PAML 4.3版软件教程：最大似然法 phylogenetic analysis

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PAML (Phylogenetic Analysis by Maximum Likelihood) 是一款由 Ziheng Yang 开发的广泛应用于生物进化研究的软件。该软件专注于基于最大似然方法的系统发育分析，版本为4.3，发布于2009年9月。PAML用户手册详细介绍了其功能、用法和版权政策。 PAML的核心理念是通过统计学方法推断物种间的演化关系，这对于理解遗传多样性、基因功能和物种起源具有重要意义。该软件提供了一系列工具，包括模型拟合、分支长度估计、选择压力分析等，旨在帮助研究人员处理DNA或蛋白质序列数据，进行分子钟分析和比较方法的评估。使用PAML之前，用户应确保阅读并遵守版权协议，该软件是“原样提供”，没有任何形式的保修，但作者及其雇主不对使用过程中可能产生的任何损失或不便负责。PAML软件及其相关资源（包括源代码、示例数据集、可执行文件和文档）仅限于学术用途，并且在复制和使用时必须保留版权信息，不得收取费用。关于引用，推荐的标准格式包括： 1. Yang, Z. (1997). PAML: A program package for phylogenetic analysis by maximum likelihood. Computer Applications in BioSciences, 13: 555-556. 2. Yang, Z. (2007). PAML4: A program package for phylogenetic analysis by maximum likelihood. Molecular Biology and Evolution, 24: 1586-1591. 可以访问网站 <http://abacus.gene.ucl.ac.uk/software/paml.html> 查看最新的更新和已修复的错误。 PAML文档（doc/pam）还包含了软件的最新更改记录和已知问题解决方案，这对于跟踪新功能和解决潜在问题非常关键。用户在使用PAML进行实际研究时，不仅要熟悉软件操作界面，还要充分了解其理论基础和适用范围，以便得出准确可靠的生物学结论。随着科技的进步和软件的迭代更新，PAML不断优化，为生物学家们提供了强大的分析工具。

P A M L M A N U A L 8

1. Go to the PAML web site http://abacus.gene.ucl.ac.uk/software/paml.html and download the

lat

2. est archive and save on your hard disk. Unpack it using gzip, with a command like the

following (replace the version numbers and use the correct name for the archive file)

gzip –d paml4.tar.gz

tar xf paml4.tar

3. You can use ls to look at the files in the folder. Delete the Windows executables (.exe files) in the bin folder.

Then cd to the src/ folder to compile using make.

ls -lF bin (this should list the .exe files in the bin folder)

rm –r bin/*.exe

cd src

make

ls -lF

rm *.o

mv baseml basemlg codeml pamp evolver yn00 chi2 ../bin

cd ..

bin/codeml

4. Those commands compile the programs and generate executables called baseml, basemlg,

codeml, pamp, evolver, yn00, and chi2, which you can see with the ls command. Then

remove (rm) the intermediate object files *.o, and move (mv) the compiled executables into

bin/ folder in the PAML main folder (that is, ../bin from paml/src/). Then cd to the PAML

main folder and run codeml, using the default control file codeml.ctl. You can then print

out a copy of codeml.ctl and look at it (and the main result file mlc).

If the compilation (the make command) is unsuccessful, you might have to open and edit the file

Makefile before issuing the make command. For example, you can change cc to gcc and -fast to -

O3 or -O4. If that none of these works, look at the file readme.txt in the src/ folder for compiling

instructions. You can copy the compiling commands onto the command line. For example

cc –o baseml baseml.c tools.c –lm

cc –o codeml codeml.c tools.c -lm

would compile baseml and codeml using the C compiler cc. However, in this case code

optimization is not turned on. You should use compiler switches to optimize the code, say,

cc –o codeml –O3 codeml.c tools.c -lm

Finally, if your current folder is not on your search path, you will have to add ./ in front of the

executable file name even if the executable is in your current working folder; that is, use ./codeml

instead of codeml to run codeml.

Mac OS X

Since Mac OSX is UNIX, you should follow the instructions for UNIX above. Open a command

terminal (Applications-Utilities-Terminal) and then compile and run the programs from the terminal.

