def heatmap(self,
conditions=None,
identifiers=None,
transform=None,
low="green",
mid="yellow",
high="blue",
width=800,
height=None,
id_map=None):
id_map = {} if id_map is None else id_map
identifiers = self.identifiers if identifiers is None else identifiers
conditions = self.conditions if conditions is None else conditions
data = self.data_frame[conditions]
data['y'] = [id_map.get(i, i) for i in identifiers]
data = melt(data, id_vars=['y'], var_name='x')
if transform:
data['value'] = data.values.apply(transform)
heatmap = plotting.heatmap(data,
y='y',
x='x',
values='value',
width=width,
height=height,
max_color=high,
min_color=low,
mid_color=mid,
title='Expression profile heatmap')
plotting.display(heatmap)
return heatmap
def histogram(self,
conditions=None,
transform=None,
filter=None,
bins=None,
width=800,
height=None,
palette='Spectral'):
if conditions is None:
conditions = self.conditions
data = melt(self.data_frame[conditions], var_name='condition')
if filter:
data = data.query(filter)
if transform:
data['value'] = data['value'].apply(transform)
hist = plotting.histogram(data,
values='value',
groups='condition',
bins=bins,
width=width,
height=height,
palette=palette,
title="Histogram of expression values",
legend=True)
plotting.display(hist)
return hist
def scatter(self, condition1=None, condition2=None, transform=float, width=800, height=None, color="#AFDCEC"):
if len(self.conditions) <= 1:
raise AssertionError("Cannot build a scatter with only one condition")
if condition1 is None:
condition1 = self.conditions[0]
elif isinstance(condition1, int):
condition1 = self.conditions[condition1]
if condition2 is None:
condition2 = self.conditions[1]
elif isinstance(condition2, int):
condition2 = self.conditions[condition2]
if transform:
data = self.data_frame.applymap(transform)
else:
data = self.data_frame
data = data.reset_index()
scatter = plotting.scatter(data, x=condition1, y=condition2, width=width, height=height,
color=color, label='index',
title="Expression values %s vs. %s" % (condition1, condition2),
xaxis_label="Expression %s" % condition1,
yaxis_label="Expression %s" % condition2)
plotting.display(scatter)
return scatter
def histogram(self, transform=float, bins=100, width=800, height=None, palette='Spectral'):
data = melt(self.data_frame, var_name='condition')
data['value'] = data['value'].apply(transform)
hist = plotting.histogram(data, values='value', groups='condition', bins=bins,
width=width, height=height, palette=palette,
title="Histogram of expression values", legend=True)
plotting.display(hist)
return hist
def boxplot(self, conditions=None, transform=None, width=800, height=None, palette='Spectral'):
if conditions is None:
conditions = self.conditions
data = melt(self.data_frame[conditions], var_name='condition')
if transform:
data['value'] = data['value'].apply(transform)
hist = plotting.boxplot(data, values='value', groups='condition', width=width, height=height, palette=palette,
title="Box plot of expression values", legend=True)
plotting.display(hist)
return hist
def heatmap(self, conditions=None, identifiers=None, transform=float, low="green", mid="yellow", high="blue",
width=800, height=None, id_map=None):
id_map = {} if id_map is None else id_map
identifiers = self.identifiers if identifiers is None else identifiers
conditions = self.conditions if conditions is None else conditions
data = self.data_frame[conditions]
data['y'] = [id_map.get(i, i) for i in identifiers]
data = melt(data, id_vars=['y'], var_name='x')
heatmap = plotting.heatmap(data, y='y', x='x', values='value', width=width, height=height,
max_color=high, min_color=low, mid_color=mid, title='Expression profile heatmap')
plotting.display(heatmap)
return heatmap
def histogram(self, conditions=None, transform=None, filter=None, bins=None,
width=800, height=None, palette='Spectral'):
if conditions is None:
conditions = self.conditions
data = melt(self.data_frame[conditions], var_name='condition')
if filter:
data = data.query(filter)
if transform:
data['value'] = data['value'].apply(transform)
hist = plotting.histogram(data, values='value', groups='condition', bins=bins,
width=width, height=height, palette=palette,
title="Histogram of expression values", legend=True)
plotting.display(hist)
return hist
