目录
1. 原版
安装比较简单。
wget https://reich.hms.harvard.edu/sites/reich.hms.harvard.edu/files/inline-files/XPCLR.tar
tar xvf XPCLR.tar
直接运行bin下的XPCLR即可，若不能运行，则编译下：
cd src
make
make install
原版分析时准备文件过程较为繁琐，因此更建议使用Python版。
$ /project/biosoft/XPCLR/bin/XPCLR -h
Usage:
XPCLR -xpclr hapmapInput1 hapmapInput2 mapInput outFile -w gWin(Morgan) snpWin gridSize(bp) chrN -p corrLevel
-w1: gWin sets the size of a sliding window(units: 100cM),sWin sets # of SNPs in a window. otherwise, no sliding window
-p1:the input genotpe is already phased. -p0: the input genotype is not phased
corrLevel: the value is on (0,1], set corrLevel equal to 0 if no correction is needed
2. Python版本
安装
conda create -n xpclr -c bioconda xpclr
conda activate xpclr
报错：
$ xpclr -h
Traceback (most recent call last):
File "/home/miniconda3/envs/xpclr/bin/xpclr", line 5, in <module>
import xpclr
File "/home/miniconda3/envs/xpclr/lib/python2.7/site-packages/xpclr/__init__.py", line 3, in <module>
from xpclr import methods
File "/home/miniconda3/envs/xpclr/lib/python2.7/site-packages/xpclr/methods.py", line 11, in <module>
from functools import lru_cache
ImportError: cannot import name lru_cache
重新安装pip install lru_cache仍然报错。
由于python版本引起，直接修改methods.py中from functools import lru_cache的为：
try:
from functools import lru_cache
except ImportError:
from backports.functools_lru_cache import lru_cache
运行
xpclr --format vcf --input /project/04.sweep/sample750_miss0.6_impute/meanDP3.miss0.6.maf0.01.impute.rename.vcf \
--samplesA /project/04.sweep/sample750_miss0.6_impute/List/w-l-c/Cultivar.list \
--samplesB /project/04.sweep/sample750_miss0.6_impute/List/w-l-c/Wild.list \
--chr 1 --maxsnps 600 --size 1000 --step 1000 --out test_out
报错：
Traceback (most recent call last):
File "/home/miniconda3/envs/xpclr/bin/xpclr", line 195, in <module>
main()
File "/home/miniconda3/envs/xpclr/bin/xpclr", line 88, in main
"No permission to write in the specified directory: {0}".format(outdir)
AssertionError: No permission to write in the specified directory:
xpclr第84行fn = args.out修改为：
fn = os.path.abspath(args.out)
运行继续报错：
2023-03-17 19:05:48 : INFO : running xpclr v1.1.0
2023-03-17 19:05:48 : INFO : Loading VCF
Traceback (most recent call last):
File "/home/miniconda3/envs/xpclr/bin/xpclr", line 196, in <module>
main()
File "/home/miniconda3/envs/xpclr/bin/xpclr", line 103, in main
gdistkey=args.gdistkey)
File "/home/miniconda3/envs/xpclr/lib/python2.7/site-packages/xpclr/util.py", line 112, inload_vcf_format_data
pos1, geno1 = load_vcf_wrapper(vcf_fn, chrom, samples1)
File "/home/miniconda3/envs/xpclr/lib/python2.7/site-packages/xpclr/util.py", line 94, in load_vcf_wrapper
callset = allel.read_vcf(
AttributeError: 'module' object has no attribute 'read_vcf'
网上没有我的同类安装相关错误报道，查看了下allel模块，确实没有read_vcf函数：
Python 2.7.18 |Anaconda, Inc.| (default, Nov 25 2022, 06:27:37)
[GCC 11.2.0] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import allel
>>> allel
<module 'allel' from '/home/miniconda3/envs/xpclr/lib/python2.7/site-packages/scikit_allel-0.20.3-py2.7-linux-x86_64.egg/allel/__init__.py'>
