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import rpy2.robjects as robjects
r = robjects.r
from Bio.Align.Applications import MuscleCommandline
import os
import subprocess as sub
fasta_directory = "/home/UNIMELB/hdashnow/resistance_database/by_gene"
# Get the filenames of all files in the input directory "fasta_directory"
files = []
for f in os.listdir(fasta_directory):
if not f.startswith("."):
if f.endswith(".fsa") or f.endswith(".fasta"):
files.append('"'+os.path.join(fasta_directory,f)+'"') # need to surround with " " due to () in filenames
print("Number of input files:", len(files))
# Run muscle on each fasta file to produce an alignment for each
# Save the alignment file names so that they can be used in R ape
for f in files:
outfilename = (f+".aln").replace("(","").replace(")","")
#print outfilename
alignment = MuscleCommandline(input=f, out=outfilename)
#alignment()
r('''
require(ape, quietly=TRUE)
all_files = list.files("/home/UNIMELB/hdashnow/resistance_database/by_gene",
pattern="aln$", full.names=TRUE)
pdf(width=9,height=12,file="trees.pdf")
for (filename in all_files) {
#print(filename)
aln = read.dna(filename, format="fasta")
if (dim(aln)[1] >= 3) {
d = dist(aln)
#print(aln)
tree=nj(d)
plot(tree, cex=0.6)
#print(filename)
min_filename = tail(strsplit(filename,"/")[[1]],1) # This needs to be made robust
#print(min_filename)
gene_name = strsplit(min_filename,"\\\.")[[1]][1]
#print(cluster)
title(paste("Gene: ", gene_name))
#dev.off()
}
}
dev.off()
''')
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