Phylosuite里面的Partitionfinder2运行实在是不够快，下了个Linux版本的来跑。
Partitionfinder2是基于Python2.7的所以新建了个python2的环境
conda create -n python2.7 conda activate python2.7 conda install python=2.7 #离开 conda deactivate git clone https://github.com/brettc/partitionfinder.git #下的是partitionfinder-2.1.1 cd partitionfinder make
但是报这个错 至今不知道为什么QAQ 如果有知道的好心人可以说一说
[root@localhost partitionfinder-2.1.1]# make find ./tests -name analysis -and -d | xargs rm -rf find: 警告: 您在非选项参数 -name 后定义了 -d 选项，但选项不是位置选项 (-d 影响在它之前或之后的指 find: 警告: 不赞成使用 -d 选项；请使用 -depth 代替，因为后者更符合 POSIX 特性。 find ./tests -name log.txt | xargs rm rm: 缺少操作数 Try 'rm --help' for more information. make: *** [clean-test] 错误 123
于是放弃了partitionfinder-2.1.1版本 然后下载了早一点的版本
tar -zxvf partitionfinder-2.0.0.tar.gz cd partitionfinder-2.0.0/ ./PartitionFinder.py #试一下 提醒要安装依赖包 pip install numpy pandas tables pyparsing scipy sklearn chmod 775 * #给权限 ./PartitionFinder.py (python2.7) [root@localhost partitionfinder-2.0.0]# ./PartitionFinder.py INFO | 2021-11-30 16:04:03,183 | Note: NumExpr detected 35 cores but "NUMEXPR_MAX_THREADS" not set, so enforcing safe limit of 8. INFO | 2021-11-30 16:04:03,184 | NumExpr defaulting to 8 threads. Usage: python PartitionFinder.py [options]PartitionFinder and PartitionFinderProtein are designed to discover optimal partitioning schemes for nucleotide and amino acid sequence alignments. They are also useful for finding the best model of sequence evolution for datasets. The Input: : the full path to a folder containing: - A configuration file (partition_finder.cfg) - A nucleotide/aa alignment in Phylip format Take a look at the included 'example' folder for more details. The Output: A file in the same directory as the .cfg file, named 'analysis' This file contains information on the best partitioning scheme, and the best model for each partiiton Usage Examples: >python PartitionFinder.py example Analyse what is in the 'example' sub-folder in the current folder. >python PartitionFinder.py -v example Analyse what is in the 'example' sub-folder in the current folder, but show all the debug output >python PartitionFinder.py -c ~/data/frogs Check the configuration files in the folder data/frogs in the current user's home folder. >python PartitionFinder.py --force-restart ~/data/frogs Deletes any data produced by the previous runs (which is in ~/data/frogs/output) and starts afresh Options: -h, --help show this help message and exit -v, --verbose show debug logging information (equivalent to --debug- out=all) -c, --check-only just check the configuration files, don't do any processing -f, --force-restart delete all previous output and start afresh (!) -p N, --processes=N Number of concurrent processes to use. Use -1 to match the number of cpus on the machine. The default is to use -1. --show-python-exceptions If errors occur, print the python exceptions --save-phylofiles save all of the phyml or raxml output. This can take a lot of space(!) --dump-results Dump all results to a binary file. This is only of use for testing purposes. --compare-results Compare the results to previously dumped binary results. This is only of use for testing purposes. -q, --quick Avoid anything slow (like writing schemes at each step),useful for very large datasets. -r, --raxml Use RAxML (rather than PhyML) to do the analysis. See the manual -n, --no-ml-tree Estimate a starting tree with NJ (PhyML) or MP (RaxML) instead of the default which is to estimate a starting tree with ML using in RAxML. Not recommended. --cmdline-extras=N Add additional commands to the phyml or raxml commandlines that PF uses.This can be useful e.g. if you want to change the accuracy of lnL calculations ('-e' option in raxml), or use multi-threaded versions of raxml that require you to specify the number of threads you will let raxml use ('-T' option in raxml. E.g. you might specify this: --cmndline_extras ' -e 2.0 -T 10 ' N.B. MAKE SURE YOU PUT YOUR EXTRAS IN QUOTES, and only use this command if you really know what you're doing and are very familiar with raxml and PartitionFinder --weights=N Mainly for algorithm development. only use it if you know what you're doing.A list of weights to use in the clustering algorithms. This list allows you to assign different weights to: the overall rate for a subset, the base/amino acid frequencies, model parameters, and alpha value. This will affect how subsets are clustered together. For instance: --cluster_weights '1, 2, 5, 1', would weight the base freqeuncies 2x more than the overall rate, the model parameters 5x more, and the alpha parameter the same as the model rate --kmeans=type This defines which sitewise values to use: entropy or tiger --kmeans entropy: use entropies for sitewise values --kmeans tiger: use TIGER rates for sitewise values (only valid for Morphology) --rcluster-percent=N This defines the proportion of possible schemes that the relaxed clustering algorithm will consider before it stops looking. The default is 10%. e.g. --rcluster- percent 10.0 --rcluster-max=N This defines the number of possible schemes that the relaxed clustering algorithm will consider before it stops looking. The default is to look at the larger value out of 1000, and 10 times the number of data blocks you have. e.g. --rcluster-max 1000 --min-subset-size=N This defines the minimum subset size that the kmeans and rcluster algorithm will accept. Subsets smaller than this will be merged at with other subsets at the end of the algorithm (for kmeans) or at the start of the algorithm (for rcluster). See manual for details. The default value for kmeans is 100. The default value for rcluster is to ignore this option. e.g. --min- subset-size 100 --debug-output=REGION,REGION,... (advanced option) Provide a list of debug regions to output extra information about what the program is doing. Possible regions are 'all' or any of {subset,su bset_ops,raxml,parser,model_util,results,entropy,numex pr,alignment,concurrent.futures,threadpool,numexpr.uti ls,progress,main,config,reporter,kmeans,util,concurren t,morph_tige,analysis_m,neighbour,scheme,submodels,dat abase,analysis,phyml,raxml_mode,model_load,phyml_mode, sklearn}. --all-states In the kmeans and rcluster algorithms, this stipulates that PartitionFinder should not produce subsets that do not have all possible states present. E.g. for DNA sequence data, all subsets in the final scheme must have A, C, T, and G nucleotides present. This can occasionally be useful for downstream analyses, particularly concerning amino acid datasets. --profile Output profiling information after running (this will slow everything down!)
终于可以用了~~
