def get_tree_style(self): ts = TreeStyle() ts.layout_fn = self.custom_layout ts.show_leaf_name = False ts.draw_guiding_lines = True ts.guiding_lines_type = 0 ts.guiding_lines_color = "#000000" self._treestyle = ts return ts
def run_action_change_style(self, tree, a_data): #print "action change style called.." if tree.tree_style == self._treestyle: ts2 = TreeStyle() ts2.layout_fn = self.custom_layout ts2.show_leaf_name = False ts2.draw_guiding_lines = True ts2.guiding_lines_type = 0 #solid line ts2.guiding_lines_color = a_data tree.tree_style = ts2 self._treestyle = ts2 else: tree.tree_style = self._treestyle
default="pies.svg") args = parser.parse_args() plot_tree, subtrees_dict, subtrees_topids = get_phyparts_nodes( args.species_tree, args.phyparts_root) concord_dict, conflict_dict = get_concord_and_conflict(args.phyparts_root, subtrees_dict, subtrees_topids) phyparts_dist, phyparts_pies = get_pie_chart_data(args.phyparts_root, args.num_genes, concord_dict, conflict_dict) #Plot Pie Chart ts = TreeStyle() ts.show_leaf_name = False ts.layout_fn = phyparts_pie_layout nstyle = NodeStyle() nstyle["size"] = 0 for n in plot_tree.traverse(): n.set_style(nstyle) n.img_style["vt_line_width"] = 0 ts.draw_guiding_lines = True ts.guiding_lines_color = "black" ts.guiding_lines_type = 0 ts.scale = 30 ts.branch_vertical_margin = 10 plot_tree.convert_to_ultrametric() my_svg = plot_tree.render(args.svg_name, tree_style=ts, w=595)
def plot_tree_barplot(tree_file, taxon2value_list_barplot, header_list, taxon2set2value_heatmap=False, header_list2=False, column_scale=True, general_max=False, barplot2percentage=False, taxon2mlst=False): ''' display one or more barplot :param tree_file: :param taxon2value_list: :param exclude_outgroup: :param bw_scale: :param barplot2percentage: list of bool to indicates if the number are percentages and the range should be set to 0-100 :return: ''' import matplotlib.cm as cm from matplotlib.colors import rgb2hex import matplotlib as mpl if taxon2mlst: mlst_list = list(set(taxon2mlst.values())) mlst2color = dict(zip(mlst_list, get_spaced_colors(len(mlst_list)))) mlst2color['-'] = 'white' if isinstance(tree_file, Tree): t1 = tree_file else: t1 = Tree(tree_file) # Calculate the midpoint node R = t1.get_midpoint_outgroup() # and set it as tree outgroup t1.set_outgroup(R) tss = TreeStyle() value = 1 tss.draw_guiding_lines = True tss.guiding_lines_color = "gray" tss.show_leaf_name = False if column_scale and header_list2: import matplotlib.cm as cm from matplotlib.colors import rgb2hex import matplotlib as mpl column2scale = {} for column in header_list2: values = taxon2set2value_heatmap[column].values() norm = mpl.colors.Normalize(vmin=min(values), vmax=max(values)) cmap = cm.OrRd m = cm.ScalarMappable(norm=norm, cmap=cmap) column2scale[column] = m cmap = cm.YlGnBu #YlOrRd#OrRd values_lists = taxon2value_list_barplot.values() scale_list = [] max_value_list = [] for n, header in enumerate(header_list): #print 'scale', n, header data = [float(i[n]) for i in values_lists] if barplot2percentage is False: max_value = max(data) #3424182# min_value = min(data) #48.23 else: if barplot2percentage[n] is True: max_value = 100 min_value = 0 else: max_value = max(data) #3424182# min_value = min(data) #48.23 norm = mpl.colors.Normalize(vmin=min_value, vmax=max_value) m1 = cm.ScalarMappable(norm=norm, cmap=cmap) scale_list.append(m1) if not general_max: max_value_list.append(float(max_value)) else: max_value_list.append(general_max) for i, lf in enumerate(t1.iter_leaves()): #if taxon2description[lf.name] == 'Pirellula staleyi DSM 6068': # lf.name = 'Pirellula staleyi DSM 6068' # continue if i == 0: col_add = 0 if taxon2mlst: header_list = ['MLST'] + header_list for col, header in enumerate(header_list): #lf.add_face(n, column, position="aligned") n = TextFace(' ') n.margin_top = 1 n.margin_right = 2 n.margin_left = 2 n.margin_bottom = 1 n.rotation = 90 n.inner_background.color = "white" n.opacity = 1. n.hz_align = 2 n.vt_align = 2 tss.aligned_header.add_face(n, col_add + 1) n = TextFace('%s' % header) n.margin_top = 1 n.margin_right = 2 n.margin_left = 2 n.margin_bottom = 2 n.rotation = 270 n.inner_background.color = "white" n.opacity = 1. n.hz_align = 2 n.vt_align = 1 tss.aligned_header.add_face(n, col_add) col_add += 2 if header_list2: for col, header in enumerate(header_list2): n = TextFace('%s' % header) n.margin_top = 1 n.margin_right = 20 n.margin_left = 2 n.margin_bottom = 1 n.rotation = 270 n.hz_align = 2 n.vt_align = 2 n.inner_background.color = "white" n.opacity = 1. tss.aligned_header.add_face(n, col + col_add) if taxon2mlst: try: #if lf.name in leaf2mlst or int(lf.name) in leaf2mlst: n = TextFace(' %s ' % taxon2mlst[int(lf.name)]) n.inner_background.color = 'white' m = TextFace(' ') m.inner_background.color = mlst2color[taxon2mlst[int(lf.name)]] except: n = TextFace(' na ') n.inner_background.color = "grey" m = TextFace(' ') m.inner_background.color = "white" n.opacity = 1. n.margin_top = 2 n.margin_right = 2 n.margin_left = 0 n.margin_bottom = 2 m.margin_top = 2 m.margin_right = 0 m.margin_left = 2 m.margin_bottom = 2 