You cd to the paml/src/ folder and look at the readme.txt or Makefile files. See above. If you type

commands gcc or make and get a "Command not found" error, you will have to download the Apple

Developer ’s Toolkit at the Apple web site http://developer.apple.com/tools/. There are some notes

about running programs on MAC OS X or UNIX at the FAQ page.

I have stopped distributing executables for old MACs running OS 9 or earlier.

P A M L M A N U A L 9

Running a program

As indicated above, you run a program by typing its name from the command line. You should

know which folder your sequence file, tree file, and control file are, relative to your working folder.

If inexperienced, you may copy the executables to the folder containing your data files. Depending

on the model used, codeml may need a data file such as grantham.dat , dayhoff.dat ,

jones.dat

wag.dat

, m

tREV24.dat

, or

mtmam.dat

, so you should copy these files as well.

The programs produce result files, with names such as

rub

lnf

rst

, or

rates

. You should

not use these names for your own files as otherwise they will be overwritten.

Example data sets

The examples/ folder contains many example data sets. They were used in the original papers to

test the new methods, and I included them so that you could duplicate our results in the papers.

Sequence alignments, control files, and detailed readme files are included. They are intended to

help you get familiar with the input data formats and with interpretation of the results, and also to

help you discover bugs in the program. If you are interested in a particular analysis, get a copy of

the paper that described the method and analyze the example dataset to duplicate the published

results. This is particularly important because the manual, as it is written, describes the meanings of

the control variables used by the programs but does not clearly explain how to set up the control file

to conduct a particular analysis.

examples/HIVNSsites/: This folder contains example data files for the HIV-1 env V3 region

analyzed in Yang et al. (2000b). The data set is for demonstrating the NSsites models

described in that paper, that is, models of variable ω ratios among amino acid sites. Those

models are called the “random-sites ” models by Yang & Swanson (2002) since a priori we

do not know which sites might be highly conserved and which under positive selection.

They are also known as “fishing-expedition ” models. The included data set is the 10th data

set analyzed by Yang et al. (2000b) and the results are in table 12 of that paper. Look at the

readme file in that folder.

examples/lysin/: This folder contains the sperm lysin genes from 25 abalone species

analyzed by Yang, Swanson & Vacquier (2000a) and Yang and Swanson (2002). The data

set is for demonstrating both the “random-sites ” models (as in Yang, Swanson & Vacquier

(2000a)) and the “fixed-sites ” models (as in (Yang and Swanson 2002)). In the latter paper,

we used structural information to partition amino acid sites in the lysin into the “buried ” and

“exposed” classes and assigned and estimated different ω ratios for the two partitions. The

hypothesis is that the sites exposed on the surface are likely to be under positive selection.

Look at the readme file in that folder.

examples/lysozyme/: This folder contains the primate lysozyme c genes of Messier and

Stewart (1997), re-analyzed by Yang (1998). This is for demonstrating codon models that

assign different ω ratios for different branches in the tree, useful for testing positive

selection along lineages. Those models are sometimes called branch models or branch-

specific models. Both the “large ” and the “small ” data sets in Yang (1998) are included.

Those models require the user to label branches in the tree, and the readme file and included

tree file explain the format in great detail. See also the section “Tree file and

representations of tree topology ” later about specifying branch/node labels.

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PAML 4.3版软件教程：最大似然法 phylogenetic analysis

PAML中文文档/计算分子进化

paml软件教程[收集].pdf

华大的生物信息学教材.pdf

macOS下PAML安装

如何利用PAML 4.3的控制文件进行不同进化模型的比较，并确定最佳模型？

在使用PAML 4.3进行系统发育分析时，如何通过最大似然法比较不同的进化模型并选择最合适的模型？

元学习在少镜头人体运动预测中的工作原理是什么？请结合PAML模型进行说明。

元学习如何在少镜头条件下提高人体运动预测的准确性？以PAML模型为例进行说明。

什么是元学习，并且在少镜头人体运动预测中它是如何工作的？请结合PAML模型进行说明。

在使用Perl进行生物信息学分析时，如何高效地处理和分析测序数据？请结合Unix/Linux命令行工具给出具体的操作方法。

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