move legend to up and fix y-axis inward if using different ymax

deeptools/heatmapper.py

@@ -1308,9 +1308,9 @@ def hmcluster(self, k, evaluate_silhouette=True, method='kmeans', clustering_sam
         _clustered_matrix = []
         cluster_number = 1
         for cluster in cluster_order:
-            self.group_labels.append("cluster_{}".format(cluster_number))
-            cluster_number += 1
             cluster_ids = _cluster_ids_list[cluster]
+            self.group_labels.append("cluster_{}_n{}".format(cluster_number,len(cluster_ids)))
+            cluster_number += 1
             self.group_boundaries.append(self.group_boundaries[-1] +
                                          len(cluster_ids))
             _clustered_matrix.append(self.matrix[cluster_ids, :])

deeptools/heatmapper_utilities.py

@@ -9,6 +9,9 @@
 
 old_settings = np.seterr(all='ignore')
 
+debug = 0
+if debug:
+    from ipdb import set_trace
 
 def plot_single(ax, ma, average_type, color, label, plot_type='lines'):
     """
@@ -18,7 +21,7 @@ def plot_single(ax, ma, average_type, color, label, plot_type='lines'):
     ----------
     ax : matplotlib axis
         matplotlib axis
-    ma : numpy array
+    ma : numpy array or list of numpy array(for plot with --repgrplist, take average between replicates )
         numpy array The data on this matrix is summarized according
         to the `average_type` argument.
     average_type : str
@@ -32,7 +35,9 @@ def plot_single(ax, ma, average_type, color, label, plot_type='lines'):
         type of plot. Either 'se' for standard error, 'std' for
         standard deviation, 'overlapped_lines' to plot each line of the matrix,
         fill to plot the area between the x axis and the value or any other string to
-        just plot the average line.
+        just plot the average line. When assign samples to replicates group such as
+        '--repgrplist WT WT KO KO' : 'std' would be the standard deviation between replicates groups.
+        'se' for standard error between replicates groups.
 
     Returns
     -------
@@ -63,7 +68,15 @@ def plot_single(ax, ma, average_type, color, label, plot_type='lines'):
 
 
     """
-    summary = np.ma.__getattribute__(average_type)(ma, axis=0)
+    if isinstance(ma,list):
+        summary_list = []
+        for ma_each in ma:
+            tmp = np.ma.__getattribute__(average_type)(ma_each, axis=0)
+            summary_list.append(tmp)
+        ma = np.array(summary_list)
+        summary = np.ma.__getattribute__("average")(ma, axis=0)
+    else:
+        summary = np.ma.__getattribute__(average_type)(ma, axis=0)
     # only plot the average profiles without error regions
     x = np.arange(len(summary))
     if isinstance(color, np.ndarray):
@@ -72,6 +85,8 @@ def plot_single(ax, ma, average_type, color, label, plot_type='lines'):
     if plot_type == 'fill':
         ax.fill_between(x, summary, facecolor=color, alpha=0.6, edgecolor='none')
 
+    if debug:
+        set_trace()
     if plot_type in ['se', 'std']:
         if plot_type == 'se':  # standard error
             std = np.std(ma, axis=0) / np.sqrt(ma.shape[0])

deeptools/parserCommon.py

@@ -851,6 +851,14 @@ def heatmapperOptionalArgs(mode=['heatmap', 'profile'][0]):
                           'group.',
                           action='store_true')
 
+    optional.add_argument('--repgrplist',
+                          default=None,
+                          nargs='+',
+                          help='Group profiles by genotype'
+                               'assign each profile to a group(as replicates) to plot average +/- se/std.'
+                               'If the number of group values is smaller than'
+                               'the number of samples, the values will be equally divide into groups.')
+
     optional.add_argument('--plotFileFormat',
                           metavar='',
                           help='Image format type. If given, this '

deeptools/plotHeatmap.py

@@ -13,8 +13,8 @@
 from matplotlib.font_manager import FontProperties
 import matplotlib.gridspec as gridspec
 from matplotlib import ticker
-import copy
-import sys
+
+import sys, re, os, copy
 import plotly.offline as py
 import plotly.graph_objs as go
 
