Computing a consensus chronogram from MT trees

Reading all 100 trees computed by Gergely from replicates of 1% of the transfer-based constraints.



In [1]:

    
import sys
from ete3 import Tree, TreeStyle, NodeStyle
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math

fileT = "100.trees" 
try:
    f=open(fileT, 'r')
except IOError:
    print ("Unknown file: " + fileT)
    sys.exit()

allTrees = list()
for l in f:
    allTrees.append( Tree( l.strip() ) )

Node ids are consistent across all trees.

Getting node Heights.



In [17]:

    
#File where I store useful functions
exec (open("/Users/boussau/Programs/PythonCode/functions.py").read ())

id2Heights=list()
for t in allTrees:
    node2Height,id2Height = getNodeHeights( t )
    id2Heights.append(id2Height)

Now we have the node heights.

Outputting the consensus chronogram, with confidence intervals.



In [18]:

    
print(len(id2Heights))
# Creating a uniform weight vector
weights = [1] * len(id2Heights)
outputsWeightedChronogram (allTrees[0].copy(), id2Heights, "consensus100MT", weights)



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