>>> dir(allel)
['AlleleCountsArray', 'AlleleCountsCArray', 'AlleleCountsCTable', 'AlleleCountsChunkedArray', 'AlleleCountsChunkedTable', 'AlleleCountsDaskArray', 'FeatureCTable', 'FeatureChunkedTable', 'FeatureTable', 'GenotypeArray', 'GenotypeCArray', 'GenotypeChunkedArray', 'GenotypeDaskArray', 'HaplotypeArray', 'HaplotypeCArray', 'HaplotypeChunkedArray', 'HaplotypeDaskArray', 'SortedIndex', 'SortedMultiIndex', 'UniqueIndex', 'VariantCTable', 'VariantChunkedTable', 'VariantTable', '__builtins__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__path__', '__version__', '_bcolz', '_da', 'chunked', 'compat', 'constants', 'io', 'model', 'plot', 'stats', 'util']
但实际上官网上是有这个函数的：
难道是版本问题吗？装了下python3版本，发现确实是有的：
试图重新安装，旧版本删除不了：
$ pip uninstall scikit-allel
DEPRECATION: Python 2.7 will reach the end of its life on January 1st, 2020. Please upgrade your Python as Python 2.7 won't be maintained after that date. A future version of pip will dropsupport for Python 2.7. More details about Python 2 support in pip, can be found at https://pip.pypa.io/en/latest/development/release-process/#python-2-support
ERROR: Cannot remove entries from nonexistent file /home/pengjx/miniconda3/envs/xpclr/lib/python2.7/site-packages/easy-install.pth
升级也升级不了：
>pip install --upgrade --ignore-installed scikit-allel -i https://pypi.tuna.tsinghua.edu.cn/simple
.......
ERROR: Command errored out with exit status 1:
没办法放弃conda安装，直接从GitHub安装：https://github.com/hardingnj/xpclr。
git clone https://github.com/hardingnj/xpclr.git
cd xpclr
python setup.py install
进入bin后，可直接运行xpclr：
$ xpclr -h
usage: xpclr [-h] --out OUT [--format FORMAT] [--input INPUT] [--gdistkey GDISTKEY] [--samplesA SAMPLESA] [--samplesB SAMPLESB] [--rrate RRATE] [--map MAP] [--popA POPA] [--popB POPB]
--chr CHROM [--ld LDCUTOFF] [--phased] [--verbose VERBOSE] [--maxsnps MAXSNPS] [--minsnps MINSNPS] [--size SIZE] [--start START] [--stop STOP] [--step STEP]
Tool to calculate XP-CLR as per Chen, Patterson, Reich 2010
需要注意的是，你如果使用xpclr的全路径是运行不了的：
$ /project/xpclr/bin/xpclr
Traceback (most recent call last):
File "/project/xpclr/bin/xpclr", line 4, in <module>
import numpy as np
ImportError: No module named numpy
安装依赖包：pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple。
这时，也可以用python（实际上我当前的版本已经是Python 3.9.1，所以xpclr也是支持的。）来调用全路径：
python /project/xpclr/bin/xpclr --format vcf --input /project/04.sweep/sample750_miss0.6_impute/meanDP3.miss0.6.maf0.01.impute.rename.vcf --samplesA /project/04.sweep/sample750_miss0.6_impute/List/w-l-c/Cultivar.list --samplesB /project/04.sweep/sample750_miss0.6_impute/List/w-l-c/Wild.list --chr 1 --maxsnps 600 --size 1000 --step 1000 --out test_out
建议还是将安装路径/project/xpclr/bin加入环境变量（测试了下，貌似不用加入环境变量也可直接调用，可能是软件安装环节已经加入），直接用xpclr。
原因分析
conda安装虽然便捷，但作者没有及时更新，最早的版本也是在3年前（Python2），导致一些包不兼容。
而GitHub版本作者还是在维护的，所以对于后来者推荐之。
后续分析推荐
标签：__,bin,vcf,--,project,xpclr,折腾,XP,CLR From： https://www.cnblogs.com/jessepeng/p/17228216.html原版XP-CLR用法参考：https://zhuanlan.zhihu.com/p/145387269
Python版XP-CLR用法参考：https://www.jianshu.com/p/9c827a0be66d