conshomfold 0.1.1

ConsHomfold, which Predicts Global Single RNA Secondary Structures to Consider Sparse Global Pairwise RNA Structural Alignments
Documentation 
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#! /usr/bin/env python

import utils
from Bio import SeqIO
import numpy
import seaborn
from matplotlib import pyplot
import matplotlib
import os
import multiprocessing
import time
import datetime
import shutil
import community
import networkx
node_size = 150
edge_width = 2
label_font_size = 10 
edge_label_font_size = 4 
cmap = pyplot.cm.viridis

def main():
  (current_work_dir_path, asset_dir_path, program_dir_path, conda_program_dir_path) = utils.get_dir_paths()
  image_dir_path = asset_dir_path + "/images"
  if not os.path.exists(image_dir_path):
    os.mkdir(image_dir_path)
  seq_file_path = asset_dir_path + "/sampled_trnas.fa"
  seqs = [rec for rec in SeqIO.parse(seq_file_path, "fasta")]
  seq = seqs[0]
  seq_lens = [len(seq) for seq in seqs]
  seq_len = len(seq)
  max_upp_mat = utils.get_upp_mats(asset_dir_path + "/sampled_trnas/max_upp_mats.dat", seq_lens)[0]
  bpp_mat = utils.get_bpp_mats(asset_dir_path + "/sampled_trnas/bpp_mats.dat", seq_lens)[0]
  bpp_mat_on_ss = utils.get_bpp_mats(asset_dir_path + "/sampled_trnas/bpp_mats_on_ss.dat", seq_lens)[0]
  access_bpp_mat_4_2l = utils.get_bpp_mats(asset_dir_path + "/sampled_trnas/access_bpp_mats_on_2l.dat", seq_lens)[0]
  access_bpp_mat_4_ml = utils.get_bpp_mats(asset_dir_path + "/sampled_trnas/access_bpp_mats_on_ml.dat", seq_lens)[0]
  bpp_mat_4_el = utils.get_bpp_mats(asset_dir_path + "/sampled_trnas/bpp_mats_on_el.dat", seq_lens)[0]
  xlabels = [str(i + 1) if (i + 1) % 20 == 0 else "" for i in range(seq_len)]
  (_, axes) = pyplot.subplots(nrows = 1, ncols = 2, figsize = (12, 6))
  seaborn.heatmap(bpp_mat_on_ss, ax = axes[0], xticklabels = xlabels, yticklabels = xlabels, cbar = False, cmap = cmap, vmin = 0, vmax = 1)
  seaborn.heatmap(bpp_mat, ax = axes[1], xticklabels = xlabels, yticklabels = xlabels, cbar = False, cmap = cmap, vmin = 0, vmax = 1)
  pyplot.savefig(image_dir_path + "/trna_bpp_mat_comparison.eps", bbox_inches = "tight")
  pyplot.clf()
  (_, axes) = pyplot.subplots(nrows = 2, ncols = 2, figsize = (12, 12))
  seaborn.heatmap(access_bpp_mat_4_2l, ax = axes[0][0], xticklabels = xlabels, yticklabels = xlabels, cbar = False, cmap = cmap, vmin = 0, vmax = 1)
  seaborn.heatmap(access_bpp_mat_4_ml, ax = axes[0][1], xticklabels = False, yticklabels = False, cbar = False, cmap = cmap, vmin = 0, vmax = 1)
  seaborn.heatmap(bpp_mat_4_el, ax = axes[1][0], xticklabels = False, yticklabels = False, cbar = False, cmap = cmap, vmin = 0, vmax = 1)
  upp_mat_4_hl = utils.get_upp_mats(asset_dir_path + "/sampled_trnas/upp_mats_on_hl.dat", seq_lens)[0]
  upp_mat_4_2l = utils.get_upp_mats(asset_dir_path + "/sampled_trnas/upp_mats_on_2l.dat", seq_lens)[0]
  upp_mat_4_ml = utils.get_upp_mats(asset_dir_path + "/sampled_trnas/upp_mats_on_ml.dat", seq_lens)[0]
  upp_mat_4_el = utils.get_upp_mats(asset_dir_path + "/sampled_trnas/upp_mats_on_el.dat", seq_lens)[0]
  pyplot.stackplot(range(seq_len), upp_mat_4_hl, upp_mat_4_2l, upp_mat_4_ml, upp_mat_4_el)
  legends = ["Unpairing accessible from 1-loop", "Unpairing accessible from 2-loop", "Unpairing accessible from multi-loop", "Unpairing accessible from external loop"]
  pyplot.legend(legends, loc = "upper right", bbox_to_anchor=(1.05, 1.2))
  pyplot.savefig(image_dir_path + "/trna_prob_dists.eps", bbox_inches = "tight")
  pyplot.clf()
  capr_prof_seqs = utils.get_capr_prof_seqs(asset_dir_path + "/capr_sampled_trnas.dat")
  pyplot.stackplot(range(seq_len), capr_prof_seqs["Hairpin"], capr_prof_seqs["Stem"], capr_prof_seqs["Bulge"], capr_prof_seqs["Internal"], capr_prof_seqs["Multibranch"], capr_prof_seqs["Exterior"])
  legends = ["Unpairing accessible from 1-loop", "Pairing of stem", "Unpairing accessible from bulge loop", "Unpairing accessible from interior loop", "Unpairing accessible from multi-loop", "Unpairing accessible from external loop"]
  pyplot.legend(legends, loc = "upper right", bbox_to_anchor=(1.05, 1.1))
  pyplot.savefig(image_dir_path + "/capr_trna_prob_dists.eps", bbox_inches = "tight")

if __name__ == "__main__":
  main()