Trees from bipartitions files

In [1]:
from Bio import Phylo
import matplotlib.pyplot as plt
%matplotlib inline
import matplotlib
plt.rcParams["figure.figsize"] = [12,9]

ipyrad_reftree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bipartitions.ipyrad-reference-empirical"
stackstree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bipartitions.stacks-empirical"
ddocenttree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bipartitions.ddocent-empirical"
ipyrad_minustree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bipartitions.ipyrad-denovo_minus_reference-empirical"
ipyrad_plustree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bipartitions.ipyrad-denovo_plus_reference-095-empirical"
treefiles = {"ipyrad-reference":ipyrad_reftree, "stacks":stackstree,\
             "ddocent":ddocenttree, "ipyrad-denovo-minus":ipyrad_minustree,\
             "ipyrad-denovo-plus":ipyrad_plustree}

## empirical
emp_pops = {}
emp_sample_names = []
popfile = "/home/iovercast/manuscript-analysis/Phocoena_empirical/stacks/popmap.txt"
with open(popfile) as infile:
    lines = [l.strip().split() for l in infile.readlines()]
    emp_sample_names = [x[0] for x in lines]
    pops = set([x[1] for x in lines])
    for pop in pops: emp_pops[pop] = []
    for line in lines:
        p = line[1]
        s = line[0]
        emp_pops[p].append(s)
emp_pop_colors = {k:v for (k,v) in zip(emp_pops, list(matplotlib.colors.cnames))}
#print(emp_pop_colors)
#print(emp_pops)

emp_colors_per_sample = {}
for samp in emp_sample_names:
    for pop in emp_pops:
        if samp in emp_pops[pop]:
            emp_colors_per_sample[samp] = emp_pop_colors[pop]
#print(emp_colors_per_sample)

legend_colors = [matplotlib.patches.Patch(color=v, label=k) for k,v in emp_pop_colors.items()]

## Root the tree on the WBS pop
outgroup = [{'name': taxon_name} for taxon_name in emp_pops["WBS"]]

f, axarr = plt.subplots(5, 1, figsize=(10, 30), dpi=1000)
#axarr = [a for b in axarr for a in b]

for name, ax in zip(treefiles.keys(), axarr):
    print(name, ax)
    tree = Phylo.read(treefiles[name], 'newick')
    tree.root_with_outgroup(*outgroup)

    tree.ladderize()
    ## This could be cool but doesn't work
    Phylo.draw(tree, axes=ax, label_colors=emp_colors_per_sample, do_show=False)
    ax.set_title(name)
    ax.legend(handles=legend_colors, loc="lower left")
#axarr[0].legend(handles=legend_colors)
('ddocent', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaadca774d0>)
('ipyrad-denovo-minus', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaadee75a90>)
('ipyrad-reference', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaadeef6f10>)
('ipyrad-denovo-plus', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaadef686d0>)
('stacks', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaadefea890>)

Trees from bestTree

In [30]:
from Bio import Phylo
import matplotlib.pyplot as plt
%matplotlib inline
import matplotlib
plt.rcParams["figure.figsize"] = [12,9]

ipyrad_reftree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bestTree.ipyrad-reference-empirical"
stackstree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bestTree.stacks-empirical"
ddocenttree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bestTree.ddocent-empirical"
ipyrad_minustree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bestTree.ipyrad-denovo_minus_reference-empirical"
ipyrad_plustree = "/home/iovercast/manuscript-analysis/Phocoena_empirical/raxml_outdir/RAxML_bestTree.ipyrad-denovo_plus_reference-095-empirical"
treefiles = {"ipyrad-reference":ipyrad_reftree, "stacks":stackstree,\
             "ddocent":ddocenttree, "ipyrad-denovo-minus":ipyrad_minustree,\
             "ipyrad-denovo-plus":ipyrad_plustree}

## empirical
emp_pops = {}
emp_sample_names = []
popfile = "/home/iovercast/manuscript-analysis/Phocoena_empirical/stacks/popmap.txt"
with open(popfile) as infile:
    lines = [l.strip().split() for l in infile.readlines()]
    emp_sample_names = [x[0] for x in lines]
    pops = set([x[1] for x in lines])
    for pop in pops: emp_pops[pop] = []
    for line in lines:
        p = line[1]
        s = line[0]
        emp_pops[p].append(s)
emp_pop_colors = {k:v for (k,v) in zip(emp_pops, list(matplotlib.colors.cnames))}
#print(emp_pop_colors)
#print(emp_pops)

emp_colors_per_sample = {}
for samp in emp_sample_names:
    for pop in emp_pops:
        if samp in emp_pops[pop]:
            emp_colors_per_sample[samp] = emp_pop_colors[pop]
#print(emp_colors_per_sample)

## Root the tree on the WBS pop
outgroup = [{'name': taxon_name} for taxon_name in emp_pops["WBS"]]

legend_colors = [matplotlib.patches.Patch(color=v, label=k) for k,v in emp_pop_colors.items()]

f, axarr = plt.subplots(5, 1, figsize=(10, 30), dpi=1000)
#axarr = [a for b in axarr for a in b]

for name, ax in zip(treefiles.keys(), axarr):
    print(name, ax)
    tree = Phylo.read(treefiles[name], 'newick')
    tree.root_with_outgroup(*outgroup)
    tree.ladderize()
    ## This could be cool but doesn't work
    Phylo.draw(tree, axes=ax, label_colors=emp_colors_per_sample, do_show=False)
    ax.set_title(name)
    ax.legend(handles=legend_colors, loc="lower left")
('ddocent', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaaf81bead0>)
('ipyrad-denovo-minus', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaaf835a1d0>)
('ipyrad-reference', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaaf834bb90>)
('ipyrad-denovo-plus', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaaf82d4b10>)
('stacks', <matplotlib.axes._subplots.AxesSubplot object at 0x2aaaf855b310>)