ETE for phylogenetic analysis

ETE能做什么

A Python framework for the construction, analysis and visualization of trees.

Default output

安装和使用

  • conda安装

    # Install Minconda  (you can ignore this step if you already have Anaconda/Miniconda)
    wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O Miniconda-latest-Linux-x86_64.sh
    bash Miniconda-latest-Linux-x86_64.sh -b -p ~/anaconda/
    export PATH=~/anaconda/bin:$PATH;
      
    # Install ETE
    conda install -c etetoolkit ete3 ete3_external_apps
      
    # Check installation
    ete3 version
    ete3 build check
    
  • github源码安装

    wget https://github.com/etetoolkit/ete/archive/master.zip -O ete3.20160719.zip
    unzip ete3.20160719.zip
    python setup.py install
    yum install python-six.noarch
    ete3 upgrade-external-tools
    

ETE运行

  • 输入序列
    • 输入序列为标准的fasta格式文件,名字可以为任意形式
    • 如果需要在序列名字中区分物种信息,fasta序列名需满足 SpeciesCode_SequenceName例如HUMAN_p53 = HUMAN, p53。 可以通过参数--spname-delimiter指定使用其它字符作为分隔符。
  • ete预先定义了多个流程用以完成从原始fasta序列到后续进化树生成的各个步骤。

    运行以下命令可以列出系统自带的流程及其解释

    ete3 build workflows genetree
    
  • 使用既定流程最简单运行

    -w指定所用的流程,-a指定输入序列,--tools-dir指定安装的外部程序的路径

    ete3 build -w standard_fasttree -a diTPS.prot.fa -o standard_fasttree 
      	--tools-dir /root/.etetoolkit/ext_apps-latest/
    
  • 自己定制流程
    • 获取可以定制的各部分命令

      ete3 build apps
      
    • 选择预定义好的模块,如tree builders: phyml_default_bootstrap, aligners: mafft_einsi, model testers: pmodeltest_full_slow, alg cleaners: trimal_gappyout.

    • 流程定制模板: 顺序为aligner-trimmer-model_tester-builder
      • totally 4 parts included as stated above, multiple sequence alignment, trimming MSA results, select best model, use appropriate softwares to build tree.
      • - represents command separator
      • none represents skipping related operations
    • 基于我们的选择定制的流程mafft_einsi-trimal_gappyout-pmodeltest_full_slow-phyml_default_bootstrap

      ete3 build -w mafft_einsi-trimal_gappyout-pmodeltest_full_slow-phyml_default_bootstrap
         -a diTPS.prot.fa -o custom_phymltree
      
    • -w可以接受多个流程(空格分开),进而得到不同的比对工具、处理方式和建树工具 输出的多个结果,可以通过ete3 compare比较这些结果的吻合度, 比如 Robinson-Foulds距离等。

      ete3 compare -r newtree1.nwq -t "tree2.nw tree3.nw tree4.nw" --unrooted
      
      # Tree file can be got using find
      find custom_phymltree -name *.nw
      
    • 定制不同的分析模块
      • 查看已有分析模块的定义

        ete3 build show phyml_default
        
        [phyml_default]
           _desc = Phyml tree using +G+I+F, 4 classes and aLRT branch supports. Default models JTT/GTR
           _app = phyml
           _aa_model = JTT
           -nt_model = GTR
              --pinv = e
             --alpha = e
          --nclasses = 4
                  -o = tlr
                  -f = m
         --bootstrap = -2
        
      • 修改部分定义获得新的模块

        ete3 build show phyml_default >customized.config
        
        ## 修改后的customized.config
        			
        [phyml_bootstrap_100]
                _desc = Phyml tree using +G+I+F, 4 classes and aLRT branch supports. Default models JTT/GTR
                 _app = phyml
            _aa_model = JTT
            -nt_model = GTR
               --pinv = e
              --alpha = e
           --nclasses = 4
                   -o = tlr
                   -f = m
          --bootstrap = 100
         [trimal_auto]
         	      _desc = trimal alignment cleaning using auto algorithm
           	      _app  = trimal
          -automated1 = 
        
        ## 使用新定义的模块
        ete3 build -a diTPS.prot.fa --clearall -o phyml_bootstrap_100 -w
        mafft_einsi-trimal_auto-none-phyml_bootstrap_100 -c customized.cfg --cpu 5
        
