Merge pull request #351 from hyanwong/viz-subtree

Show trees of Pango lineages

pyproject.toml

@@ -12,7 +12,9 @@ dependencies = [
   # FIXME
   "tsinfer @ git+https://github.com/jeromekelleher/tsinfer.git@experimental-hmm",
   "pyfaidx",
-  "tskit>=0.5.3",
+  # FIXME - reinstate when 0.5.9 is released
+  # "tskit>=0.5.9",
+  "tskit @ git+https://github.com/tskit-dev/tskit.git@main#subdirectory=python",
   "tszip",
   "pandas",
   "numba",

sc2ts/info.py

@@ -1543,6 +1543,134 @@ def plot_recombinants_per_day(self):
         ax2.set_ylabel("Fraction of samples recombinant")
         ax2.set_ylim(0, 0.01)
 
+    def plot_pango_lineage_subtree(
+        self,
+        lineage,
+        position=None,
+        collapse_tracked=None,
+        remove_clones=None,
+        *,
+        pack_untracked_polytomies=True,
+        time_scale="rank",
+        title=None,
+        mutation_labels=None,
+        size=None,
+        style="",
+        **kwargs
+    ):
+        if position is None:
+            position = 21563  # pick the start of the spike
+        if size is None:
+            size = (1000, 1000)
+        if remove_clones:
+            # TODO
+            raise NotImplementedError("remove_clones not implemented")
+        # remove mutation times, so they get spaced evenly along a branch
+        tables = self.ts.dump_tables()
+        time = tables.mutations.time
+        time[:] = tskit.UNKNOWN_TIME
+        tables.mutations.time = time
+        ts = tables.tree_sequence()
+        tracked_nodes = self.pango_lineage_samples[lineage]
+        tree = ts.at(position, tracked_samples=tracked_nodes)
+        order = np.array(list(tskit.drawing._postorder_tracked_minlex_traversal(
+            tree, collapse_tracked=collapse_tracked)))
+        if title is None:
+            simplified_ts = ts.simplify(order[np.where(ts.nodes_flags[order] & tskit.NODE_IS_SAMPLE)[0]])
+            num_trees = simplified_ts.num_trees
+            tree_pos = simplified_ts.at(position).index
+            title = (
+                f"Sc2ts genealogy of {len(tracked_nodes)} {lineage} samples "
+                f"at position {position} (tree {tree_pos}/{num_trees})"
+                # f" --- file: "  # TODO - show filename
+            )
+
+        # Find the actually shown nodes (i.e. if polytomies are packed, we may not 
+        # see some tips. This is copied from tskit.drawing.SvgTree.assign_x_coordinates
+        shown_nodes = order
+        if pack_untracked_polytomies:
+            shown_nodes = []
+            untracked_children = collections.defaultdict(list)
+            prev = tree.virtual_root
+            for u in order:
+                parent = tree.parent(u)
+                assert parent != prev
+                if tree.parent(prev) != u:  # is a tip
+                    if tree.num_tracked_samples(u) == 0:
+                        untracked_children[parent].append(u)
+                    else:
+                        shown_nodes.append(u)
+                else:
+                    if len(untracked_children[u]) == 1:
+                            # If only a single non-focal lineage, we might as well show it
+                            for child in untracked_children[u]:
+                                shown_nodes.append(child)
+                    shown_nodes.append(u)
+                prev = u
+
+        if mutation_labels is None:
+            mutation_labels = collections.defaultdict(list)
+            multiple_mutations = []
+            reverted_mutations = []
+            use_mutations = np.where(np.isin(ts.mutations_node, shown_nodes))[0]
+            sites = ts.mutations_site[use_mutations]
+            for mut_id in use_mutations:
+                # TODO Viz the recurrent mutations
+                mut = ts.mutation(mut_id)
+                site = ts.site(mut.site)
+                if len(sites == site.id) > 1:
+                    multiple_mutations.append(mut.id)
+                inherited_state = site.ancestral_state
+                if mut.parent >= 0:
+                    parent = ts.mutation(mut.parent)
+                    inherited_state = parent.derived_state
+                    parent_inherited_state = site.ancestral_state
+                    if parent.parent >= 0:
+                        parent_inherited_state = ts.mutation(parent.parent).derived_state
+                    if parent_inherited_state == mut.derived_state:
+                        reverted_mutations.append(mut.id)
+                # Reverse map label name to mutation id, so we can count duplicates
+                label = f"{inherited_state}{int(site.position)}{mut.derived_state}"
+                mutation_labels[label].append(mut.id)
+            # If more than one mutation has the same label, add a prefix with the counts
+            mutation_labels = {
+                m_id: label + (f" ({i+1}/{len(ids)})" if len(ids) > 1 else "")
+                for label, ids in mutation_labels.items()
+                for i, m_id in enumerate(ids)
+            }
+        # some default styles
+        styles = [
+            "".join(f".n{u} > .sym {{fill: cyan}}" for u in tracked_nodes),
+            ".lab.summary {font-size: 12px}", 
+            ".polytomy {font-size: 10px}",
+            ".mut .lab {font-size: 10px}",
+            ".y-axis .lab {font-size: 12px}",
+            ".mut .lab {fill: darkred} .mut .sym {stroke: darkred} .background path {fill: white}"
+        ]
+        if len(multiple_mutations) > 0:
+            lab_css = ", ".join(f".mut.m{m} .lab" for m in multiple_mutations)
+            sym_css = ", ".join(f".mut.m{m} .sym" for m in multiple_mutations)
+            styles.append(lab_css + "{fill: red}" + sym_css + "{stroke: red}")
+        if len(reverted_mutations) > 0:
+            lab_css = ", ".join(f".mut.m{m} .lab" for m in reverted_mutations)
+            sym_css = ", ".join(f".mut.m{m} .sym" for m in reverted_mutations)
+            styles.append(lab_css + "{fill: magenta}" + sym_css + "{stroke: magenta}")
+
+        return tree.draw_svg(
+            time_scale=time_scale,
+            y_axis=True,
+            x_axis=False,
+            title=title,
+            size=size,
+            order=order,
+            mutation_labels=mutation_labels,
+            all_edge_mutations=True,
+            symbol_size=4,
+            pack_untracked_polytomies=pack_untracked_polytomies,
+            style="".join(styles) + style,
+            **kwargs,
+        )
+
     def get_sample_group_info(self, group_id):
         samples = []