最近学习微生物宏基因组分箱（binning），按官方文档安装metaWRAP，踩了一堆坑，记录一下报错及解决方法：
1. metaWRAP安装
作者推荐使用Conda/Mamba安装，不推荐使用bioconda及docker，于是找了个包含conda的docker镜像，开始了漫漫长路的第一步：
（1）conda安装软件
conda create -y -n metawrap-env python=2.7 source activate metawrap-env conda config --add channels defaults conda config --add channels conda-forge conda config --add channels bioconda conda config --add channels ursky conda install -y -c ursky metawrap-mg conda install -y blas=2.5=mkl
装完大概5GB大小，提交到了docker hub上：
docker push raser216/metawrap:v1.0.0
本以为大功告成，结果随之而来的是一系列的报错……
（2）安装libtbb2库
运行到quant_bins，才发现少了个依赖库没装，导致salmon软件统计基因丰度时报错：
salmon: error while loading shared libraries: libtbb.so.2
解决方法：
#安装libtbb2库 apt-get install libtbb2
（3）安装libGL.so.1
bin_refinement步骤figures目录下无图片，python绘图程序报错：
ImportError: Failed to import any qt binding #python2.7 已安装matplotlib，但无法导入 import matplotlib import matplotlib.pyplot as plt ImportError: libGL.so.1: cannot open shared object file: No such file or directory
解决方法：安装libGL.so.1依赖。
apt-get -y update apt-get install -y libgl1-mesa-glx #安装后，python2可以导入该模块，不再报错 python 2.7 import matplotlib.pyplot as plt
（4）prokka安装失败，报错
prokka无法使用，安装失败：
可能原因：metawrap安装的perl版本不符合prokka要求 （metawrap不支持perl 5.26？）。
prokka -h Can't locate Bio/Root/Version.pm in @INC (you may need to install the Bio::Root::Version module) (@INC contains: /opt/conda/envs/metawrap-env/bin/../perl5 /opt/conda/envs/metawrap-env/lib/site_perl/5.26.2//x86_64-linux-thread-multi /opt/conda/envs/metawrap-env/lib/site_perl/5.26.2/ /opt/conda/envs/metawrap-env/lib/site_perl/5.26.2/x86_64-linux-thread-multi /opt/conda/envs/metawrap-env/lib/site_perl/5.26.2 /opt/conda/envs/metawrap-env/lib/5.26.2/x86_64-linux-thread-multi /opt/conda/envs/metawrap-env/lib/5.26.2 .) at /opt/conda/envs/metawrap-env/bin/prokka line 32. BEGIN failed--compilation aborted at /opt/conda/envs/metawrap-env/bin/prokka line 32.
解决方法：在当前metawrap 环境中用conda重装prokka-1.13。
conda create -n prokka-test prokka=1.13 minced=0.3.0 parallel=20180522 blast=2.12.0 source activate prokka-test
2.conda报错
（1）无法进入conda环境
无法在shell脚本中通过source activate metawrap-env进入conda环境，报错：
/opt/conda/envs/metawrap-env/etc/conda/activate.d/activate-binutils_linux-64.sh: line 65: ADDR2LINE: unbound variable
解决方法：通过dockerfile进入conda环境，并把安装软件的路径加到环境变量中：
cat metawrap_v1.dockerfile #dockerfile内容如下 FROM raser216/metawrap:v1.0.0 RUN echo "source activate metawrap-env" > ~/.bashrc
ENV PATH /opt/conda/envs/metawrap-env/bin:$PATH
3.数据库路径及版本
metaWRAP中调用的比对软件（kraken、BLAST等）的数据库可以外置，但数据库外置的路径需要在config中写明：
#config文件路径 which config-metawrap /opt/conda/envs/metawrap-env/bin/config-metawrap #用sed -i更改为各数据库真实路径 kraken_database=/database/kraken_database/kraken_newdb2/axel_dowload nt_database=/database/newdownload3 tax_database=/database/metawrap_database/ncbi_taxonomy sed -i "s#~/KRAKEN_DB#$kraken_database#g" /opt/conda/envs/metawrap-env/bin/config-metawrap sed -i "s#~/NCBI_NT_DB#$nt_database#g" /opt/conda/envs/metawrap-env/bin/config-metawrap sed -i "s#~/NCBI_TAX_DB#$tax_database#g" /opt/conda/envs/metawrap-env/bin/config-metawrap
该文件必须有写权限，否则bin_refinement步骤报错：
#bin_refinement步骤报错 You do not seem to have permission to edit the checkm config file located at /opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/DATA_CONFIG
解决方法：改变config文件权限，不再报错。
chmod 777 /opt/conda/envs/metawrap-env/bin/config-metawrap
4. kraken软件报错
kraken是个直接对测序reads（fastq）进行物种注释的软件，目前有两个主版本，1代（kraken）耗内存极高（>100GB），2代（kraken2）改良了很多（35GB左右就行）。
（1）注释行导致的报错
kraken.sh脚本路径在/opt/conda/envs/metawrap-env/bin/metawrap-modules/，该脚本第123-125行的注释信息直接写在行后，导致kraken.sh运行报错（错误信息未记录）:
123 awk '{ printf("%s",$0); n++; if(n%4==0) { printf("\n");} else { printf("\t\t");} }' | \ #combine paired end reads onto one line