  • 氨基酸比对指导核苷酸比对的进化树构建 (要求氨基酸序列与核苷酸序列名字一一对应,核苷酸序列可以含有终止密码子,最终获得的核苷酸比对序列存储在*.used_alg.fa文件中。)

    ete3 build -a diTPS.prot.fa -n diTPS.nucl.fa -o aa2nt 
       -w standard_fasttree --clearall --nt-switch-threshold 0.9
       -C 20
    
  • 使用预先比对好的序列, 使用none代替aligner

    ete3 build -a diTPS.prot.aln.fa -w none-none-none-fasttree
       -o manual_alg --clearall
    
  • 设置树的根节点

    from ete3 import Tree
      
    tree = Tree('tree.nw')
    
    root = 'one_node_name'
    tree.set_outgroup(root)
    
    #use mid-point as root
    mid = tree.get_midpoint_outgroup()
    tree.set_outgroup(mid)
      
    tree.write('tree.rooted.nw')
    tree.render('tree.rooted.pdf')
    

问题解决

  • ETE: cannot connect to X server 如果程序运行出现错误ETE: cannot connect to X server则安装Xvfb, 并运行 xvfb-run ete3取代ete3, 后面的代码不变。

    yum install xorg-x11-server-Xvfb.x86_64
    xvfb-run ete3 build -w standard_fasttree -a diTPS.prot.fa -o standard_fasttree 
    
  • ETE: cannot connect to X server (solve in python script or jupyter ref)

    • Install xvfbwrapper using pip install xvfbwrapper
    # Add the following 4 lines at the beginning of python code 
    # or the first cell in Jupyter
    from xvfbwrapper import Xvfb
    
    vdisplay = Xvfb()
    vdisplay.start()
    	
    # launch stuff inside virtual display here
    # other python codes here
      
    # Add this line at the end of python code
    # or the last cell in Jupyter
    vdisplay.stop()
    
  • External applications directory are not found 指定ETE使用的工具的安装路径;一般发生在普通用户使用根用户编译的ETE时。

    --tools-dir /root/.etetoolkit/ext_apps-latest/
    

Tree annotation

# A virtual X-server XVFB is used in case you do not have X-server
from xvfbwrapper import Xvfb

vdisplay = Xvfb()
vdisplay.start()

# launch stuff inside virtual display here

#vdisplay.stop()


from ete3 import Tree, faces, TreeStyle, NodeStyle
from ete3 import ClusterTree, RectFace, AttrFace, ProfileFace, TextFace
from ete3.treeview.faces import add_face_to_node
import pandas as pd
import numpy as np
import colorsys

The most simple way of showing a tree.

t = Tree()
t.populate(7,names_library=['A','B','C','D','E','F','G'])
## %%liline is used for showing plots in ipythonnotebook.
## t.render(file_name="tree.pdf") # will save tree into pdf file
t.render(file_name="%%inline")

png

Get the randomly generated tree in newick format and save to a string variable which can be read using Tree() function.

t_str = t.write(outfile=None, format=0)
t_str

'(((B:1,A:1)1:1,(G:1,F:1)1:1)1:1,(E:1,(D:1,C:1)1:1)1:1);'
t = Tree(t_str)
ts = TreeStyle()
ts.show_leaf_name = True
ts.show_branch_length = True
ts.show_branch_support = True
t.render(file_name="%%inline", tree_style=ts)

png

Get the randomly generated tree in newick format and save to file which can also be read using Tree() function.

t.write(outfile="tree.nw", format=0)
t = Tree("tree.nw")
ts.mode = "c"
ts.arc_start = -180 # 0 degrees = 3 o'clock
ts.arc_span = 180
t.render(file_name="%%inline", w=500, tree_style=ts)

png

设置根节点、叶节点和中间节点的属性

ts = TreeStyle()
ts.show_leaf_name = True
ts.show_branch_length = True
ts.show_branch_support = True

# Draws nodes as small red spheres of diameter equal to 10 pixels
for n in t.traverse():  # Traverse each node and set attribute for each type of nodes
	if n.is_leaf(): # Decide if leaf node
		nstyle = NodeStyle()
		nstyle["shape"] = "sphere"
		nstyle["size"] = 10
		nstyle["fgcolor"] = "darkred"
		n.set_style(nstyle)
	else:
		nstyle = NodeStyle()
		nstyle["shape"] = "square"
		nstyle["size"] = 15
		nstyle["fgcolor"] = "orange"
		n.set_style(nstyle)        

t.img_style["size"] = 30
t.img_style["fgcolor"] = "blue"
	
t.render(file_name="%%inline", w=500, tree_style=ts)

png

修改节点的名字

t = Tree(t_str)

nameMap = {'A': 'American', 'B': 'Britain', 'C':'China', 
		   'D':'Dutch', 'E':'Egypt','F':'France','G':'German'}

ts = TreeStyle()
ts.show_leaf_name = False
ts.show_branch_length = True
ts.show_branch_support = True

