E:0.1,D:0.1):0.1,C:0.11):0.01,B:0.1,A:0.01);\n"
if (model =="BEAST"):
m = re.match(r'(.*?\):)[0-9]+[.][0-9]+(.*?\):)[0-9]+[.][0-9]+(.*?\):)[0-9]+[.][0-9]+(.+;)',temptree)
else:
m = re.match(r'(.*?\):)[0-9]+[.][0-9]+(.*?\):)[0-9]+[.][0-9]+(.+;)',temptree)
if not m:
print("Error: can't change interior edges lengths")
exit
if (model =="BEAST"):
temptree = m.group(1) + '0.000000001' + m.group(2) + '0.000000001' + m.group(3)