Added DAG plot to gobrowser module and smokers workflow.
This commit is contained in:
parent
155dfada5c
commit
7ea87e646a
|
|
@ -2,10 +2,14 @@
|
|||
import gtk
|
||||
from fluents import dataset, logger, plots, workflow, fluents, project
|
||||
import geneontology
|
||||
from matplotlib.nxutils import points_inside_poly
|
||||
import matplotlib
|
||||
#from scipy import array, randn, log, ones, zeros
|
||||
from scipy import *
|
||||
from numpy import matlib
|
||||
import networkx
|
||||
import re
|
||||
import rpy
|
||||
|
||||
EVIDENCE_CODES=[('IMP', 'Inferred from mutant phenotype'),
|
||||
('IGI', 'Inferred from genetic interaction'),
|
||||
|
|
@ -449,6 +453,47 @@ class TTestFunction(workflow.Function):
|
|||
return options
|
||||
|
||||
|
||||
class PlotDagFunction(workflow.Function):
|
||||
def __init__(self):
|
||||
workflow.Function.__init__(self, 'go-dag', 'Build DAG')
|
||||
|
||||
def run(self, selection):
|
||||
g = self.get_network(list(selection['go-terms']))
|
||||
# print g.edges()
|
||||
ds = dataset.GraphDataset(networkx.adj_matrix(g),
|
||||
[('go-terms', g.nodes()), ('_go-terms', g.nodes())],
|
||||
name="DAG")
|
||||
return [DagPlot(g)]
|
||||
|
||||
def get_network(self, terms, subtree='bp'):
|
||||
"""Returns a DAG connecting the given terms by including their parents
|
||||
up to the level needed to connect them. The subtree parameter is one of
|
||||
mf - molecular function
|
||||
bp - biological process
|
||||
cc - cellular component"""
|
||||
|
||||
rpy.r.library("GOstats")
|
||||
|
||||
if subtree == 'mf':
|
||||
subtree_r = rpy.r.GOMFPARENTS
|
||||
elif subtree == 'bp':
|
||||
subtree_r = rpy.r.GOBPPARENTS
|
||||
elif subtree == 'cc':
|
||||
subtree_r = rpy.r.GOCCPARENTS
|
||||
else:
|
||||
raise Exception("Unknown subtree. Use mf, bp or cc.")
|
||||
|
||||
g = rpy.r.GOGraph(terms, subtree_r)
|
||||
edges = rpy.r.edges(g)
|
||||
|
||||
nxgraph = networkx.DiGraph()
|
||||
for child, d in edges.items():
|
||||
for parent in d.keys():
|
||||
nxgraph.add_edge(parent, child)
|
||||
|
||||
return nxgraph
|
||||
|
||||
|
||||
class TTestOptions(workflow.Options):
|
||||
|
||||
def __init__(self):
|
||||
|
|
@ -473,7 +518,6 @@ class GOWeightOptions(workflow.Options):
|
|||
self['similarity_threshold'] = 0.0
|
||||
self['rank_threshold'] = 0.0
|
||||
|
||||
|
||||
class ProbabilityHistogramPlot(plots.HistogramPlot):
|
||||
def __init__(self, ds):
|
||||
plots.HistogramPlot.__init__(self, ds, name="Confidence", bins=50)
|
||||
|
|
@ -486,3 +530,129 @@ class VolcanoPlot(plots.ScatterPlot):
|
|||
name="Volcano plot",
|
||||
sel_dim_2='_p', **kw)
|
||||
|
||||
|
||||
class DagPlot(plots.Plot):
|
||||
def __init__(self, graph, dim='go-terms', pos=None, nodecolor='b', nodesize=40,
|
||||
with_labels=False, name='DAG Plot'):
|
||||
|
||||
plots.Plot.__init__(self, name)
|
||||
self.nodes = graph.nodes()
|
||||
self.graph = graph
|
||||
self._pos = pos
|
||||
self._nodesize = nodesize
|
||||
self._nodecolor = nodecolor
|
||||
self._with_labels = with_labels
|
||||
|
||||
self.current_dim = dim
|
||||
|
||||
if not self._pos:
|
||||
self._pos = self._calc_pos(graph)
|
||||
self._xy = asarray([self._pos[node] for node in self.nodes])
|
||||
self.xaxis_data = self._xy[:,0]
|
||||
self.yaxis_data = self._xy[:,1]
|
||||
|
||||
# Initial draw
|
||||
self.default_props = {'nodesize' : 50,
|
||||
'nodecolor' : 'blue',
|
||||
'edge_color' : 'gray',
|
||||
'edge_color_selected' : 'red'}
|
||||
self.node_collection = None
|
||||
self.edge_collection = None
|
||||
self.node_labels = None
|
||||
lw = zeros(self.xaxis_data.shape)
|
||||
self.node_collection = self.axes.scatter(self.xaxis_data, self.yaxis_data,
|
||||
s=self._nodesize,
|
||||
c=self._nodecolor,
|
||||
linewidth=lw,
|
||||
zorder=3)
|
||||
