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cov_plot.py
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cov_plot.py
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### Boas Pucker ###
### bpucker@cebitec.uni-bielefeld.de ###
### v0.15 ###
### reference: https://doi.org/10.3390/genes10090671 ####
__usage__ = """
python cov_plot.py
--in <FULL_PATH_TO_COVERAGE_FILE>
--out <FULL_PATH_TO_OUTPUT_FILE>
--res <RESOLUTION, WINDOW_SIZE_FOR_COVERAGE_CALCULATION>
--sat <SATURATION, CUTOFF_FOR_MAX_COVERAGE_VALUE>
--cov <AVERAGE_COVERAGE>
--name <NAME>
"""
import sys, os
import matplotlib.pyplot as plt
import numpy as np
# --- end of imports --- #
def load_cov( cov_file ):
"""! @brief load all information from coverage file """
cov = {}
with open( cov_file, "r" ) as f:
line = f.readline()
header = line.split('\t')[0]
tmp = []
while line:
parts = line.strip().split('\t')
if parts[0] != header:
cov.update( { header: tmp } )
header = parts[0]
tmp = []
tmp.append( float( parts[-1] ) )
line = f.readline()
cov.update( { header: tmp } )
return cov
def generate_plot( cov, out_file, resolution, saturation, name ):
"""! @brief generate figure """
fig, ax = plt.subplots( figsize=( 10, 7 ) )
ymax = 5 #len( cov.keys() )+1
max_value = 0
collected_values = {}
# --- generate list for plotting --- #
for idx, key in enumerate( sorted( cov.keys() ) ):
y = ymax-idx-1
x = []
blocks = [ cov[ key ] [ i : i + resolution ] for i in xrange( 0, len( cov[ key ] ), resolution ) ]
for block in blocks:
x.append( min( [ np.mean( block ), saturation ] ) )
max_value = max( [ max_value, max( x ) ] )
collected_values.update( { key: x } )
# --- plot values --- #
max_value = float( min( [ saturation, max_value ] ) )
for idx, key in enumerate( sorted( cov.keys() )[:5] ):
y = ymax - ( idx*1.3 )
x = []
for each in collected_values[ key ]:
x.append( y + min( [ 1, ( each / max_value ) ] ) )
ax.scatter( np.arange( 0, len( x ), 1 ), x, s=1, color="lime" )
ax.text( 1, y, key )
ax.plot( [ 0, len( x ) ], [ y+( 0 / max_value ), y+( 0 / max_value ) ], color="black" , linewidth=0.1)
#ax.plot( [ 0, len( x ) ], [ y+( 10 / max_value ), y+( 10 / max_value ) ], color="black" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 20 / max_value ), y+( 20 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 30 / max_value ), y+( 30 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 40 / max_value ), y+( 40 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 50 / max_value ), y+( 50 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 60 / max_value ), y+( 60 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 70 / max_value ), y+( 70 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 80 / max_value ), y+( 80 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 90 / max_value ), y+( 90 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, len( x ) ], [ y+( 100 / max_value ), y+( 100 / max_value ) ], color="grey" , linewidth=0.1)
ax.plot( [ 0, 0 ], [ y, y+1 ], color="black", linewidth=1, markersize=1 )
ax.text( 0, y+1, str( int( max_value ) ), ha="right", fontsize=5 )
ax.text( 0, y+0.5, str( int( max_value / 2 ) ), ha="right", fontsize=5 )
ax.text( 0, y, "0", ha="right", fontsize=5 )
ax.set_xlabel( "position on chromosome [ Mbp ]" )
ax.set_ylabel( "coverage" )
ax.set_xlim( 0, 30500 )
ax.set_title( name )
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.get_yaxis().set_ticks([])
ax.yaxis.labelpad = 10
ax.xaxis.set_ticks( np.arange( 0, 31000, 1000 ) )
labels = map( str, np.arange( 0, 31, 1 ) )
ax.set_xticklabels( labels ) #[ "0", "5", "10", "15", "20", "25", "30" ]
plt.subplots_adjust( left=0.03, right=0.999, top=0.95, bottom=0.1 )
fig.savefig( out_file, dpi=300 )
def generate_hist( cov_values, outputfile, saturation, resolution, title ):
"""! @brief generate coverage histogram """
values = []
blocks = [ cov_values[ i : i + resolution ] for i in xrange( 0, len( cov_values ), resolution ) ]
for block in blocks:
values.append( min( [ np.mean( block ), saturation ] ) )
fig, ax = plt.subplots()
ax.set_title( title )
ax.hist( values, bins=300, color="lime" )
ax.set_xlim( 0, 300 )
ax.set_xlabel( "sequencing coverage depth" )
ax.set_ylabel( "number of positions" )
fig.savefig( outputfile, dpi=300 )
def main( arguments ):
"""! @brief runs everything """
cov_file = arguments[ arguments.index( '--in' ) + 1 ]
output_folder = arguments[ arguments.index( '--out' ) + 1 ]
if not os.path.exists( output_folder ):
os.makedirs( output_folder )
if '--res' in arguments:
resolution = int( arguments[ arguments.index( '--res' ) + 1 ] )
else:
resolution = 1000
if '--sat' in arguments:
saturation = int( arguments[ arguments.index( '--sat' ) + 1 ] )
else:
saturation = 100
if '--name' in arguments:
name = arguments[ arguments.index( '--name' ) + 1 ]
else:
name = ""
cov = load_cov( cov_file )
# --- generate coverage histograms per chromosome --- #
for key in cov.keys():
outputfile = output_folder + key + ".pdf"
generate_hist( cov[ key ], outputfile, saturation, resolution, key )
# --- generate per chromosome position coveage plot --- #
out_file = output_folder + name + ".pdf"
generate_plot( cov, out_file, resolution, saturation, name )
if '--in' in sys.argv and '--out' in sys.argv:
main( sys.argv )
else:
sys.exit( __usage__ )