Come creare una trama di Manhattan con matplotlib in python?

Question

Purtroppo, non ho trovato una soluzione da solo. Come creare un Manhattan plot all'interno di python usando, ad esempio, matplotlib/panda. Il problema è che in questi grafici l'asse x è discreto.

from pandas import DataFrame 
from scipy.stats import uniform 
from scipy.stats import randint 
import numpy as np 

# some sample data 
df = DataFrame({'gene' : ['gene-%i' % i for i in np.arange(1000)], 
'pvalue' : uniform.rvs(size=1000), 
'chromosome' : ['ch-%i' % i for i in randint.rvs(0,12,size=1000)]}) 

# -log_10(pvalue) 
df['minuslog10pvalue'] = -np.log10(df.pvalue) 
df = df.sort_values('chromosome') 

# How to plot gene vs. -log10(pvalue) and colour it by chromosome? 

Answer 1

si può usare qualcosa di simile:

from pandas import DataFrame 
from scipy.stats import uniform 
from scipy.stats import randint 
import numpy as np 
import matplotlib.pyplot as plt 

# some sample data 
df = DataFrame({'gene' : ['gene-%i' % i for i in np.arange(10000)], 
'pvalue' : uniform.rvs(size=10000), 
'chromosome' : ['ch-%i' % i for i in randint.rvs(0,12,size=10000)]}) 

# -log_10(pvalue) 
df['minuslog10pvalue'] = -np.log10(df.pvalue) 
df.chromosome = df.chromosome.astype('category') 
df.chromosome = df.chromosome.cat.set_categories(['ch-%i' % i for i in range(12)], ordered=True) 
df = df.sort_values('chromosome') 

# How to plot gene vs. -log10(pvalue) and colour it by chromosome? 
df['ind'] = range(len(df)) 
df_grouped = df.groupby(('chromosome')) 

fig = plt.figure() 
ax = fig.add_subplot(111) 
colors = ['red','green','blue', 'yellow'] 
x_labels = [] 
x_labels_pos = [] 
for num, (name, group) in enumerate(df_grouped): 
    group.plot(kind='scatter', x='ind', y='minuslog10pvalue',color=colors[num % len(colors)], ax=ax) 
    x_labels.append(name) 
    x_labels_pos.append((group['ind'].iloc[-1] - (group['ind'].iloc[-1] - group['ind'].iloc[0])/2)) 
ax.set_xticks(x_labels_pos) 
ax.set_xticklabels(x_labels) 
ax.set_xlim([0, len(df)]) 
ax.set_ylim([0, 3.5]) 
ax.set_xlabel('Chromosome') 

Ho appena creato una colonna in più di correre dell'indice di avere il controllo sulla x etichette posizioni.

Answer 2

import matplotlib.pyplot als plt 
from numpy.random import randn, random_sample 

g = random_sample(int(1e5))*10 # uniform random values between 0 and 10 
p = abs(randn(int(1e5))) # abs of normally distributed data 

""" 
plot g vs p in groups with different colors 
colors are cycled automatically by matplotlib 
use another colormap or define own colors for a different cycle 
""" 
for i in range(1,11): 
    plt.plot(g[abs(g-i)<1], p[abs(g-i)<1], ls='', marker='.') 

plt.show() 

Si può anche verificare this script, che sembra offrire una soluzione completa al problema.