lf.add_face(m, 0, position="aligned") lf.add_face(n, 1, position="aligned") col_add = 2 else: col_add = 0 try: val_list = taxon2value_list_barplot[lf.name] except: if not taxon2mlst: val_list = ['na'] * len(header_list) else: val_list = ['na'] * (len(header_list) - 1) for col, value in enumerate(val_list): # show value itself try: n = TextFace(' %s ' % str(value)) except: n = TextFace(' %s ' % str(value)) n.margin_top = 1 n.margin_right = 5 n.margin_left = 10 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, col_add, position="aligned") # show bar try: color = rgb2hex(scale_list[col].to_rgba(float(value))) except: color = 'white' try: percentage = (value / max_value_list[col]) * 100 #percentage = value except: percentage = 0 try: maximum_bar = ( (max_value_list[col] - value) / max_value_list[col]) * 100 except: maximum_bar = 0 #maximum_bar = 100-percentage b = StackedBarFace([percentage, maximum_bar], width=100, height=10, colors=[color, "white"]) b.rotation = 0 b.inner_border.color = "grey" b.inner_border.width = 0 b.margin_right = 15 b.margin_left = 0 lf.add_face(b, col_add + 1, position="aligned") col_add += 2 if taxon2set2value_heatmap: shift = col + col_add + 1 i = 0 for col, col_name in enumerate(header_list2): try: value = taxon2set2value_heatmap[col_name][lf.name] except: try: value = taxon2set2value_heatmap[col_name][int(lf.name)] except: value = 0 if int(value) > 0: if int(value) > 9: n = TextFace(' %i ' % int(value)) else: n = TextFace(' %i ' % int(value)) n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.fgcolor = "white" n.inner_background.color = rgb2hex( column2scale[col_name].to_rgba( float(value))) #"orange" n.opacity = 1. lf.add_face(n, col + col_add, position="aligned") i += 1 else: n = TextFace(' ') #% str(value)) n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, col + col_add, position="aligned") n = TextFace(lf.name, fgcolor="black", fsize=12, fstyle='italic') lf.add_face(n, 0) for n in t1.traverse(): nstyle = NodeStyle() if n.support < 1: nstyle["fgcolor"] = "black" nstyle["size"] = 6 n.set_style(nstyle) else: nstyle["fgcolor"] = "red" nstyle["size"] = 0 n.set_style(nstyle) return t1, tss
def bub_tree(tree, fasta, outfile1, root, types, c_dict, show, size, colours, field1, field2, scale, multiplier, dna): """ :param tree: tree object from ete :param fasta: the fasta file used to make the tree :param outfile1: outfile suffix :param root: sequence name to use as root :param types: tree type: circular (c) or rectangle (r) :param c_dict: dictionary mapping colour to time point (from col_map) :param show: show the tree in a gui (y/n) :param size: scale the terminal nodes by frequency information (y/n) :param colours: if using a matched fasta file, colour the sequence by charge/IUPAC :param field1: the field that contains the size/frequency value :param field2: the field that contains the size/frequency value :param scale: how much to scale the x axis :param multiplier :param dna true/false, is sequence a DNA sequence? :param t_list list of time points :return: None, outputs svg/pdf image of the tree """ if multiplier is None: mult = 500 else: mult = multiplier if dna: dna_prot = 'dna' bg_c = { 'A': 'green', 'C': 'blue', 'G': 'black', 'T': 'red', '-': 'grey', 'X': 'white' } fg_c = { 'A': 'black', 'C': 'black', 'G': 'black', 'T': 'black', '-': 'black', 'X': 'white' } else: dna_prot = 'aa' bg_c = { 'K': '#145AFF', 'R': '#145AFF', 'H': '#8282D2', 'E': '#E60A0A', 'D': '#E60A0A', 'N': '#00DCDC', 'Q': '#00DCDC', 'S': '#FA9600', 'T': '#FA9600', 'L': '#0F820F', 'I': '#0F820F', 'V': '#0F820F', 'Y': '#3232AA', 'F': '#3232AA', 'W': '#B45AB4', 'C': '#E6E600', 'M': '#E6E600', 'A': '#C8C8C8', 'G': '#EBEBEB', 'P': '#DC9682', '-': 'grey', 'X': 'white' } fg_c = { 'K': 'black', 'R': 'black', 'H': 'black', 'E': 'black', 'D': 'black', 'N': 'black', 'Q': 'black', 'S': 'black', 'T': 'black', 'L': 'black', 'I': 'black', 'V': 'black', 'Y': 'black', 'F': 'black', 'W': 'black', 'C': 'black', 'M': 'black', 'A': 'black', 'G': 'black', 'P': 'black', '-': 'grey', 'X': 'white' } if colours == 3: bg_c = None fg_c = None # outfile3 = str(outfile1.replace(".svg", ".nwk")) tstyle = TreeStyle() tstyle.force_topology = False tstyle.mode = types tstyle.scale = scale tstyle.min_leaf_separation = 0 tstyle.optimal_scale_level = 'full' # 'mid' # tstyle.complete_branch_lines_when_necessary = False if types == 'c': tstyle.root_opening_factor = 0.25 tstyle.draw_guiding_lines = False tstyle.guiding_lines_color = 'slateblue' tstyle.show_leaf_name = False tstyle.allow_face_overlap = True tstyle.show_branch_length = False tstyle.show_branch_support = False TreeNode(format=0, support=True) # tnode = TreeNode() if root is not None: tree.set_outgroup(root) # else: # r = tnode.get_midpoint_outgroup() # print("r", r) # tree.set_outgroup(r) time_col = [] for node in tree.traverse(): # node.ladderize() if node.is_leaf() is True: try: name = node.name.split("_") time = name[field2] kind = name[3] # print(name) except: time = 'zero' name = node.name print("Incorrect name format for ", node.name) if size is True: try: s = 20 + float(name[field1]) * mult except: s = 20 print("No frequency information for ", node.name) else: s = 20 colour = c_dict[time] time_col.append((time, colour)) nstyle = NodeStyle() nstyle["fgcolor"] = colour nstyle["size"] = s nstyle["hz_line_width"] = 10 nstyle["vt_line_width"] = 10 nstyle["hz_line_color"] = colour nstyle["vt_line_color"] = 'black' nstyle["hz_line_type"] = 0 nstyle["vt_line_type"] = 0 node.set_style(nstyle) if root is not None and node.name == root: # place holder in case you want to do something with the root leaf print('root is ', node.name) # nstyle["shape"] = "square" # nstyle["fgcolor"] = "black" # nstyle["size"] = s # nstyle["shape"] = "circle" # node.set_style(nstyle) else: nstyle["shape"] = "circle" node.set_style(nstyle) if fasta is not None: seq = fasta[str(node.name)] seqFace = SequenceFace(seq, seqtype=dna_prot, fsize=10, fg_colors=fg_c, bg_colors=bg_c, codon=None, col_w=40, alt_col_w=3, special_col=None, interactive=True) # seqFace = SeqMotifFace(seq=seq, motifs=None, seqtype=dna_prot, gap_format=' ', seq_format='()', scale_factor=20, # height=20, width=50, fgcolor='white', bgcolor='grey', gapcolor='white', ) # seqFace = SeqMotifFace(seq, seq_format="seq", fgcolor=fg_c, bgcolor=bg_c) #interactive=True (tree & node.name).add_face(seqFace, 0, "aligned") else: nstyle = NodeStyle() nstyle["size"] = 0.1 nstyle["hz_line_width"] = 10 nstyle["vt_line_width"] = 10 node.set_style(nstyle) continue tree.ladderize() # tnode.ladderize() legendkey = sorted(set(time_col)) legendkey = [(tp, col) for tp, col in legendkey] # legendkey.insert(0, ('Root', 'black')) legendkey.append(('', 'white')) for tm, clr in legendkey: tstyle.legend.add_face(faces.CircleFace(30, clr), column=0) tstyle.legend.add_face(faces.TextFace('\t' + tm, ftype='Arial', fsize=60, fgcolor='black', tight_text=True), column=1) if show is True: tree.show(tree_style=tstyle) tree.render(outfile1, dpi=600, tree_style=tstyle)
def plot_tree_barplot(tree_file, taxon2mlst, header_list): ''' display one or more barplot :param tree_file: :param taxon2value_list: :param exclude_outgroup: :param bw_scale: :param barplot2percentage: list of bool to indicates if the number are percentages and the range should be set to 0-100 :return: ''' import matplotlib.cm as cm from matplotlib.colors import rgb2hex import matplotlib as mpl mlst_list = list(set(taxon2mlst.values())) mlst2color = dict(zip(mlst_list, get_spaced_colors(len(mlst_list)))) mlst2color['-'] = 'white' if isinstance(tree_file, Tree): t1 = tree_file else: t1 = Tree(tree_file) # Calculate the midpoint node R = t1.get_midpoint_outgroup() # and set it as tree outgroup t1.set_outgroup(R) tss = TreeStyle() value = 1 tss.draw_guiding_lines = True tss.guiding_lines_color = "gray" tss.show_leaf_name = False cmap = cm.YlGnBu #YlOrRd#OrRd scale_list = [] max_value_list = [] for i, lf in enumerate(t1.iter_leaves()): #if taxon2description[lf.name] == 'Pirellula staleyi DSM 6068': # lf.name = 'Pirellula staleyi DSM 6068' # continue if i == 0: # header col_add = 0 #lf.add_face(n, column, position="aligned") n = TextFace('MLST') n.margin_top = 1 n.margin_right = 2 n.margin_left = 2 n.margin_bottom = 1 n.rotation = 90 n.inner_background.color = "white" n.opacity = 1. n.hz_align = 2 n.vt_align = 2 tss.aligned_header.add_face(n, col_add + 1) try: #if lf.name in leaf2mlst or int(lf.name) in leaf2mlst: n = TextFace(' %s ' % taxon2mlst[int(lf.name)]) n.inner_background.color = 'white' m = TextFace(' ') m.inner_background.color = mlst2color[taxon2mlst[int(lf.name)]] except: n = TextFace(' na ') n.inner_background.color = "grey" m = TextFace(' ') m.inner_background.color = "white" n.opacity = 1. n.margin_top = 2 n.margin_right = 2 n.margin_left = 0 n.margin_bottom = 2 m.margin_top = 2 m.margin_right = 0 m.margin_left = 2 m.margin_bottom = 2 lf.add_face(m, 0, position="aligned") lf.add_face(n, 1, position="aligned") n = TextFace(lf.name, fgcolor="black", fsize=12, fstyle='italic') lf.add_face(n, 0) for n in t1.traverse(): nstyle = NodeStyle() if n.support < 1: nstyle["fgcolor"] = "black" nstyle["size"] = 6 n.set_style(nstyle) else: nstyle["fgcolor"] = "red" nstyle["size"] = 0 n.set_style(nstyle) return t1, tss
from ete3 import TreeStyle from ete3 import EvolTree from ete3 import faces tree = EvolTree("data/S_example/measuring_S_tree.nw") tree.link_to_alignment('data/S_example/alignment_S_measuring_evol.fasta') print(tree) print('\n Running free-ratio model with calculation of ancestral sequences...') tree.run_model('fb_anc') #tree.link_to_evol_model('/tmp/ete3-codeml/fb_anc/out', 'fb_anc') I = TreeStyle() I.force_topology = False I.draw_aligned_faces_as_table = True I.draw_guiding_lines = True I.guiding_lines_type = 2 I.guiding_lines_color = "#CCCCCC" for n in sorted(tree.get_descendants() + [tree], key=lambda x: x.node_id): if n.is_leaf(): continue anc_face = faces.SequenceFace(n.sequence, 'aa', fsize=10, bg_colors={}) I.aligned_foot.add_face(anc_face, 1) I.aligned_foot.add_face( faces.TextFace('node_id: #%d ' % (n.node_id), fsize=8), 0) print('display result of bs_anc model, with ancestral amino acid sequences.') tree.show(tree_style=I) print('\nThe End.')