# Creates my own layout function. I will use all previously created
# faces and will set different node styles depending on the type of
# node.
def mylayout(node):   
	# If node is a leaf, add the nodes name and a its scientific
	# name
	if node.is_leaf():
		# We can also create faces on the fly
		newName = nameMap.get(node.name, node.name)
		newNameFace = faces.TextFace(newName)
		faces.add_face_to_node(newNameFace, node, column=1, aligned=True)

		# Sets the style of leaf nodes
		node.img_style["size"] = 12
		node.img_style["shape"] = "sphere"
		node.img_style["fgcolor"] = "blue"
	#If node is an internal node
	else:
		# Sets the style of internal nodes
		node.img_style["size"] = 1
		node.img_style["shape"] = "circle"
		node.img_style["fgcolor"] = "darkred"

ts.layout_fn = mylayout

t.img_style["size"] = 30
t.img_style["fgcolor"] = "black"
	
t.render(file_name="%%inline", w=600, tree_style=ts)

png

不同的节点设置不同的背景色,树枝的颜色

t = Tree(t_str)

nameMap = {'A': 'American', 'B': 'Britain', 'C':'China', 
		   'D':'Dutch', 'E':'Egypt','F':'France','G':'German'}

colorMap = { 'American': '#ACFFFF',
			 'Britain': '#ACACFF',
			 'China': '#ACACAC',
			 'Dutch': '#59ACAC',
			 'Egypt': '#5959AC',
			 'France': '#595959',
			 'German': '#065959'}

ts = TreeStyle()
ts.show_leaf_name = False
ts.show_branch_length = True
ts.show_branch_support = True

# Creates my own layout function. I will use all previously created
# faces and will set different node styles depending on the type of
# node.
def mylayout(node):   
	#Change branch color
	node.img_style["hz_line_color"] = 'orange'  # change horizontal branch color 
	node.img_style["vt_line_color"] = 'red' # Change vertical branch color
	
	# If node is a leaf, add the nodes name and a its scientific
	# name
	if node.is_leaf():
		# We can also create faces on the fly
		newName = nameMap.get(node.name, node.name)
		newNameFace = faces.TextFace(newName)
		faces.add_face_to_node(newNameFace, node, column=1, aligned=True)

		# Sets the style of leaf nodes
		node.img_style["size"] = 12
		node.img_style["shape"] = "sphere"
		node.img_style["fgcolor"] = "blue"
		node.img_style["bgcolor"] = colorMap[newName]
		
		node.img_style["hz_line_color"] = 'blue'  # change branch color 
	#If node is an internal node
	else:
		# Sets the style of internal nodes
		node.img_style["size"] = 1
		node.img_style["shape"] = "circle"
		node.img_style["fgcolor"] = "darkred"

ts.layout_fn = mylayout

t.img_style["size"] = 30
t.img_style["fgcolor"] = "black"
	
t.render(file_name="%%inline",tree_style=ts)

png

树+热图(自定义颜色+列名字)

自定义热图函数,同时该函数也支持替换或新增节点的名字。

nameFace = AttrFace("name", fsize=12) #Set leaf node attribute

def setup_heatmap(tree, tree_style, header, center_value=0.0, nameMap ={}, nameLabel = '',
				  color_up=0.7, color_down=0.2, color_center="white"):
	DEFAULT_COLOR_SATURATION = 0.5
	BASE_LIGHTNESS = 0.7
	def gradient_color(value, max_value, saturation=0.5, hue=0.1):    
		def rgb2hex(rgb):
			return '#%02x%02x%02x' % rgb
		def hls2hex(h, l, s):
			return rgb2hex( tuple(map(lambda x: int(x*255), 
						  colorsys.hls_to_rgb(h, l, s))))
	
		lightness = 1 - (value * BASE_LIGHTNESS) / max_value
		return hls2hex(hue, lightness, DEFAULT_COLOR_SATURATION)


	# Calculate max gradient value from the ClusterTree matrix
	maxv = abs(center_value - tree.arraytable._matrix_max)
	minv = abs(center_value - tree.arraytable._matrix_min)
	if center_value <= tree.arraytable._matrix_min:
		MAX_VALUE = minv + maxv
	else:
		MAX_VALUE = max(maxv, minv)
		