124 shuf | head -n $depth | sed 's/\t\t/\n/g' | \ #shuffle reads, select top N reads, and then restore tabulation
125 awk -F"\t" '{print $1 > "'"${out}/tmp_1.fastq"'"; print $2 > "'"${out}/tmp_2.fastq"'"}' #separate reads into F and R files
解决方法：把注释行全部换到新行
123 # combine paired end reads onto one line, then
124 # shuffle reads, select top N reads, and then restore tabulation, then
125 # separate reads into F and R files
126 awk '{ printf("%s",$0); n++; if(n%4==0) { printf("\n");} else { printf("\t\t");} }' | \
127 shuf | head -n $depth | sed 's/\t\t/\n/g' | \
128 awk -F"\t" '{print $1 > "'"${out}/tmp_1.fastq"'"; print $2 > "'"${out}/tmp_2.fastq"'"}'
（2） 脚本无权限报错
注意kraken.sh脚本权限应为可执行，否则使用时报错：
/opt/conda/envs/metawrap-env/bin/metawrap: line 69: /opt/conda/envs/metawrap-env/bin/metawrap-modules/kraken.sh: Permission denied
解决方法：修改脚本权限为775，不再报错。
chmod 775 kraken.sh ls -l kraken.sh -rwxrwxr-x 1 root root 8.9K Sep 22 20:12 kraken.sh
（3）python注释脚本报错
python脚本kraken2_translate.py，字典names_map遇到未知key，报KeyError错误。
Something went wrong with running kraken-translate... Exiting.
Traceback (most recent call last):
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 120, in <module>
main()
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 114, in main
translate_kraken2_annotations(annotation_file=kraken_file, kraken2_db=database_location, output=output_file)
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 98, in translate_kraken2_annotations
taxonomy = get_full_name(taxid, names_map, ranks_map)
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 30, in get_full_name
name = names_map[taxid]
KeyError: '1054037'
解决方法：修改字典获取值的方式，改为dict.get()函数，并加入None值判断。
vi /opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py
#修改get_full_name函数，使key不存在时names_map不报错：
for taxid in taxid_lineage:
#name = names_map[taxid]
name = names_map.get(taxid)
if name == None:
name = "unknown"
names_lineage.append(name)
（4）找不到taxonomy数据库报错
下载的NCBI taxonomy数据库需要放到下载的kraken数据库目录下，否则报错：
Traceback (most recent call last):
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 120, in <module>
main()
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 114, in main
translate_kraken2_annotations(annotation_file=kraken_file, kraken2_db=database_location, output=output_file)
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 87, in translate_kraken2_annotations
names_map, ranks_map = load_kraken_db_metadata(kraken2_db)
File "/opt/conda/envs/metawrap-env/bin/metawrap-scripts/kraken2_translate.py", line 50, in load_kraken_db_metadata
with open(names_path) as input:
IOError: [Errno 2] No such file or directory: '/database/kraken_database/kraken_newdb2/axel_dowload/taxonomy/names.dmp'
解决方法：把taxonomy数据库复制到kraken数据库目录下。
（5）kraken软件与数据库版本不相符，报错
此前用过kraken2（2代软件），服务器上已经下载了2代所需的（巨大的）数据库，不想再下一次kraken（1代软件）数据库，于是试了试2代的数据库能否兼容1代软件，果然不行，报错：
kraken: database ("/database/kraken_database/kraken_newdb2/axel_dowload") does not contain necessary file database.kdb
遂考虑更新metaWRAP中的kraken版本，结果发现，默认安装的metaWRAP不支持kraken2，需要更新到最新的1.3.2版本：
解决方法：更新metaWRAP版本至1.3.2。
conda install -y -c ursky metawrap-mg=1.3.2 #更新后需要重新修改config文件权限，及其中的内容 chmod 777 /opt/conda/envs/metawrap-env/bin/config-metawrap
5.checkM软件报错
（1）py换行符报错
checkM是用于检测基因组拼接组装完整性的软件，bin_refinement会用到，直接报错：
Traceback (most recent call last):
File "/opt/conda/envs/metawrap-env/bin/checkm", line 36, in <module>
from checkm import main
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/main.py", line 25, in <module>
from checkm.defaultValues import DefaultValues
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/defaultValues.py", line 26, in <module>
class DefaultValues():
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/defaultValues.py", line 29, in DefaultValues