F = faces.TextFace(mynode.name,fsize=20) faces.add_face_to_node(F,mynode,0,position="aligned") #Plot Pie Chart ts = TreeStyle() ts.show_leaf_name = False ts.layout_fn = phyparts_pie_layout nstyle = NodeStyle() nstyle["size"] = 0 for n in plot_tree.traverse(): n.set_style(nstyle) n.img_style["vt_line_width"] = 0 ts.draw_guiding_lines = True ts.guiding_lines_color = "black" ts.guiding_lines_type = 0 ts.scale = 30 ts.branch_vertical_margin = 10 plot_tree.convert_to_ultrametric() plot_tree.ladderize(direction=1) my_svg = plot_tree.render(args.svg_name,tree_style=ts,w=595,dpi=300) if args.show_nodes: node_style = TreeStyle() node_style.show_leaf_name=False node_style.layout_fn = node_text_layout plot_tree.show(tree_style=node_style)
def plot_phylum_counts(NOG_id, rank='phylum', colapse_low_species_counts=4, remove_unlassified=True): ''' 1. get phylum tree 2. foreach species => get phylum 3. build phylum2count dictionnary 3. plot barchart # merge eukaryotes into 5 main clades # merge virus as a single clade ATTENTION: no-rank groups and no-rank species... ''' import MySQLdb import os from chlamdb.biosqldb import manipulate_biosqldb from ete3 import NCBITaxa, Tree, TextFace, TreeStyle, StackedBarFace ncbi = NCBITaxa() sqlpsw = os.environ['SQLPSW'] conn = MySQLdb.connect( host="localhost", # your host, usually localhost user="******", # your username passwd=sqlpsw, # your password db="eggnog") # name of the data base cursor = conn.cursor() sql = 'select * from eggnog.leaf2n_genomes_%s' % rank cursor.execute(sql, ) leaf_taxon2n_species = manipulate_biosqldb.to_dict(cursor.fetchall()) leaf_taxon2n_species_with_domain = get_NOG_taxonomy(NOG_id, rank) sql = 'select phylogeny from eggnog.phylogeny where rank="%s"' % (rank) cursor.execute(sql, ) tree = Tree(cursor.fetchall()[0][0], format=1) sql = 'select * from eggnog.taxid2label_%s' % rank cursor.execute(sql, ) taxon_id2scientific_name_and_rank = manipulate_biosqldb.to_dict( cursor.fetchall()) taxon_id2scientific_name_and_rank = { str(k): v for k, v in taxon_id2scientific_name_and_rank.items() } tss = TreeStyle() tss.draw_guiding_lines = True tss.guiding_lines_color = "blue" keep = [] for lf in tree.iter_leaves(): # n genomes if remove_unlassified: label = taxon_id2scientific_name_and_rank[str(lf.name)][0] if 'unclassified' in label: continue n_genomes = int(leaf_taxon2n_species[lf.name]) if n_genomes > colapse_low_species_counts: keep.append(lf.name) print('number of leaaves:', len(keep)) tree.prune(keep) header_list = ['Rank', 'N genomes', 'N with %s' % NOG_id, 'Percentage'] for col, header in enumerate(header_list): n = TextFace('%s' % (header)) n.margin_top = 0 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.rotation = 270 n.hz_align = 2 n.vt_align = 2 n.inner_background.color = "white" n.opacity = 1. tss.aligned_header.add_face(n, col) for lf in tree.iter_leaves(): # n genomes n_genomes = int(leaf_taxon2n_species[lf.name]) if n_genomes <= colapse_low_species_counts: continue n = TextFace(' %s ' % str(leaf_taxon2n_species[lf.name])) n.margin_top = 1 n.margin_right = 1 n.margin_left = 0 n.margin_bottom = 1 n.fsize = 7 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, 2, position="aligned") # n genomes with domain try: m = TextFace(' %s ' % str(leaf_taxon2n_species_with_domain[lf.name])) except: m = TextFace(' 0 ') m.margin_top = 1 m.margin_right = 1 m.margin_left = 0 m.margin_bottom = 1 m.fsize = 7 m.inner_background.color = "white" m.opacity = 1. lf.add_face(m, 3, position="aligned") # rank ranks = ncbi.get_rank([lf.name]) try: r = ranks[max(ranks.keys())] except: r = '-' n = TextFace(' %s ' % r, fsize=14, fgcolor='red') n.margin_top = 1 n.margin_right = 1 n.margin_left = 0 n.margin_bottom = 1 n.fsize = 7 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, 1, position="aligned") # percent with target domain try: percentage = (float(leaf_taxon2n_species_with_domain[lf.name]) / float(leaf_taxon2n_species[lf.name])) * 100 except: percentage = 0 m = TextFace(' %s ' % str(round(percentage, 2))) m.fsize = 1 m.margin_top = 1 m.margin_right = 1 m.margin_left = 0 m.margin_bottom = 1 m.fsize = 7 m.inner_background.color = "white" m.opacity = 1. lf.add_face(m, 4, position="aligned") b = StackedBarFace([percentage, 100 - percentage], width=100, height=10, colors=["#7fc97f", "white"]) b.rotation = 0 b.inner_border.color = "grey" b.inner_border.width = 0 b.margin_right = 15 b.margin_left = 0 lf.add_face(b, 5, position="aligned") n = TextFace('%s' % taxon_id2scientific_name_and_rank[str(lf.name)][0], fgcolor="black", fsize=9) # , fstyle = 'italic' lf.name = " %s (%s)" % (taxon_id2scientific_name_and_rank[str( lf.name)][0], str(lf.name)) n.margin_right = 10 lf.add_face(n, 0) tss.show_leaf_name = False for node in tree.traverse("postorder"): try: r = taxon_id2scientific_name_and_rank[str(node.name)][1] except: pass try: if r in ['phylum', 'superkingdom', 'class', 'subphylum' ] or taxon_id2scientific_name_and_rank[str( node.name)][0] in ['FCB group']: hola = TextFace( "%s" % (taxon_id2scientific_name_and_rank[str(node.name)][0])) node.add_face(hola, column=0, position="branch-top") except: pass return tree, tss
circular_style = TreeStyle() circular_style.show_leaf_name = False circular_style.show_branch_length = True circular_style.show_branch_support = True circular_style.scale = 75 circular_style.tree_width = 50 #circular_style.rotation = 90 #circular_style.extra_branch_line_type=(0) #circular_style.guiding_lines_type= (0) #circular_style.title.add_face(TextFace(File, fsize=25), column=0) circular_style.layout_fn = layout t.render(adres+"/out/"+File[:-4]+".png", tree_style=circular_style) circular_style.mode = "r" # draw tree in circular mode circular_style.extra_branch_line_type=(2) circular_style.guiding_lines_type= (2) circular_style.guiding_lines_color =("red") for n in t.traverse(): nstyle = NodeStyle() nstyle["fgcolor"] = "red" nstyle["size"] = 15 n.set_style(nstyle) #N = AttrFace("name", fsize=30) #faces.add_face_to_node(N, node, 0, position="aligned") circular_style.legend.add_face =(TextFace("0.5 support"), column=1) circular_style.legend.add_face =(CircleFace(10, "red"), column=0) circular_style.layout_fn = layout circular_style.legend.add_face(TextFace("0.5 support"), column=1) circular_style.title.add_face(TextFace(File, fsize=40), column=0) TextFace_=TextFace(text, ftype='Verdana', fsize=10, fgcolor='black', penwidth=0, fstyle='normal', tight_text=False, bold=False) t.render(adres+"/out/"+File[:-4]+"_c.png", tree_style=circular_style)
from ete3 import faces tree = EvolTree ("data/S_example/measuring_S_tree.nw") tree.link_to_alignment ('data/S_example/alignment_S_measuring_evol.fasta') print tree print '\n Running free-ratio model with calculation of ancestral sequences...' tree.run_model ('fb_anc') #tree.link_to_evol_model('/tmp/ete3-codeml/fb_anc/out', 'fb_anc') I = TreeStyle() I.force_topology = False I.draw_aligned_faces_as_table = True I.draw_guiding_lines = True I.guiding_lines_type = 2 I.guiding_lines_color = "#CCCCCC" for n in sorted (tree.get_descendants()+[tree], key=lambda x: x.node_id): if n.is_leaf(): continue anc_face = faces.SequenceFace (n.sequence, 'aa', fsize=10, bg_colors={}) I.aligned_foot.add_face(anc_face, 1) I.aligned_foot.add_face(faces.TextFace('node_id: #%d '%(n.node_id), fsize=8), 0) print 'display result of bs_anc model, with ancestral amino acid sequences.' tree.show(tree_style=I) print '\nThe End.'
