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gcPlots.py
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gcPlots.py
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###############################################################################
#
# gcPlots.py - Create a GC histogram and delta-GC plot.
#
###############################################################################
# #
# This program is free software: you can redistribute it and/or modify #
# it under the terms of the GNU General Public License as published by #
# the Free Software Foundation, either version 3 of the License, or #
# (at your option) any later version. #
# #
# This program is distributed in the hope that it will be useful, #
# but WITHOUT ANY WARRANTY; without even the implied warranty of #
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the #
# GNU General Public License for more details. #
# #
# You should have received a copy of the GNU General Public License #
# along with this program. If not, see <http://www.gnu.org/licenses/>. #
# #
###############################################################################
import numpy as np
from checkm.plot.AbstractPlot import AbstractPlot
from checkm.binTools import BinTools
from checkm.util.seqUtils import readFasta, baseCount
from checkm.common import findNearest, readDistribution
class GcPlots(AbstractPlot):
def __init__(self, options):
AbstractPlot.__init__(self, options)
def plot(self, fastaFile, distributionsToPlot):
# Set size of figure
self.fig.clear()
self.fig.set_size_inches(self.options.width, self.options.height)
axesHist = self.fig.add_subplot(121)
axesDeltaGC = self.fig.add_subplot(122)
self.plotOnAxes(fastaFile, distributionsToPlot, axesHist, axesDeltaGC)
self.fig.tight_layout(pad=1, w_pad=1)
self.draw()
def plotOnAxes(self, fastaFile, distributionsToPlot, axesHist, axesDeltaGC):
# Read reference distributions from file
dist = readDistribution('gc_dist')
# get GC for windows
seqs = readFasta(fastaFile)
data = []
seqLens = []
for _, seq in seqs.items():
start = 0
end = self.options.gc_window_size
seqLen = len(seq)
seqLens.append(seqLen)
while(end < seqLen):
a, c, g, t = baseCount(seq[start:end])
try:
data.append(float(g + c) / (a + c + g + t))
except:
# it is possible to reach a long stretch of
# N's that causes a division by zero error
pass
start = end
end += self.options.gc_window_size
if len(data) == 0:
axesHist.set_xlabel('[Error] No seqs >= %d, the specified window size' % self.options.gc_window_size)
return
# Histogram plot
bins = [0.0]
binWidth = self.options.gc_bin_width
binEnd = binWidth
while binEnd <= 1.0:
bins.append(binEnd)
binEnd += binWidth
axesHist.hist(data, bins=bins, density=True, color=(0.5, 0.5, 0.5))
axesHist.set_xlabel('% GC')
axesHist.set_ylabel('% windows (' + str(self.options.gc_window_size) + ' bp)')
# Prettify plot
for a in axesHist.yaxis.majorTicks:
a.tick1On = True
a.tick2On = False
for a in axesHist.xaxis.majorTicks:
a.tick1On = True
a.tick2On = False
for line in axesHist.yaxis.get_ticklines():
line.set_color(self.axesColour)
for line in axesHist.xaxis.get_ticklines():
line.set_color(self.axesColour)
for loc, spine in axesHist.spines.items():
if loc in ['right', 'top']:
spine.set_color('none')
else:
spine.set_color(self.axesColour)
# get GC bin statistics
binTools = BinTools()
meanGC, deltaGCs, _ = binTools.gcDist(seqs)
# Delta-GC vs Sequence length plot
axesDeltaGC.scatter(deltaGCs, seqLens, c=abs(deltaGCs), s=10, lw=0.5, cmap='gray_r')
axesDeltaGC.set_xlabel(r'$\Delta$ GC (mean GC = %.1f%%)' % (meanGC * 100))
axesDeltaGC.set_ylabel('Sequence length (kbp)')
_, yMaxSeqs = axesDeltaGC.get_ylim()
xMinSeqs, xMaxSeqs = axesDeltaGC.get_xlim()
# plot reference distributions
for distToPlot in distributionsToPlot:
closestGC = findNearest(np.array(list(dist.keys())), meanGC)
# find closest distribution values
sampleSeqLen = list(dist[closestGC].keys())[0]
d = dist[closestGC][sampleSeqLen]
gcLowerBoundKey = findNearest(list(d.keys()), (100 - distToPlot) / 2.0)
gcUpperBoundKey = findNearest(list(d.keys()), (100 + distToPlot) / 2.0)
xL = []
xU = []
y = []
for windowSize in dist[closestGC]:
xL.append(dist[closestGC][windowSize][gcLowerBoundKey])
xU.append(dist[closestGC][windowSize][gcUpperBoundKey])
y.append(windowSize)
# sort by y-values
sortIndexY = np.argsort(y)
xL = np.array(xL)[sortIndexY]
xU = np.array(xU)[sortIndexY]
y = np.array(y)[sortIndexY]
axesDeltaGC.plot(xL, y, 'r--', lw=0.5, zorder=0)
axesDeltaGC.plot(xU, y, 'r--', lw=0.5, zorder=0)
# ensure y-axis include zero and covers all sequences
axesDeltaGC.set_ylim([0, yMaxSeqs])
# ensure x-axis is set appropriately for sequences
axesDeltaGC.set_xlim([xMinSeqs, xMaxSeqs])
# draw vertical line at x=0
axesDeltaGC.vlines(0, 0, yMaxSeqs, linestyle='dashed', color=self.axesColour, zorder=0)
# Change sequence lengths from bp to kbp
yticks = axesDeltaGC.get_yticks()
kbpLabels = []
for seqLen in yticks:
label = '%.1f' % (float(seqLen) / 1000)
label = label.replace('.0', '') # remove trailing zero
kbpLabels.append(label)
axesDeltaGC.set_yticklabels(kbpLabels)
# Prettify plot
for a in axesDeltaGC.yaxis.majorTicks:
a.tick1On = True
a.tick2On = False
for a in axesDeltaGC.xaxis.majorTicks:
a.tick1On = True
a.tick2On = False
for line in axesDeltaGC.yaxis.get_ticklines():
line.set_color(self.axesColour)
for line in axesDeltaGC.xaxis.get_ticklines():
line.set_color(self.axesColour)
for loc, spine in axesDeltaGC.spines.items():
if loc in ['right', 'top']:
spine.set_color('none')
else:
spine.set_color(self.axesColour)