@@ -117,6 +117,21 @@ def prepare_layout(hm_matrix, heatmapsize, showSummaryPlot, showColorbar, perGro
 
     return grids
 
+def autobreaklinetitle(title,sep="[-_,.:]",lmax=15):
+    outsep = "-"
+    sss = [ rr for rr in re.split(sep,title) if len(rr) ]
+    newtitle, tmp = "", ""
+    for ss in sss:
+        tmp0 = tmp
+        tmp += ss
+        if len(tmp) > lmax:
+            newtitle += tmp0.strip(outsep) + "\n"
+            tmp = ss
+        else:
+            tmp += outsep
+    newtitle += tmp.strip(outsep)
+    newtitle = "\n" + newtitle
+    return newtitle
 
 def addProfilePlot(hm, plt, fig, grids, iterNum, iterNum2, perGroup, averageType, plot_type, yAxisLabel, color_list, yMin, yMax, wspace, hspace, colorbar_position, label_rotation=0.0):
     """
@@ -146,7 +161,7 @@ def addProfilePlot(hm, plt, fig, grids, iterNum, iterNum2, perGroup, averageType
             else:
                 ax_profile = fig.add_subplot(grids[0, sample_id])
 
-        ax_profile.set_title(title)
+        ax_profile.set_title(autobreaklinetitle(title))
         for group in range(iterNum2):
             if perGroup:
                 sub_matrix = hm.matrix.get_matrix(sample_id, group)
@@ -163,6 +178,7 @@ def addProfilePlot(hm, plt, fig, grids, iterNum, iterNum2, perGroup, averageType
         if sample_id > 0 and len(yMin) == 1 and len(yMax) == 1:
             plt.setp(ax_profile.get_yticklabels(), visible=False)
 
+        ax_profile.get_yaxis().set_tick_params(direction='in',pad=-22) # beisi
         if sample_id == 0 and yAxisLabel != '':
             ax_profile.set_ylabel(yAxisLabel)
         xticks, xtickslabel = hm.getTicks(tickIdx)
@@ -591,8 +607,13 @@ def plotMatrix(hm, outFileName,
         ax_list = addProfilePlot(hm, plt, fig, grids, iterNum, iterNum2, perGroup, averageType, plot_type, yAxisLabel, color_list, yMin, yMax, None, None, colorbar_position, label_rotation)
 
         if legend_location != 'none':
-            ax_list[-1].legend(loc=legend_location.replace('-', ' '), ncol=1, prop=fontP,
-                               frameon=False, markerscale=0.5)
+            ax = ax_list[-1] # beisi
+            box = ax.get_position()
+            ax.set_position([box.x0, box.y0 - box.height * 0.1, box.width, box.height * 0.9])
+            legend = ax.legend(loc='lower right', shadow=False, fontsize='x-large', bbox_to_anchor=(0, 1.3, 1, .22), ncol=10, frameon=False, prop=fontP) # beisi, legend line
+            ax.add_artist(legend)
+            #            ax_list[-1].legend(loc=legend_location.replace('-', ' '), ncol=1, prop=fontP,
+            #                   frameon=False, markerscale=0.5)
 
     first_group = 0  # helper variable to place the title per sample/group
     for sample in range(hm.matrix.get_num_samples()):
@@ -628,7 +649,7 @@ def plotMatrix(hm, outFileName,
 
             if group == first_group and not showSummaryPlot and not perGroup:
                 title = hm.matrix.sample_labels[sample]
-                ax.set_title(title)
+                ax.set_title(autobreaklinetitle(title))
 
             if box_around_heatmaps is False:
                 # Turn off the boxes around the individual heatmaps
@@ -681,9 +702,9 @@ def plotMatrix(hm, outFileName,
                 ax.axes.set_xlabel(xAxisLabel)
             ax.axes.set_yticks([])
             if perGroup and group == 0:
-                ax.axes.set_ylabel(sub_matrix['sample'])
+                ax.axes.set_ylabel(sub_matrix['sample'],rotation=75,labelpad=0,fontsize=15)
             elif not perGroup and sample == 0:
-                ax.axes.set_ylabel(sub_matrix['group'])
+                ax.axes.set_ylabel(sub_matrix['group'],rotation=75,labelpad=0,horizontalalignment='right',fontsize=15)
 
             # Plot vertical lines at tick marks if desired
             if linesAtTickMarks:

deeptools/plotProfile.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 
 
-import sys
+import sys, os, re
 
 import argparse
 import numpy as np
@@ -26,12 +26,12 @@
 from deeptools.heatmapper_utilities import plot_single, plotly_single, getProfileTicks
 from deeptools.computeMatrixOperations import filterHeatmapValues
 