def plot_tree_stacked_barplot( tree_file, taxon2value_list_barplot=False, header_list=False, # header stackedbarplots taxon2set2value_heatmap=False, taxon2label=False, header_list2=False, # header counts columns biodb=False, column_scale=True, general_max=False, header_list3=False, set2taxon2value_list_simple_barplot=False, set2taxon2value_list_simple_barplot_counts=True, rotate=False, taxon2description=False): ''' taxon2value_list_barplot list of lists: [[bar1_part1, bar1_part2,...],[bar2_part1, bar2_part2]] valeures de chaque liste transformes en pourcentages :param tree_file: :param taxon2value_list: :param biodb: :param exclude_outgroup: :param bw_scale: :return: ''' if biodb: from chlamdb.biosqldb import manipulate_biosqldb server, db = manipulate_biosqldb.load_db(biodb) taxon2description = manipulate_biosqldb.taxon_id2genome_description( server, biodb, filter_names=True) t1 = Tree(tree_file) # Calculate the midpoint node R = t1.get_midpoint_outgroup() # and set it as tree outgroup t1.set_outgroup(R) colors2 = [ "red", "#FFFF00", "#58FA58", "#819FF7", "#F781F3", "#2E2E2E", "#F7F8E0", 'black' ] colors = [ "#7fc97f", "#386cb0", "#fdc086", "#ffffb3", "#fdb462", "#f0027f", "#F7F8E0", 'black' ] # fdc086ff 386cb0ff f0027fff tss = TreeStyle() tss.draw_guiding_lines = True tss.guiding_lines_color = "gray" tss.show_leaf_name = False if column_scale and header_list2: import matplotlib.cm as cm from matplotlib.colors import rgb2hex import matplotlib as mpl column2scale = {} col_n = 0 for column in header_list2: values = taxon2set2value_heatmap[column].values() #print values if min(values) == max(values): min_val = 0 max_val = 1.5 * max(values) else: min_val = min(values) max_val = max(values) #print 'min-max', min_val, max_val norm = mpl.colors.Normalize(vmin=min_val, vmax=max_val) # *1.1 if col_n < 4: cmap = cm.OrRd # else: cmap = cm.YlGnBu #PuBu#OrRd m = cm.ScalarMappable(norm=norm, cmap=cmap) column2scale[column] = [m, float(max_val)] # *0.7 col_n += 1 for i, lf in enumerate(t1.iter_leaves()): #if taxon2description[lf.name] == 'Pirellula staleyi DSM 6068': # lf.name = 'Pirellula staleyi DSM 6068' # continue if i == 0: if taxon2label: n = TextFace(' ') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.hz_align = 2 n.vt_align = 2 n.rotation = 270 n.inner_background.color = "white" n.opacity = 1. tss.aligned_header.add_face(n, 0) col_add = 1 else: col_add = 1 if header_list: for col, header in enumerate(header_list): n = TextFace('%s' % (header)) n.margin_top = 0 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.rotation = 270 n.hz_align = 2 n.vt_align = 2 n.inner_background.color = "white" n.opacity = 1. tss.aligned_header.add_face(n, col + col_add) col_add += col + 1 if header_list3: #print 'header_list 3!' col_tmp = 0 for header in header_list3: n = TextFace('%s' % (header)) n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.rotation = 270 n.hz_align = 2 n.vt_align = 2 n.inner_background.color = "white" n.opacity = 1. if set2taxon2value_list_simple_barplot_counts: if col_tmp == 0: col_tmp += 1 tss.aligned_header.add_face(n, col_tmp + 1 + col_add) n = TextFace(' ') tss.aligned_header.add_face(n, col_tmp + col_add) col_tmp += 2 else: tss.aligned_header.add_face(n, col_tmp + col_add) col_tmp += 1 if set2taxon2value_list_simple_barplot_counts: col_add += col_tmp else: col_add += col_tmp if header_list2: for col, header in enumerate(header_list2): n = TextFace('%s' % (header)) n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.rotation = 270 n.hz_align = 2 n.vt_align = 2 n.inner_background.color = "white" n.opacity = 1. tss.aligned_header.add_face(n, col + col_add) col_add += col + 1 if taxon2label: try: n = TextFace('%s' % taxon2label[lf.name]) except: try: n = TextFace('%s' % taxon2label[int(lf.name)]) except: n = TextFace('-') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. if rotate: n.rotation = 270 lf.add_face(n, 1, position="aligned") col_add = 2 else: col_add = 2 if taxon2value_list_barplot: try: val_list_of_lists = taxon2value_list_barplot[lf.name] except: val_list_of_lists = taxon2value_list_barplot[int(lf.name)] #col_count = 0 for col, value_list in enumerate(val_list_of_lists): total = float(sum(value_list)) percentages = [(i / total) * 100 for i in value_list] if col % 3 == 0: col_list = colors2 else: col_list = colors b = StackedBarFace(percentages, width=150, height=18, colors=col_list[0:len(percentages)]) b.rotation = 0 b.inner_border.color = "white" b.inner_border.width = 0 b.margin_right = 5 b.margin_left = 5 if rotate: b.rotation = 270 lf.add_face(b, col + col_add, position="aligned") #col_count+=1 col_add += col + 1 if set2taxon2value_list_simple_barplot: col_list = [ '#fc8d59', '#91bfdb', '#99d594', '#c51b7d', '#f1a340', '#999999' ] color_i = 0 col = 0 for one_set in header_list3: if color_i > 5: color_i = 0 color = col_list[color_i] color_i += 1 # values for all taxons values_lists = [ float(i) for i in set2taxon2value_list_simple_barplot[one_set].values() ] #print values_lists #print one_set value = set2taxon2value_list_simple_barplot[one_set][lf.name] if set2taxon2value_list_simple_barplot_counts: if isinstance(value, float): a = TextFace(" %s " % str(round(value, 2))) else: a = TextFace(" %s " % str(value)) a.margin_top = 1 a.margin_right = 2 a.margin_left = 5 a.margin_bottom = 1 if rotate: a.rotation = 270 lf.add_face(a, col + col_add, position="aligned") #print 'value and max', value, max(values_lists) fraction_biggest = (float(value) / max(values_lists)) * 100 fraction_rest = 100 - fraction_biggest #print 'fractions', fraction_biggest, fraction_rest b = StackedBarFace([fraction_biggest, fraction_rest], width=100, height=15, colors=[color, 