self._mappable = self.node_collection
|
||||
|
||||
# selected nodes is a transparent graph that adjust node-edge visibility
|
||||
# according to the current selection needed to get get the selected
|
||||
# nodes 'on top' as zorder may not be defined individually
|
||||
self.selected_nodes = self.axes.scatter(self.xaxis_data,
|
||||
self.yaxis_data,
|
||||
s=self._nodesize,
|
||||
c=self._nodecolor,
|
||||
edgecolor='r',
|
||||
linewidth=lw,
|
||||
zorder=4,
|
||||
alpha=0)
|
||||
|
||||
edge_color = self.default_props['edge_color']
|
||||
self.edge_collection = networkx.draw_networkx_edges(self.graph,
|
||||
self._pos,
|
||||
ax=self.axes,
|
||||
edge_color=edge_color)
|
||||
# edge color rgba-arrays
|
||||
self._edge_color_rgba = matlib.repmat(plots.ColorConverter().to_rgba(edge_color),
|
||||
self.graph.number_of_edges(),1)
|
||||
self._edge_color_selected = plots.ColorConverter().to_rgba(self.default_props['edge_color_selected'])
|
||||
if self._with_labels:
|
||||
self.node_labels = networkx.draw_networkx_labels(self.graph,
|
||||
self._pos,
|
||||
ax=self.axes)
|
||||
|
||||
# remove axes, frame and grid
|
||||
self.axes.set_xticks([])
|
||||
self.axes.set_yticks([])
|
||||
self.axes.grid(False)
|
||||
self.axes.set_frame_on(False)
|
||||
self.fig.subplots_adjust(left=0, right=1, bottom=0, top=1)
|
||||
|
||||
def _calc_pos(self, graph):
|
||||
"""Calculates position for graph nodes."""
|
||||
gv_graph = networkx.DiGraph()
|
||||
for start, end in graph.edges():
|
||||
gv_graph.add_edge(start.replace('GO:', ''), end.replace('GO:', ''))
|
||||
|
||||
pos_gv = networkx.pygraphviz_layout(gv_graph, prog="dot")
|
||||
pos = {}
|
||||
for k, v in pos_gv.items():
|
||||
if k != "all":
|
||||
pos["GO:%s" % k] = v
|
||||
else:
|
||||
pos[k] = v
|
||||
return pos
|
||||
|
||||
def rectangle_select_callback(self, x1, y1, x2, y2, key):
|
||||
ydata = self.yaxis_data
|
||||
xdata = self.xaxis_data
|
||||
|
||||
# find indices of selected area
|
||||
if x1>x2:
|
||||
x1, x2 = x2, x1
|
||||
if y1>y2:
|
||||
y1, y2 = y2, y1
|
||||
assert x1<=x2
|
||||
assert y1<=y2
|
||||
|
||||
index = nonzero((xdata>x1) & (xdata<x2) & (ydata>y1) & (ydata<y2))[0]
|
||||
ids = [self.nodes[i] for i in index]
|
||||
ids = self.update_selection(ids, key)
|
||||
self.selection_listener(self.current_dim, ids)
|
||||
|
||||
def lasso_select_callback(self, verts, key=None):
|
||||
xys = c_[self.xaxis_data[:,newaxis], self.yaxis_data[:,newaxis]]
|
||||
index = nonzero(points_inside_poly(xys, verts))[0]
|
||||
ids = [self.nodes[i] for i in index]
|
||||
ids = self.update_selection(ids, key)
|
||||
self.selection_listener(self.current_dim, ids)
|
||||
|
||||
def set_current_selection(self, selection):
|
||||
linewidth = zeros(self.xaxis_data.shape)
|
||||
edge_color_rgba = self._edge_color_rgba.copy()
|
||||
index = [i for i in range(len(self.nodes)) if self.nodes[i] in selection[self.current_dim]]
|
||||
if len(index) > 0:
|
||||
linewidth[index] = 2
|
||||
idents = selection[self.current_dim]
|
||||
edge_index = [i for i,edge in enumerate(self.graph.edges()) if (edge[0] in idents and edge[1] in idents)]
|
||||
if len(edge_index)>0:
|
||||
for i in edge_index:
|
||||
edge_color_rgba[i,:] = self._edge_color_selected
|
||||
self._A = None
|
||||
|
||||
self.edge_collection._colors = edge_color_rgba
|
||||
self.selected_nodes.set_linewidth(linewidth)
|
||||
self.canvas.draw()
|
||||
|
||||
|
|
|
|||
|
|
@ -55,6 +55,7 @@ class SmallTestWorkflow(workflow.Workflow):
|
|||
go.add_function(gobrowser.GOWeightFunction())
|
||||
go.add_function(gobrowser.DistanceToSelectionFunction())
|
||||
go.add_function(gobrowser.TTestFunction())
|
||||
go.add_function(gobrowser.PlotDagFunction())
|
||||
self.add_stage(go)
|
||||
|
||||
# EXTRA PLOTS
|
||||
|
|
|
|||
Reference in New Issue