-
 debug = 0
+if debug:
+    from ipdb import set_trace
 old_settings = np.seterr(all='ignore')
 plt.ioff()
 
-
 def parse_arguments(args=None):
     parser = argparse.ArgumentParser(
         parents=[parserCommon.heatmapperMatrixArgs(),
@@ -51,6 +51,21 @@ def parse_arguments(args=None):
 
     return parser
 
+def autobreaklinetitle(title,sep="[-_,.:]",lmax=15):
+    outsep = "-"
+    sss = [ rr for rr in re.split(sep,title) if len(rr) ]
+    newtitle, tmp = "", ""
+    for ss in sss:
+        tmp0 = tmp
+        tmp += ss
+        if len(tmp) > lmax:
+            newtitle += tmp0.strip(outsep) + "\n"
+            tmp = ss
+        else:
+            tmp += outsep
+    newtitle += tmp.strip(outsep)
+    newtitle = "\n" + newtitle
+    return newtitle
 
 def process_args(args=None):
     args = parse_arguments().parse_args(args)
@@ -98,6 +113,7 @@ def __init__(self, hm, out_file_name,
                  plot_height=7,
                  plot_width=11,
                  per_group=False,
+                 repgrplist=None,
                  plot_type='lines',
                  image_format=None,
                  color_list=None,
@@ -124,6 +140,7 @@ def __init__(self, hm, out_file_name,
             plot_height: in cm
             plot_width: in cm
             per_group: bool
+            repgrplist: list
             plot_type: string
             image_format: string
             color_list: list
@@ -147,6 +164,7 @@ def __init__(self, hm, out_file_name,
         self.plot_height = plot_height
         self.plot_width = plot_width
         self.per_group = per_group
+        self.repgrplist = repgrplist
         self.plot_type = plot_type
         self.image_format = image_format
         self.color_list = color_list
@@ -158,11 +176,13 @@ def __init__(self, hm, out_file_name,
         # Honor reference point labels from computeMatrix
         if reference_point_label is None:
             self.reference_point_label = hm.parameters['ref point']
-
         # decide how many plots are needed
         if self.per_group:
             self.numplots = self.hm.matrix.get_num_groups()
-            self.numlines = self.hm.matrix.get_num_samples()
+            if self.repgrplist:
+                self.numlines = len(set(self.repgrplist))
+            else:
+                self.numlines = self.hm.matrix.get_num_samples()
         else:
             self.numplots = self.hm.matrix.get_num_samples()
             self.numlines = self.hm.matrix.get_num_groups()
@@ -271,7 +291,7 @@ def plot_hexbin(self):
             for data_idx in range(self.numlines)[::-1]:
                 ax = self.fig.add_subplot(sub_grid[data_idx, 0])
                 if data_idx == 0:
-                    ax.set_title(title)
+                    ax.set_title(autobreaklinetitle(title))
                 if data_idx != self.numlines - 1:
                     plt.setp(ax.get_xticklabels(), visible=False)
 
@@ -512,11 +532,11 @@ def plot_heatmap(self):
 
             if self.per_group:
                 title = self.hm.matrix.group_labels[plot]
-                tickIdx = plot % self.hm.matrix.get_num_samples()
+                tickIdx = plot % self.numlines
             else:
                 title = self.hm.matrix.sample_labels[plot]
                 tickIdx = plot
-            ax.set_title(title)
+            ax.set_title(autobreaklinetitle(title))
             mat = []  # when drawing a heatmap (in contrast to drawing lines)
             for data_idx in range(self.numlines):
                 if self.per_group:
@@ -718,41 +738,84 @@ def plot_profile(self):
                 title = self.hm.matrix.group_labels[plot]
                 if row != 0 and len(self.y_min) == 1 and len(self.y_max) == 1:
                     plt.setp(ax.get_yticklabels(), visible=False)
-                tickIdx = plot % self.hm.matrix.get_num_samples()
+                tickIdx = plot % self.numlines
             else:
                 title = self.hm.matrix.sample_labels[plot]
                 if col != 0 and len(self.y_min) == 1 and len(self.y_max) == 1:
                     plt.setp(ax.get_yticklabels(), visible=False)
                 tickIdx = plot
 