'white']) b.rotation = 0 b.inner_border.color = "grey" b.inner_border.width = 0 b.margin_right = 15 b.margin_left = 0 if rotate: b.rotation = 270 if set2taxon2value_list_simple_barplot_counts: if col == 0: col += 1 lf.add_face(b, col + 1 + col_add, position="aligned") col += 2 else: lf.add_face(b, col + col_add, position="aligned") col += 1 if set2taxon2value_list_simple_barplot_counts: col_add += col else: col_add += col if taxon2set2value_heatmap: i = 0 #if not taxon2label: # col_add-=1 for col2, head in enumerate(header_list2): col_name = header_list2[i] try: value = taxon2set2value_heatmap[col_name][str(lf.name)] except: try: value = taxon2set2value_heatmap[col_name][round( float(lf.name), 2)] except: value = 0 if header_list2[i] == 'duplicates': print('dupli', lf.name, value) #print 'val----------------', value if int(value) > 0: if int(value) >= 10 and int(value) < 100: n = TextFace('%4i' % value) elif int(value) >= 100: n = TextFace('%3i' % value) else: n = TextFace('%5i' % value) n.margin_top = 1 n.margin_right = 2 n.margin_left = 5 n.margin_bottom = 1 n.hz_align = 1 n.vt_align = 1 if rotate: n.rotation = 270 n.inner_background.color = rgb2hex( column2scale[col_name][0].to_rgba( float(value))) #"orange" #print 'xaxaxaxaxa', value, if float(value) > column2scale[col_name][1]: n.fgcolor = 'white' n.opacity = 1. n.hz_align = 1 n.vt_align = 1 lf.add_face(n, col2 + col_add, position="aligned") i += 1 else: n = TextFace('') n.margin_top = 1 n.margin_right = 1 n.margin_left = 5 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. if rotate: n.rotation = 270 lf.add_face(n, col2 + col_add, position="aligned") i += 1 #lf.name = taxon2description[lf.name] n = TextFace(taxon2description[lf.name], fgcolor="black", fsize=12, fstyle='italic') lf.add_face(n, 0) for n in t1.traverse(): nstyle = NodeStyle() if n.support < 1: nstyle["fgcolor"] = "black" nstyle["size"] = 6 n.set_style(nstyle) else: nstyle["fgcolor"] = "red" nstyle["size"] = 0 n.set_style(nstyle) return t1, tss
def plot_heat_tree(tree_file, biodb="chlamydia_04_16", exclude_outgroup=False, bw_scale=True): from chlamdb.biosqldb import manipulate_biosqldb import matplotlib.cm as cm from matplotlib.colors import rgb2hex import matplotlib as mpl server, db = manipulate_biosqldb.load_db(biodb) sql_biodatabase_id = 'select biodatabase_id from biodatabase where name="%s"' % biodb db_id = server.adaptor.execute_and_fetchall(sql_biodatabase_id, )[0][0] if type(tree_file) == str: t1 = Tree(tree_file) try: R = t1.get_midpoint_outgroup() #print 'root', R # and set it as tree outgroup t1.set_outgroup(R) except: pass elif isinstance(tree_file, Tree): t1 = tree_file else: IOError('Unkown tree format') tss = TreeStyle() tss.draw_guiding_lines = True tss.guiding_lines_color = "gray" tss.show_leaf_name = False #print "tree", t1 sql1 = 'select taxon_id, description from bioentry where biodatabase_id=%s and description not like "%%%%plasmid%%%%"' % db_id sql2 = 'select t2.taxon_id, t1.GC from genomes_info_%s as t1 inner join bioentry as t2 ' \ ' on t1.accession=t2.accession where t2.biodatabase_id=%s and t1.description not like "%%%%plasmid%%%%";' % (biodb, db_id) sql3 = 'select t2.taxon_id, t1.genome_size from genomes_info_%s as t1 ' \ ' inner join bioentry as t2 on t1.accession=t2.accession ' \ ' where t2.biodatabase_id=%s and t1.description not like "%%%%plasmid%%%%";' % (biodb, db_id) sql4 = 'select t2.taxon_id,percent_non_coding from genomes_info_%s as t1 ' \ ' inner join bioentry as t2 on t1.accession=t2.accession ' \ ' where t2.biodatabase_id=%s and t1.description not like "%%%%plasmid%%%%";' % (biodb, db_id) sql_checkm_completeness = 'select taxon_id, completeness from custom_tables.checkm_%s;' % biodb sql_checkm_contamination = 'select taxon_id,contamination from custom_tables.checkm_%s;' % biodb try: taxon_id2completeness = manipulate_biosqldb.to_dict( server.adaptor.execute_and_fetchall(sql_checkm_completeness)) taxon_id2contamination = manipulate_biosqldb.to_dict( server.adaptor.execute_and_fetchall(sql_checkm_contamination)) except: taxon_id2completeness = False #taxon2description = manipulate_biosqldb.to_dict(server.adaptor.execute_and_fetchall(sql1,)) taxon2description = manipulate_biosqldb.taxon_id2genome_description( server, biodb, filter_names=True) taxon2gc = manipulate_biosqldb.to_dict( server.adaptor.execute_and_fetchall(sql2, )) taxon2genome_size = manipulate_biosqldb.to_dict( server.adaptor.execute_and_fetchall(sql3, )) taxon2coding_density = manipulate_biosqldb.to_dict( server.adaptor.execute_and_fetchall(sql4, )) my_taxons = [lf.name for lf in t1.iter_leaves()] # Calculate the midpoint node if exclude_outgroup: excluded = str(list(t1.iter_leaves())[0].name) my_taxons.pop(my_taxons.index(excluded)) genome_sizes = [float(taxon2genome_size[i]) for i in my_taxons] gc_list = [float(taxon2gc[i]) for i in my_taxons] fraction_list = [float(taxon2coding_density[i]) for i in my_taxons] value = 1 max_genome_size = max(genome_sizes) #3424182# max_gc = max(gc_list) #48.23 cmap = cm.YlGnBu #YlOrRd#OrRd norm = mpl.colors.Normalize(vmin=min(genome_sizes) - 100000, vmax=max(genome_sizes)) m1 = cm.ScalarMappable(norm=norm, cmap=cmap) norm = mpl.colors.Normalize(vmin=min(gc_list), vmax=max(gc_list)) m2 = cm.ScalarMappable(norm=norm, cmap=cmap) norm = mpl.colors.Normalize(vmin=min(fraction_list), vmax=max(fraction_list)) m3 = cm.ScalarMappable(norm=norm, cmap=cmap) for i, lf in enumerate(t1.iter_leaves()): #if taxon2description[lf.name] == 'Pirellula staleyi DSM 6068': # lf.name = 'Pirellula staleyi DSM 6068' # continue if i == 0: n = TextFace('Size (Mbp)') n.rotation = -25 n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. #lf.add_face(n, 