__DBM = DBManager()
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/checkmData.py", line 114, in __init__
if not self.setRoot():
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/checkmData.py", line 140, in setRoot
path = self.confirmPath(path=path)
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/checkmData.py", line 162, in confirmPath
path = raw_input("Where should CheckM store it's data?\n" \
EOFError: EOF when reading a line
解决方法：修改checkmData.py文件raw_input()函数参数。
该py脚本所在路径：/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/
报错原因：第162行的raw_input()函数加了“\”作为换行符，python没识别
162 path = raw_input("Where should CheckM store it's data?\n" \
163 Please specify a location or type 'abort' to stop trying: \n")
解决方法：删除该换行符。
162 path = raw_input("Where should CheckM store it's data?\nPlease specify a location or type 'abort' to stop trying: \n")
（2）找不到数据库报错
第一次运行checkM时，会被要求选择数据库位置，所以最好是在安装后就运行一下checkm data setRoot，先设置好数据库路径：
checkm data setRoot ******************************************************************************* [CheckM - data] Check for database updates. [setRoot] ******************************************************************************* Where should CheckM store it's data? Please specify a location or type 'abort' to stop trying: /checkm_database Path [/checkm_database] exists and you have permission to write to this folder.
否则，checkM找不到数据库，会显示以下信息：
It seems that the CheckM data folder has not been set yet or has been removed. Running: 'checkm data setRoot'. You do not seem to have permission to edit the checkm config file located at /opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/DATA_CONFIG Please try again with updated privileges. Unexpected error: <type 'exceptions.TypeError'>
（3）tmpdir路径过长，报错
*******************************************************************************
[CheckM - tree] Placing bins in reference genome tree.
*******************************************************************************
Identifying marker genes in 8 bins with 32 threads:
Process SyncManager-1:
Traceback (most recent call last):
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/process.py", line 267, in _bootstrap
self.run()
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/process.py", line 114, in run
self._target(*self._args, **self._kwargs)
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/managers.py", line 550, in _run_server
server = cls._Server(registry, address, authkey, serializer)
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/managers.py", line 162, in __init__
self.listener = Listener(address=address, backlog=16)
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/connection.py", line 132, in __init__
self._listener = SocketListener(address, family, backlog)
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/connection.py", line 256, in __init__
self._socket.bind(address)
File "/opt/conda/envs/metawrap-env/lib/python2.7/socket.py", line 228, in meth
return getattr(self._sock,name)(*args)
error: AF_UNIX path too long
Traceback (most recent call last):
File "/opt/conda/envs/metawrap-env/bin/checkm", line 708, in <module>
checkmParser.parseOptions(args)
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/main.py", line 1251, in parseOptions
self.tree(options)
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/main.py", line 133, in tree
options.bCalledGenes)
File "/opt/conda/envs/metawrap-env/lib/python2.7/site-packages/checkm/markerGeneFinder.py", line 67, in find
binIdToModels = mp.Manager().dict()
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/__init__.py", line 99, in Manager
m.start()
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/managers.py", line 528, in start
