群体遗传学在进化论中起着重要作用.它分析了物种之间以及同一物种中两个或更多个体之间的遗传差异.
Biopython为群体遗传学提供Bio.PopGen模块，主要支持GenePop，一种开发的流行遗传学包作者:Michel Raymond和Francois Rousset.
让我们编写一个简单的应用程序来解析GenePop格式并理解这个概念.
从下面给出的链接下载Biopython团队提供的genePop文件 : https://raw.githubusercontent.com/biopython/biopython/master/Tests/PopGen/c3line.gen
使用以下代码片段加载GenePop模块 : ;
from Bio.PopGen import GenePop
使用解析文件GenePop.read方法如下 :
record = GenePop.read(open("c3l") ine.gen"))显示下面给出的基因座和人口信息 :
>>> record.loci_list
['136255903', '136257048', '136257636']
>>> record.pop_list
['4', 'b3', '5']
>>> record.populations
[[('1', [(3, 3), (4, 4), (2, 2)]), ('2', [(3, 3), (3, 4), (2, 2)]),
('3', [(3, 3), (4, 4), (2, 2)]), ('4', [(3, 3), (4, 3), (None, None)])],
[('b1', [(None, None), (4, 4), (2, 2)]), ('b2', [(None, None), (4, 4), (2, 2)]),
('b3', [(None, None), (4, 4), (2, 2)])],
[('1', [(3, 3), (4, 4), (2, 2)]), ('2', [(3, 3), (1, 4), (2, 2)]),
('3', [(3, 2), (1, 1), (2, 2)]), ('4',
[(None, None), (4, 4), (2, 2)]), ('5', [(3, 3), (4, 4), (2, 2)])]]
>>>这里，文件中有三个基因座和三组人口:第一个人口有4个记录，第二个人口有3个记录，第三个人口有5个记录. record.populations显示每个基因座的所有人群和等位基因数据.
Biopython提供删除基因座和群体数据的选项.
删除按位置设置的人口，
>>> record.remove_population(0)
>>> record.populations
[[('b1', [(None, None), (4, 4), (2, 2)]),
('b2', [(None, None), (4, 4), (2, 2)]),
('b3', [(None, None), (4, 4), (2, 2)])],
[('1', [(3, 3), (4, 4), (2, 2)]),
('2', [(3, 3), (1, 4), (2, 2)]),
('3', [(3, 2), (1, 1), (2, 2)]),
('4', [(None, None), (4, 4), (2, 2)]),
('5', [(3, 3), (4, 4), (2, 2)])]]
>>>按位置删除基因座，
>>> record.remove_locus_by_position(0)
>>> record.loci_list
['136257048', '136257636']
>>> record.populations
[[('b1', [(4, 4), (2, 2)]), ('b2', [(4, 4), (2, 2)]), ('b3', [(4, 4), (2, 2)])],
[('1', [(4, 4), (2, 2)]), ('2', [(1, 4), (2, 2)]),
('3', [(1, 1), (2, 2)]), ('4', [(4, 4), (2, 2)]), ('5', [(4, 4), (2, 2)])]]
>>>按名称删除基因座，
>>> record.remove_locus_by_name('136257636') >>> record.loci_list
['136257048']
>>> record.populations
[[('b1', [(4, 4)]), ('b2', [(4, 4)]), ('b3', [(4, 4)])],
[('1', [(4, 4)]), ('2', [(1, 4)]),
('3', [(1, 1)]), ('4', [(4, 4)]), ('5', [(4, 4)])]]
>>>Biopython提供与GenePop软件交互的接口，从而从中暴露出许多功能. Bio.PopGen.GenePop模块用于此目的.一个这样易于使用的界面是EasyController.让我们检查如何解析GenePop文件并使用EasyController进行一些分析.
首先，安装GenePop软件并将安装文件夹放在系统路径中.要获取有关GenePop文件的基本信息，请创建一个EasyController对象，然后按照以下指定调用get_basic_info方法 :
>>> from Bio.PopGen.GenePop.EasyController import EasyController
>>> ec = EasyController('c3line.gen')
>>> print(ec.get_basic_info())
(['4', 'b3', '5'], ['136255903', '136257048', '136257636'])
>>>这里，第一项是人口清单，第二项是基因座清单.
获取所有等位基因列表一个特定的基因座，通过传递下面指定的轨迹名称来调用get_alleles_all_pops方法 :
>>> allele_list = ec.get_alleles_all_pops("136255903")
>>> print(allele_list)
[2, 3]要获得特定人群和基因座的等位基因列表，请通过传递基因座名称和人口位置来调用get_alleles如下所示 :
>>> allele_list = ec.get_alleles(0, "136255903") >>> print(allele_list) [] >>> allele_list = ec.get_alleles(1, "136255903") >>> print(allele_list) [] >>> allele_list = ec.get_alleles(2, "136255903") >>> print(allele_list) [2, 3] >>>
类似地，EasyController暴露了许多功能:等位基因频率，基因型频率，多位置F统计，Hardy-Weinberg平衡，连锁不平衡等.