3, position="aligned") tss.aligned_header.add_face(n, 3) n = TextFace('GC (%)') n.rotation = -25 n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. #lf.add_face(n, 5, position="aligned") tss.aligned_header.add_face(n, 5) n = TextFace('') #lf.add_face(n, 2, position="aligned") tss.aligned_header.add_face(n, 2) #lf.add_face(n, 4, position="aligned") tss.aligned_header.add_face(n, 4) n = TextFace('Non coding (%)') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. n.rotation = -25 #lf.add_face(n, 7, position="aligned") tss.aligned_header.add_face(n, 7) n = TextFace('') #lf.add_face(n, 6, position="aligned") tss.aligned_header.add_face(n, 6) if taxon_id2completeness: n = TextFace('Completeness (%)') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. n.rotation = -25 #lf.add_face(n, 7, position="aligned") tss.aligned_header.add_face(n, 9) n = TextFace('') #lf.add_face(n, 6, position="aligned") tss.aligned_header.add_face(n, 8) n = TextFace('Contamination (%)') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. n.rotation = -25 #lf.add_face(n, 7, position="aligned") tss.aligned_header.add_face(n, 11) n = TextFace('') #lf.add_face(n, 6, position="aligned") tss.aligned_header.add_face(n, 10) value += 1 #print '------ %s' % lf.name if exclude_outgroup and i == 0: lf.name = taxon2description[lf.name] #print '#######################' continue n = TextFace( ' %s ' % str(round(taxon2genome_size[lf.name] / float(1000000), 2))) n.margin_top = 1 n.margin_right = 1 n.margin_left = 0 n.margin_bottom = 1 n.fsize = 7 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, 2, position="aligned") #if max_genome_size > 3424182: # max_genome_size = 3424182 fraction_biggest = (float(taxon2genome_size[lf.name]) / max_genome_size) * 100 fraction_rest = 100 - fraction_biggest if taxon2description[lf.name] == 'Rhabdochlamydia helveticae T3358': col = '#fc8d59' else: if not bw_scale: col = rgb2hex(m1.to_rgba(float( taxon2genome_size[lf.name]))) # 'grey' else: col = '#fc8d59' b = StackedBarFace([fraction_biggest, fraction_rest], width=100, height=9, colors=[col, 'white']) b.rotation = 0 b.inner_border.color = "black" b.inner_border.width = 0 b.margin_right = 15 b.margin_left = 0 lf.add_face(b, 3, position="aligned") fraction_biggest = (float(taxon2gc[lf.name]) / max_gc) * 100 fraction_rest = 100 - fraction_biggest if taxon2description[lf.name] == 'Rhabdochlamydia helveticae T3358': col = '#91bfdb' else: if not bw_scale: col = rgb2hex(m2.to_rgba(float(taxon2gc[lf.name]))) else: col = '#91bfdb' b = StackedBarFace([fraction_biggest, fraction_rest], width=100, height=9, colors=[col, 'white']) b.rotation = 0 b.inner_border.color = "black" b.inner_border.width = 0 b.margin_left = 0 b.margin_right = 15 lf.add_face(b, 5, position="aligned") n = TextFace(' %s ' % str(round(float(taxon2gc[lf.name]), 2))) n.margin_top = 1 n.margin_right = 0 n.margin_left = 0 n.margin_bottom = 1 n.fsize = 7 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, 4, position="aligned") if taxon2description[lf.name] == 'Rhabdochlamydia helveticae T3358': col = '#99d594' else: if not bw_scale: col = rgb2hex(m3.to_rgba(float(taxon2coding_density[lf.name]))) else: col = '#99d594' n = TextFace(' %s ' % str(float(taxon2coding_density[lf.name]))) n.margin_top = 1 n.margin_right = 0 n.margin_left = 0 n.margin_right = 0 n.margin_bottom = 1 n.fsize = 7 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, 6, position="aligned") fraction = (float(taxon2coding_density[lf.name]) / max(taxon2coding_density.values())) * 100 fraction_rest = ((max(taxon2coding_density.values()) - taxon2coding_density[lf.name]) / float(max(taxon2coding_density.values()))) * 100 #print 'fraction, rest', fraction, fraction_rest b = StackedBarFace( [fraction, fraction_rest], width=100, height=9, colors=[col, 'white' ]) # 1-round(float(taxon2coding_density[lf.name]), 2) b.rotation = 0 b.margin_right = 1 b.inner_border.color = "black" b.inner_border.width = 0 b.margin_left = 5 lf.add_face(b, 7, position="aligned") if taxon_id2completeness: n = TextFace(' %s ' % str(float(taxon_id2completeness[lf.name]))) n.margin_top = 1 n.margin_right = 0 n.margin_left = 0 n.margin_right = 0 n.margin_bottom = 1 n.fsize = 7 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, 8, position="aligned") fraction = float(taxon_id2completeness[lf.name]) fraction_rest = 100 - fraction #print 'fraction, rest', fraction, fraction_rest b = StackedBarFace( [fraction, fraction_rest], width=100, height=9, colors=["#d7191c", 'white' ]) # 1-round(float(taxon2coding_density[lf.name]), 2) b.rotation = 0 b.margin_right = 1 b.inner_border.color = "black" b.inner_border.width = 0 b.margin_left = 5 lf.add_face(b, 9, position="aligned") n = TextFace(' %s ' % str(float(taxon_id2contamination[lf.name]))) n.margin_top = 1 n.margin_right = 0 n.margin_left = 0 n.margin_right = 0 n.margin_bottom = 1 n.fsize = 7 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, 10, position="aligned") fraction = float(taxon_id2contamination[lf.name]) fraction_rest = 100 - fraction #print 'fraction, rest', fraction, fraction_rest b = StackedBarFace( [fraction, fraction_rest], width=100, height=9, colors=["black", 'white' ]) # 1-round(float(taxon2coding_density[lf.name]), 2) b.rotation = 0 b.margin_right = 1 b.inner_border.color = "black" b.inner_border.width = 0 b.margin_left = 5 lf.add_face(b, 11, position="aligned") #lf.name = taxon2description[lf.name] n = TextFace(taxon2description[lf.name], fgcolor="black", fsize=9, fstyle='italic') n.margin_right = 30 lf.add_face(n, 0) for n in t1.traverse(): nstyle = NodeStyle() if n.support < 1: nstyle["fgcolor"] = "black" nstyle["size"] = 6 n.set_style(nstyle) else: nstyle["fgcolor"] = "red" nstyle["size"] = 0 n.set_style(nstyle) return t1, tss