	# Add heatmap colors to tree
	cols_add_before_heat = 0
	if nameMap:
		cols_add_before_heat = 1
	for lf in tree:
		if nameMap:
			longNameFace = faces.TextFace(nameMap.get(lf.name, lf.name))
			lf.add_face(longNameFace, column=0, position="aligned")
			
		for i, value in enumerate(getattr(lf, "profile", [])):
			if value > center_value:
				color = gradient_color(abs(center_value - value), MAX_VALUE, 
									   hue=color_up)
			elif value < center_value:
				color = gradient_color(abs(center_value - value), MAX_VALUE, 
									   hue=color_down)
			else:
				color = color_center
			lf.add_face(RectFace(20, 20, color, color), position="aligned", 
						column=i+cols_add_before_heat)
			# Uncomment to add numeric values to the matrix
			#lf.add_face(TextFace("%0.2f "%value, fsize=5), position="aligned", column=i)
		lf.add_face(nameFace, column=i+cols_add_before_heat+1, position="aligned")
		
	if nameMap and nameLabel:
		nameF = TextFace(nameLabel, fsize=7)
		#nameF.rotation = -90
		tree_style.aligned_header.add_face(nameF, column=0)
	# Add header 
	for i, name in enumerate(header):
		nameF = TextFace(name, fsize=7)
		nameF.rotation = -90
		tree_style.aligned_header.add_face(nameF, column=i+cols_add_before_heat)
 #-------------END setup_heatmap----------------------------------------------        

读入矩阵 (可把文后的测试矩阵存储到文件中读入)

矩阵需满足三个条件:

  • 矩阵为TAB键分割,第一行是每列的名字
  • 矩阵每一行第一列为行名字,与树的节点对应
  • 矩阵可以存储与一个文件中,也可以是如下的字符串
data = pd.read_table("matrix", header=0, index_col=0)
data.index.name = "#Names"  #修改第一行的名字使其符合ETE的要求
data_mat = data.to_csv(None, sep="\t", float_format="%.2f")
header = list(data.columns.values)  #获取列的名字用于标记

data
col1 col2 col3 col4 col5 col6 col7
#Names
A -1.23 -0.81 1.79 0.78 -0.42 -0.69 0.58
B -1.76 -0.94 1.16 0.36 0.41 -0.35 1.12
C -2.19 0.13 0.65 -0.51 0.52 1.04 0.36
D -1.22 -0.98 0.79 -0.76 -0.29 1.54 0.93
E -1.47 -0.83 0.85 0.07 -0.81 1.53 0.65
F -1.04 -1.11 0.87 -0.14 -0.80 1.74 0.48
G -1.57 -1.17 1.29 0.23 -0.20 1.17 0.26
data_mat
'#Names\tcol1\tcol2\tcol3\tcol4\tcol5\tcol6\tcol7\nA\t-1.23\t-0.81\t1.79\t0.78\t-0.42\t-0.69\t0.58\nB\t-1.76\t-0.94\t1.16\t0.36\t0.41\t-0.35\t1.12\nC\t-2.19\t0.13\t0.65\t-0.51\t0.52\t1.04\t0.36\nD\t-1.22\t-0.98\t0.79\t-0.76\t-0.29\t1.54\t0.93\nE\t-1.47\t-0.83\t0.85\t0.07\t-0.81\t1.53\t0.65\nF\t-1.04\t-1.11\t0.87\t-0.14\t-0.80\t1.74\t0.48\nG\t-1.57\t-1.17\t1.29\t0.23\t-0.20\t1.17\t0.26\n'
header
['col1', 'col2', 'col3', 'col4', 'col5', 'col6', 'col7']

调用函数绘制热图

t = ClusterTree(t_str, data_mat)

ts = TreeStyle()
ts.show_leaf_name = False
ts.show_branch_length = True
ts.show_branch_support = True

setup_heatmap(t, ts, header, center_value=0, color_up=0.9, color_down=0.3, color_center="white")

t.render(file_name="%%inline", tree_style=ts)

png

绘制热图时修改Layout

def mylayout_only(node):   
	#Change branch color
	node.img_style["hz_line_color"] = 'orange'  # change horizontal branch color 
	node.img_style["vt_line_color"] = 'red' # Change vertical branch color
	
