https://mp.weixin.qq.com/s/HVFY5vu2IQT40zC0oXrNuA

系统发生树

定义

系统发生树（phylogenetic tree）是表明被认为具有共同祖先的各物种相互间演化关系的树

分类

• 是否有根？
  • 有根树：具有方向的树
  • 无根树：没有方向，其中线段的两个演化方向都有可能

• 基因树和物种树

构建方法

计算的精度和时间均依次增大

• 非加权分组平均法：UPGAM（Unweighted pair group method with arithmetic mean）
• 矩阵法：邻接法 neighbor-joining (NJ)
• 简约法：最大简约法 maximum parsimony (MP)
• 似然法：最大似然法 maximum likelihood (ML)
• 后验概率法：贝叶斯法 Bayesian

用什么序列建树？

• 如果DNA序列两两间一致度大于70%，选用DNA序列

• 低于70%选用蛋白质序列或DNA序列

What is the difference between a guide tree and a true phylogenetic tree?

A guide tree is calculated based on the distance matrix that is generated from the pairwise scores. The output can be found in the .dnd file. A phylogenetic tree is calculated based on the multiple alignment that it receives. The distances between the sequences in the alignment are calculated and can be found in the .ph file. These distances are then used by the method chosen (nj, phylip, dist) to make the phylogenetic tree (.nj, .ph, .dst file).

---

from Bio import SeqIO

## 读入序列数据`

covid = SeqIO.read('data/covid19.fasta', 'fasta')
sars = SeqIO.read('data/sars.fasta', 'fasta')
mers = SeqIO.read('data/mers.fasta', 'fasta')
ebola = SeqIO.read('data/ebola.fasta', 'fasta')

## 合并文件
all_virus = [covid, sars, mers, ebola]
SeqIO.write(all_virus, 'data/all_virus.fasta', 'fasta')


## 数据来源 GenBank
## 打印数据信息
for i in all_virus:
    print('%s\t%s' % (i.id, i.description))

> NC_045512.2 NC_045512.2 Severe acute respiratory syndrome coronavirus 2 isolate Wuhan-Hu-1, complete genome
> NC_004718.3 NC_004718.3 SARS coronavirus Tor2, complete genome
> NC_019843.3 NC_019843.3 Middle East respiratory syndrome-related coronavirus isolate HCoV-EMC/2012, complete genome
> NC_002549.1 NC_002549.1 Zaire ebolavirus isolate Ebola virus/H.sapiens-tc/COD/1976/Yambuku-Mayinga, complete genome

Alignment 进行对齐/序列比对

from Bio.Align.Applications import ClustalwCommandline


cline = ClustalwCommandline('clustalw', infile='data/all_virus.fasta')
stdout, stderr = cline()

## 输出文件将保存在源路径下: all_virus.aln  all_virus.dnd%ls data

> all_virus.aln all_virus.fasta ebola.fasta sars.fasta
> all_virus.dnd covid19.fasta mers.fasta

## 可以用Bio.AlignIO读取输出结果
from Bio import AlignIO

align = AlignIO.read('data/all_virus.aln', 'clustal')

print(align)type(align)

> Alignment with 4 rows and 30972 columns
> ATTAAAGGTTTATACCTTCCCAGGTAACAAACCAACCAACTTTC…AAA NC_045512.2
> ATATTAGGTTTTTACCTACCCAGGAAA–AGCCAACCAACCT-C…— NC_004718.3
> -------GATTTAAGTGAATAGCTTGGCTATCTCACTTCCCCTC…— NC_019843.3
> --------------------------------------------…— NC_002549.1

> Bio.Align.MultipleSeqAlignment


## 写出为phylip格式
AlignIO.write(align, 'data/all_virus_align.phy', 'phylip')

## 可以用Bio.Phylo读取树文件
from Bio import Phylo

## clustalw 生成的 
guide treeguide_tree = Phylo.read('data/all_virus.dnd', 'newick')

Phylo.draw_ascii(guide_tree)

                           __________ NC_045512.2  ________________________| |                        |__________ NC_004718.3_| |___________________________________ NC_019843.3 | |_________________________________________________________________ NC_002549.1


## 建树
from Bio.Phylo.Applications import PhymlCommandline


## 调用Phyml，以ML法生成系统发生树
cmd = PhymlCommandline(input='data/all_virus_align.phy')out_log, err_log = cmd()

## 生成树文件和统计文件%
ls data | grep .txt

> all_virus_align.phy_phyml_stats.txt
> all_virus_align.phy_phyml_tree.txt

tree = Phylo.read('data/all_virus_align.phy_phyml_tree.txt', 'newick')

## 自定义
labellabels = {    covid.id[:10]: 'COVID-19',    sars.id[:10]: 'SARS',    mers.id[:10]: 'MERS',    ebola.id[:10]: 'EBOLA',    None: None}

Phylo.draw(tree, label_func=lambda a:labels[a.name])

---

其他

对齐和建树的时候，python分别调用了外部程序：clustalw和phyml，
可从bioconda安装：

conda install bioconda::clustalw

or

conda install -c bioconda phyml