def plot_tree_text_metadata(tree_file, header2taxon2text, ordered_header_list, biodb): from chlamdb.biosqldb import manipulate_biosqldb server, db = manipulate_biosqldb.load_db(biodb) t1 = Tree(tree_file) taxon2description = manipulate_biosqldb.taxon_id2genome_description( server, biodb, filter_names=True) # Calculate the midpoint node R = t1.get_midpoint_outgroup() # and set it as tree outgroup t1.set_outgroup(R) tss = TreeStyle() tss.draw_guiding_lines = True tss.guiding_lines_color = "gray" tss.show_leaf_name = False for i, leaf in enumerate(t1.iter_leaves()): # first leaf, add headers if i == 0: for column, header in enumerate(ordered_header_list): n = TextFace('%s' % (header)) n.margin_top = 0 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.rotation = 270 n.hz_align = 2 n.vt_align = 2 n.inner_background.color = "white" n.opacity = 1. tss.aligned_header.add_face(n, column) for column, header in enumerate(ordered_header_list): text = header2taxon2text[header][int(leaf.name)] n = TextFace('%s' % text) n.margin_top = 1 n.margin_right = 1 n.margin_left = 5 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. #n.rotation = 270 leaf.add_face(n, column + 1, position="aligned") # rename leaf (taxon_id => description) n = TextFace(taxon2description[leaf.name], fgcolor="black", fsize=12, fstyle='italic') leaf.add_face(n, 0) for n in t1.traverse(): # rename leaf nstyle = NodeStyle() if n.support < 1: nstyle["fgcolor"] = "black" nstyle["size"] = 6 n.set_style(nstyle) else: nstyle["fgcolor"] = "red" nstyle["size"] = 0 n.set_style(nstyle) return t1, tss
def plot_heatmap_tree_locus(biodb, tree_file, taxid2count, taxid2identity=False, taxid2locus=False, reference_taxon=False, n_paralogs_barplot=False): ''' plot tree and associated heatmap with count of homolgs optional: - add identity of closest homolog - add locus tag of closest homolog ''' from chlamdb.biosqldb import manipulate_biosqldb server, db = manipulate_biosqldb.load_db(biodb) taxid2organism = manipulate_biosqldb.taxon_id2genome_description( server, biodb, True) t1 = Tree(tree_file) ts = TreeStyle() ts.draw_guiding_lines = True ts.guiding_lines_color = "gray" # Calculate the midpoint node R = t1.get_midpoint_outgroup() # and set it as tree outgroup t1.set_outgroup(R) leaf_number = 0 for lf in t1.iter_leaves(): if str(lf.name) not in taxid2count: taxid2count[str(lf.name)] = 0 max_count = max([taxid2count[str(lf.name)] for lf in t1.iter_leaves()]) for i, lf in enumerate(t1.iter_leaves()): # top leaf, add header if i == 0: n = TextFace('Number of homologs') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. n.rotation = -25 #lf.add_face(n, 7, position="aligned") ts.aligned_header.add_face(n, 1) if taxid2identity: n = TextFace('Protein identity') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. n.rotation = -25 #lf.add_face(n, 7, position="aligned") ts.aligned_header.add_face(n, 2) if taxid2locus: n = TextFace('Locus tag') n.margin_top = 1 n.margin_right = 1 n.margin_left = 20 n.margin_bottom = 1 n.inner_background.color = "white" n.opacity = 1. n.rotation = -25 #lf.add_face(n, 7, position="aligned") ts.aligned_header.add_face(n, 3) leaf_number += 1 lf.branch_vertical_margin = 0 data = [taxid2count[str(lf.name)]] # possibility to add one or more columns for col, value in enumerate(data): col_index = col if value > 0: n = TextFace(' %s ' % str(value)) n.margin_top = 2 n.margin_right = 2 if col == 0: n.margin_left = 20 else: n.margin_left = 2 n.margin_bottom = 2 n.inner_background.color = "white" # #81BEF7 n.opacity = 1. lf.add_face(n, col, position="aligned") else: n = TextFace(' %s ' % str(value)) n.margin_top = 2 n.margin_right = 2 if col == 0: n.margin_left = 20 else: n.margin_left = 2 n.margin_bottom = 2 n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, col, position="aligned") # optionally indicate number of paralogs as a barplot if n_paralogs_barplot: col_index += 1 percent = (float(value) / max_count) * 100 n = StackedBarFace([percent, 100 - percent], width=150, height=18, colors=['#6699ff', 'white'], line_color='white') n.rotation = 0 n.inner_border.color = "white" n.inner_border.width = 0 n.margin_right = 15 n.margin_left = 0 lf.add_face(n, col + 1, position="aligned") # optionally add additionnal column with identity if taxid2identity: import matplotlib.cm as cm from matplotlib.colors import rgb2hex import matplotlib as mpl norm = mpl.colors.Normalize(vmin=0, vmax=100) cmap = cm.OrRd m = cm.ScalarMappable(norm=norm, cmap=cmap) try: if round(taxid2identity[str(lf.name)], 2) != 100: value = "%.2f" % round(taxid2identity[str(lf.name)], 2) else: value = "%.1f" % round(taxid2identity[str(lf.name)], 2) except: value = '-' if str(lf.name) == str(reference_taxon): value = ' ' n = TextFace(' %s ' % value) n.margin_top = 2 n.margin_right = 2 n.margin_left = 20 n.margin_bottom = 2 if not value.isspace() and value is not '-': n.inner_background.color = rgb2hex(m.to_rgba(float(value))) if float(value) > 82: n.fgcolor = 'white' n.opacity = 1. if str(lf.name) == str(reference_taxon): n.inner_background.color = '#800000' lf.add_face(n, col_index + 1, position="aligned") # optionaly add column with locus name if taxid2locus: try: value = str(taxid2locus[str(lf.name)]) except: value = '-' n = TextFace(' %s ' % value) n.margin_top = 2 n.margin_right = 2 n.margin_left = 2 n.margin_bottom = 2 if str(lf.name) != str(reference_taxon): n.inner_background.color = "white" else: n.fgcolor = '#ff0000' n.inner_background.color = "white" n.opacity = 1. lf.add_face(n, col_index + 2, position="aligned") lf.name = taxid2organism[str(lf.name)] return t1, leaf_number, ts