-            ax.set_title(title)
-            for data_idx in range(self.numlines):
-                if self.per_group:
-                    _row, _col = plot, data_idx
-                else:
-                    _row, _col = data_idx, plot
-                if localYMin is None or self.y_min[col % len(self.y_min)] < localYMin:
-                    localYMin = self.y_min[col % len(self.y_min)]
-                if localYMax is None or self.y_max[col % len(self.y_max)] > localYMax:
-                    localYMax = self.y_max[col % len(self.y_max)]
-
-                sub_matrix = self.hm.matrix.get_matrix(_row, _col)
-
-                if self.per_group:
-                    label = sub_matrix['sample']
-                else:
-                    label = sub_matrix['group']
-
-                if self.numlines > 1:
-                    coloridx = data_idx
-                else:
-                    coloridx = plot
-                plot_single(ax, sub_matrix['matrix'],
-                            self.averagetype,
-                            self.color_list[coloridx],
-                            label,
-                            plot_type=self.plot_type)
-            globalYmin = min(float(globalYmin), ax.get_ylim()[0])
+            ax.set_title(autobreaklinetitle(title))
+            if localYMin is None or self.y_min[col % len(self.y_min)] < localYMin:
+                localYMin = self.y_min[col % len(self.y_min)]
+            if localYMax is None or self.y_max[col % len(self.y_max)] > localYMax:
+                localYMax = self.y_max[col % len(self.y_max)]
+            if self.per_group and self.repgrplist:
+                nsamptmp = self.hm.matrix.get_num_samples()
+                repgrp_samp_dict = {}
+                repgrplistuniq = []
+                for tmp in self.repgrplist:
+                    if not tmp in repgrplistuniq:
+                        repgrplistuniq.append(tmp)
+
+                for data_idx in range(nsamptmp):
+                    if len(self.repgrplist) >= nsamptmp:
+                        thisrepgrp = self.repgrplist[data_idx]
+                    else:
+                        thisrepgrp = repgrplistuniq[int(data_idx / (nsamptmp/self.numlines))]
+                    try:
+                        repgrp_samp_dict[thisrepgrp].append(data_idx)
+                    except:
+                        repgrp_samp_dict[thisrepgrp] = [ data_idx ]
+
+                if debug:
+                    set_trace()
+                for irepgrp, repgrp in enumerate(repgrplistuniq):
+                    sub_matrix_list = []
+                    for data_idx in repgrp_samp_dict[repgrp]:
+                        _row, _col = plot, data_idx
+                        sub_matrix = self.hm.matrix.get_matrix(_row, _col)
+                        sub_matrix_list.append(sub_matrix['matrix'])
+
+                    label = f"{repgrp}(n={len(repgrp_samp_dict[repgrp])})"
+
+                    if self.numlines > 1:
+                        coloridx = irepgrp
+                    else:
+                        coloridx = plot
+                    plot_single(ax, sub_matrix_list,
+                                self.averagetype,
+                                self.color_list[coloridx],
+                                label,
+                                plot_type=self.plot_type)
+            else:
+                for data_idx in range(self.numlines):
+                    if self.per_group:
+                        _row, _col = plot, data_idx
+                    else:
+                        _row, _col = data_idx, plot
+                    if localYMin is None or self.y_min[col % len(self.y_min)] < localYMin:
+                        localYMin = self.y_min[col % len(self.y_min)]
+                    if localYMax is None or self.y_max[col % len(self.y_max)] > localYMax:
+                        localYMax = self.y_max[col % len(self.y_max)]
+
+                    sub_matrix = self.hm.matrix.get_matrix(_row, _col)
+
+                    if self.per_group:
+                        label = sub_matrix['sample']
+                    else:
+                        label = sub_matrix['group']
+
+                    if self.numlines > 1:
+                        coloridx = data_idx
+                    else:
+                        coloridx = plot
+                    plot_single(ax, sub_matrix['matrix'],
+                                self.averagetype,
+                                self.color_list[coloridx],
+                                label,
+                                plot_type=self.plot_type)
+            globalYmin = min(np.float64(globalYmin), ax.get_ylim()[0])
             globalYmax = max(globalYmax, ax.get_ylim()[1])
 
             # Exclude ticks from all but one subplot by default
@@ -957,6 +1020,7 @@ def main(args=None):
                    plot_height=args.plotHeight,
                    plot_width=args.plotWidth,
                    per_group=args.perGroup,
+                   repgrplist=args.repgrplist,
                    plot_type=args.plotType,
                    image_format=args.plotFileFormat,
                    color_list=args.colors,