	# If node is a leaf, add the nodes name and a its scientific
	# name
	if node.is_leaf():
		newName = nameMap.get(node.name)
		node.img_style["size"] = 12
		node.img_style["shape"] = "sphere"
		node.img_style["fgcolor"] = "blue"
		node.img_style["bgcolor"] = colorMap[newName]        
		node.img_style["hz_line_color"] = 'blue'  # change branch color 
	#If node is an internal node
	else:
		# Sets the style of internal nodes
		node.img_style["size"] = 1
		node.img_style["shape"] = "circle"
		node.img_style["fgcolor"] = "darkred"



t = ClusterTree(t_str, data_mat)

ts = TreeStyle()
ts.show_leaf_name = False
ts.show_branch_length = True
ts.show_branch_support = True
ts.layout_fn = mylayout_only

setup_heatmap(t, ts, header, center_value=0, color_up=0.9, color_down=0.3, 
			  color_center="white", nameMap=nameMap, nameLabel="Full")

t.render(file_name="%%inline", tree_style=ts)

png

测试矩阵

## 矩阵为TAB键分割
## 矩阵每一行第一列为行名字,与树的节点对应
## 矩阵可以存储于一个文件中,也可以是如下的字符串
matrix = """
#Names\tcol1\tcol2\tcol3\tcol4\tcol5\tcol6\tcol7
A\t-1.23\t-0.81\t1.79\t0.78\t-0.42\t-0.69\t0.58
B\t-1.76\t-0.94\t1.16\t0.36\t0.41\t-0.35\t1.12
C\t-2.19\t0.13\t0.65\t-0.51\t0.52\t1.04\t0.36
D\t-1.22\t-0.98\t0.79\t-0.76\t-0.29\t1.54\t0.93
E\t-1.47\t-0.83\t0.85\t0.07\t-0.81\t1.53\t0.65
F\t-1.04\t-1.11\t0.87\t-0.14\t-0.80\t1.74\t0.48
G\t-1.57\t-1.17\t1.29\t0.23\t-0.20\t1.17\t0.26
"""

产生颜色的辅助函数,给定一个列表,这个函数会自动返回一个字典包含每个字段对应的颜色。

def hex2rgb(hexcolor):
	return [(hexcolor>>16) & 0xff, (hexcolor>>8) & 0xff, hexcolor & 0xff]

def rgb2hex(rgbcolor):
	r, g, b = rgbcolor
	rgb = hex((r << 16) + (g << 8) +b)[2:].upper()
	zero = '0'* (6-len(rgb))
	return '#'+zero+rgb
#----------------------------------
def generateColor(labelL):
	labelL = list(set(labelL))
	labelL.sort()
	colorD = {}
	
	r = 255
	g = 255
	b = 255
	len_label = int(len(labelL) / 3 + 1)
	step = int(250 / len_label)
	
	cnt = 1
	for labels in labelL:
		if cnt % 3 == 1:
			r = r - step 
		elif cnt % 3 == 2:
			g = g -step
		else:
			b = b - step
		cnt += 1
		color = rgb2hex([r, g, b])
		colorD[labels] = color
	return colorD

clan_colorD = generateColor(nameMap.values())
clan_colorD

{'American': '#ACFFFF',
 'Britain': '#ACACFF',
 'China': '#ACACAC',
 'Dutch': '#59ACAC',
 'Egypt': '#5959AC',
 'France': '#595959',
 'German': '#065959'}

带有Support value的Newick树,供测试不同的属性使用

nw = """
(((Dre:0.008339,Dme:0.300613)1.000000:0.596401,
(Cfa:0.640858,Hsa:0.753230)1.000000:0.182035)1.000000:0.106234,
((Dre:0.271621,Cfa:0.046042)1.000000:0.953250,
(Hsa:0.061813,Mms:0.110769)1.000000:0.204419)1.000000:0.973467);

关闭Virtual X-server

vdisplay.stop()

Ipython notebook for easy usage

https://github.com/Tong-Chen/notebook/blob/master/ETE.ipynb

Reference

原文链接 http://blog.genesino.com//2016/07/ete/

CHENTONG
版权声明:本文为博主原创文章,转载请注明出处。
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CHENTONG

CHENTONG
积微,月不胜日,时不胜月,岁不胜时。凡人好敖慢小事,大事至,然后兴之务之。如是,则常不胜夫敦比于小事者矣!何也?小事之至也数,其悬日也博,其为积也大。大事之至也希,其悬日也浅,其为积也小。故善日者王,善时者霸,补漏者危,大荒者亡!故,王者敬日,霸者敬时,仅存之国危而后戚之。亡国至亡而后知亡,至死而后知死,亡国之祸败,不可胜悔也。霸者之善著也,可以时托也。王者之功名,不可胜日志也。财物货宝以大为重,政教功名者反是,能积微者速成。诗曰:德如毛,民鲜能克举之。此之谓也。

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