關(guān)鍵詞：互作，弦圖，python
摘要：本帖分享的是簡單的弦圖實(shí)現(xiàn)

#輸入數(shù)據(jù)每列意義："基因/蛋白","互作基因/互作蛋白","第一列基因分類","pvalue","color（同一分類顏色一致）"
gene1   gene2   fam1    0.5     red
gene2   gene3   fam1    1       red
gene3   gene1   fam2    0.1     blue
gene4   gene5   fam2    0.3     blue
gene5   gene2   fam2    0.9     blue
gene6   gene3   fam3    1.8     green
gene7   gene1   fam3    1.771428571     green
gene8   gene5   fam3    1.742857143     green
gene9   gene2   fam3    1.714285714     green
gene10  gene3   fam5    1.685714286     gold
gene11  gene1   fam5    1.657142857     gold
gene12  gene3   fam5    1.628571429     gold
gene13  gene1   fam5    1.6     gold
gene14  gene5   fam5    1.571428571     gold
gene15  gene2   fam4    1.542857143     orange
gene16  gene3   fam4    1.514285714     orange
gene17  gene1   fam4    1.485714286     orange
gene18  gene5   fam4    1.457142857     orange
gene19  gene2   fam4    1.428571429     orange
gene20  gene3   fam4    1.4     orange
cell1   cell2   fam3    0.7     green
cell2   cell1   fam3    0.2     green
cell3   cell4   fam3    5       green
cell4   cell6   fam6    0.7     grey
cell5   cell6   fam6    0.1     grey
cell6   cell4   fam6    0.3     grey
cell7   cell4   fam6    2       grey

#############################################代碼#############################################
#Usage:python gene_act.py 半徑（10） gene_act.xls（上述輸入文件） gene_act1.pdf（輸出文件）

import sys
import numpy as np
import matplotlib.pyplot as plt
from collections import defaultdict
import seaborn as sns
import pandas as pd


def getB(i):
    t = np.math.factorial(n)*init_t**i*(1-init_t)**(n-i)/(np.math.factorial(i)*np.math.factorial(n-i))
    return np.array([t,t]).T

#數(shù)據(jù)導(dǎo)入
r=float(sys.argv[1])
inputfile = sys.argv[2]
outpdf = sys.argv[3]

head_lst=["gene","act_gene","family","pvalue","color"]
df = pd.read_csv(inputfile, names=head_lst, header=None, sep="\t")
df = df.sort_values(by=['family', 'pvalue'], ascending=[True, True]).reset_index(drop=True)
famlist=df["family"].drop_duplicates().to_list()

#均分角度，計(jì)算X，y坐標(biāo)
sample_angle = np.linspace(0, 2 * np.pi, len(df) + len(famlist), endpoint=False)
circles = []
x = r * np.cos(sample_angle)
y = r * np.sin(sample_angle)
t = sample_angle * 180 /np.pi
circles.append(np.c_[x, y, t])
data = pd.DataFrame(circles[0],columns=['X','Y','angle'])
space_index = []
fam_len = 0
for i in famlist:
    if fam_len == 0:
        fam_len = df[df["family"] == i].shape[0]
    else:
        fam_len = fam_len + df[df["family"] == i].shape[0] + 1
    space_index.append(fam_len)
data=data.drop(space_index).reset_index(drop=True)
fig, ax = plt.subplots()
plt.rcParams['pdf.fonttype'] = 42
plt.rcParams['ps.fonttype'] = 42
plt.ylim(-2.5*r,2*r)
plt.xlim(-2.5*r,2*r)
# plt.legend(loc='upper left')


cmap = []
#添加數(shù)據(jù)
df.loc[:, 'X'] = data["X"]
df.loc[:, 'Y'] = data["Y"]
df.loc[:, 'angle'] = data["angle"]
end_x = []
end_y = []
end_xy = defaultdict(list)
start_x = []
start_y = []
for i in range(0,df.shape[0]):
    s_x = df.iloc[i,-3]
    s_y = df.iloc[i,-2]
    Color = df.iloc[i,-4]
    if Color not in cmap:
        cmap.append(Color)
    line = df.iloc[i,3]
    for act in df.iloc[i,1].split(","):
        e_x = df[df["gene"] == act].iloc[0,-3]
        e_y = df[df["gene"] == act].iloc[0,-2]
        points = np.array([[s_x,s_y],[0,0],[e_x,e_y]])# 在此處修改坐標(biāo)
        n = points.shape[0]-1
        init_t = np.linspace(0,1,1000)
        P = np.zeros((1000,2))
        for i in range(n+1):
            P += getB(i)*points[i]
        plt.plot(P[:,0],P[:,1],marker="None",color=Color,zorder=0,linewidth=line)
        plt.plot(points[:,0],points[:,1],'r.',zorder=0,alpha=0,linewidth=line)

df.to_csv("test.out",sep = "\t")
plt.rcParams['pdf.fonttype'] = 42
plt.rcParams['ps.fonttype'] = 42
plt.ylim(-1.5*r,1.5*r)
plt.xlim(-1.5*r,1.5*r)
sns.scatterplot(data=df, x="X", y="Y", size="pvalue", hue="family",hue_order=famlist,alpha=1,zorder=3,cmap=cmap)
for i in range(0,df.shape[0]):
    ax.text(df.iloc[i,-3] * 1.5, df.iloc[i,-2]* 1.5, df.iloc[i,0],ha="center",va="center",rotation=df.iloc[i,-1], color=df.iloc[i,-4],size=10,zorder=3)
ax.axis('off')
ax.set_aspect('equal')
ax.margins(x=0.1, y=0.1)
plt.legend(loc='upper left',ncol=2,prop={'size':5})
plt.savefig(outpdf)
plt.close()

結(jié)果圖展示