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介绍
本教程是使用一个Python脚本来绘制马赛克图，用于可视化两个变量的频率分布。
数据
大家通过以下链接下载数据：
- 百度网盘链接：https://pan.baidu.com/s/1f1SyyvRfpNVO3sLYEblz1A
- 提取码: 请关注WX公zhong号_生信学习者_后台发送 复现msm 获取提取码
Python packages required
- Pandas
- SciPy
- Matplotlib
- statsmodels
Drawing a mosaic plot using mosaic_plot.py
使用一个Python脚本mosaic_plot.py，以及一个包含MSM 和 Non-MSM个体相关的物种的表格，这些物种被识别为革兰氏阴性或非革兰氏阴性，在two_variable_mosaic.tsv: ./data/two_variable_mosaic.tsv中。
mosaic_plot.pycodes
#!/usr/bin/env python"""
NAME: mosaic_plot.py
DESCRIPTION: mosaic_plot.py is a python script for visualizing proportions of data points along two variables.
"""import pandas as pd
from scipy.stats import fisher_exact
import matplotlib.pyplot as plt
from statsmodels.graphics.mosaicplot import mosaic
import matplotlib
import sys
import argparse
import textwrapdef make_mosaic_plot(two_variable_file, facecolor_dict, output_fig, font_style = "sans-serif,Arial"):font_family, font_type = font_style.split(",")matplotlib.rcParams['font.family'] = font_familymatplotlib.rcParams['font.sans-serif'] = font_typetwo_variable_df = pd.read_csv(two_variable_file, sep = "\t", index_col = False)features, variable1, variable2 = two_variable_df.columnscont_df = pd.crosstab(two_variable_df[variable1], two_variable_df[variable2])res = fisher_exact(cont_df, alternative = "two-sided")label_dict = {}for idx in cont_df.index.to_list():for col in cont_df.columns.to_list():label_dict[(idx, col)] = cont_df.loc[idx, col]labelizer = lambda k:label_dict[k]variable2_0, variable2_1 = sorted(set(two_variable_df[variable2].to_list()))props = {}for variable in facecolor_dict:props[(variable, variable2_0)] = {"facecolor": facecolor_dict[variable], "edgecolor": "white"}props[(variable, variable2_1)] = {"facecolor": facecolor_dict[variable], "edgecolor": "white"}mosaic(two_variable_df, [variable1, variable2], labelizer = labelizer, properties = props, title = " P-value: "+ str(res[1]) + " (Fisher's exact test)")plt.savefig(output_fig)if __name__ == "__main__":def read_args(args):# This function is to parse argumentsparser = argparse.ArgumentParser(formatter_class=argparse.RawDescriptionHelpFormatter,description = textwrap.dedent('''\This program is to draw a mosaic plot.'''),epilog = textwrap.dedent('''\examples: mosaic_plot.py --input input_file.tsv --facecolor_map facecolor_mapfile.tsv --output mosaic_plot.png '''))parser.add_argument('--input',nargs = '?',help = 'Input a file containing two variable information regarding each individual subject.',type = str,default = None)parser.add_argument('--facecolor_map',nargs = '?',help = 'Specify the the pathway to SCFA metabolisms database. default: /vol/projects/khuang/databases/SCFA/SCFA_pathways.tsv',default = '/vol/projects/khuang/databases/SCFA/SCFA_pathways.tsv')parser.add_argument('--font_style',nargs = '?',help = 'Specify the font style, font family and font type is delimited by a comma. default: [sans-serif,Arial]',default = 'sans-serif,Arial')parser.add_argument('--output',nargs = '?',help = 'Specify the output figure name.',type = str,default = None)return vars(parser.parse_args())pars = read_args(sys.argv)facecolor_dict = {i.rstrip().split("\t")[0]: i.rstrip().split("\t")[1] for i in open(pars['facecolor_map']).readlines()}make_mosaic_plot(pars["input"], facecolor_dict , pars["output"], font_style = pars["font_style"])
- Usage:
mosaic_plot.py [-h] [--input [INPUT]] [--facecolor_map [FACECOLOR_MAP]] [--font_style [FONT_STYLE]] [--output [OUTPUT]]This program is to draw a mosaic plot.optional arguments:-h, --help show this help message and exit--input [INPUT] Input a file containing two variable information regarding each individual subject.--facecolor_map [FACECOLOR_MAP]Specify the the pathway to SCFA metabolisms database. default: /vol/projects/khuang/databases/SCFA/SCFA_pathways.tsv--font_style [FONT_STYLE]Specify the font style, font family and font type is delimited by a comma. default: [sans-serif,Arial]--output [OUTPUT] Specify the output figure name.examples: python mosaic_plot.py --input input_file.tsv --facecolor_map facecolor_mapfile.tsv --output mosaic_plot.png
示例命令:
python mosaic_plot.py \--input two_variable_mosaic.tsv \--facecolor_map facecolor_map.tsv \--output mosaic_plot.png
Note
马赛克图的面颜色应该按照示例中的映射文件mapping file: ./data/facecolor_map.tsv来指定。