self._address = reader.recv()
EOFError
解决方法：修改binning.sh等脚本中指定的checkm --tmpdir，指定一个绝对路径较短的临时文件存放目录。
#该路径下这3个脚本都用到checkM，都需要改默认的--tmpdir
cd /opt/conda/envs/metawrap-env/bin/metawrap-modules
grep checkm *sh|awk -F ":" '{print $1}'|sort|uniq
bin_refinement.sh
binning.sh
reassemble_bins.sh
#以binning.sh为例
#在checkm命令前加一行，新建一个较短的tmp目录，用于存放checkM的tmp文件
mkdir -p /tmp/$(basename ${1}).tmp
#修改checkm的--tmpdir
61 checkm lineage_wf -x fa ${1} ${1}.checkm -t $threads --tmpdir /tmp/$(basename ${1}).tmp --pplacer_threads $p_threads
62 if [[ ! -s ${1}.checkm/storage/bin_stats_ext.tsv ]]; then error "Something went wrong with running CheckM. Exiting..."; fi
#运行完毕后删除该tmp目录
rm -r /tmp/$(basename ${1}).tmp
#其余两个脚本同样需要修改对应checkm行
#bin_refinement.sh脚本修改
if [ ! -d /tmp/$(basename ${bin_set}) ]; then mkdir -p /tmp/$(basename ${bin_set}).tmp; fi
if [ "$quick" == "true" ]; then
comm "Note: running with --reduced_tree option"
checkm lineage_wf -x fa $bin_set ${bin_set}.checkm -t $threads --tmpdir /tmp/$(basename ${bin_set}).tmp --pplacer_threads $p_threads --reduced_tree
else
checkm lineage_wf -x fa $bin_set ${bin_set}.checkm -t $threads --tmpdir /tmp/$(basename ${bin_set}).tmp --pplacer_threads $p_threads
fi
if [[ ! -s ${bin_set}.checkm/storage/bin_stats_ext.tsv ]]; then error "Something went wrong with running CheckM. Exiting..."; fi
${SOFT}/summarize_checkm.py ${bin_set}.checkm/storage/bin_stats_ext.tsv $bin_set | (read -r; printf "%s\n" "$REPLY"; sort) > ${bin_set}.stats
if [[ $? -ne 0 ]]; then error "Cannot make checkm summary file. Exiting."; fi
rm -r ${bin_set}.checkm; rm -r /tmp/$(basename ${bin_set}).tmp
mkdir -p /tmp/binsO.tmp
if [ "$quick" == "true" ]; then
checkm lineage_wf -x fa binsO binsO.checkm -t $threads --tmpdir /tmp/binsO.tmp --pplacer_threads $p_threads --reduced_tree
else
checkm lineage_wf -x fa binsO binsO.checkm -t $threads --tmpdir /tmp/binsO.tmp --pplacer_threads $p_threads
fi
if [[ ! -s binsO.checkm/storage/bin_stats_ext.tsv ]]; then error "Something went wrong with running CheckM. Exiting..."; fi
rm -r /tmp/binsO.tmp
#reassemble_bins.sh脚本修改
mkdir -p /tmp/$(basename ${out}).tmp
checkm lineage_wf -x fa ${out}/reassembled_bins ${out}/reassembled_bins.checkm -t $threads --tmpdir /tmp/$(basename ${out}).tmp --pplacer_threads $p_threads
if [[ ! -s ${out}/reassembled_bins.checkm/storage/bin_stats_ext.tsv ]]; then error "Something went wrong with running CheckM. Exiting..."; fi
${SOFT}/summarize_checkm.py ${out}/reassembled_bins.checkm/storage/bin_stats_ext.tsv | (read -r; printf "%s\n" "$REPLY"; sort) > ${out}/reassembled_bins.stats
if [[ $? -ne 0 ]]; then error "Cannot make checkm summary file. Exiting."; fi
rm -r /tmp/$(basename ${out}).tmp
mkdir -p /tmp/$(basename ${out}).tmp
checkm lineage_wf -x fa ${out}/reassembled_bins ${out}/reassembled_bins.checkm -t $threads --tmpdir /tmp/$(basename ${out}).tmp --pplacer_threads $p_threads
if [[ ! -s ${out}/reassembled_bins.checkm/storage/bin_stats_ext.tsv ]]; then error "Something went wrong with running CheckM. Exiting..."; fi
rm -r /tmp/$(basename ${out}).tmp
该错误会连带导致bin_refinement报错（因为checkM未正确运行，无对应统计结果）：
Traceback (most recent call last):
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/util.py", line 277, in _run_finalizers
finalizer()
File "/opt/conda/envs/metawrap-env/lib/python2.7/multiprocessing/util.py", line 207, in __call__
res = self._callback(*self._args, **self._kwargs)
File "/opt/conda/envs/metawrap-env/lib/python2.7/shutil.py", line 266, in rmtree
one rror(os.remove, fullname, sys.exc_info())
File "/opt/conda/envs/metawrap-env/lib/python2.7/shutil.py", line 264, in rmtree
os.remove(fullname)
OSError: [Errno 16] Device or resource busy: 'binsO.tmp/pymp-REeR36/.nfs9061e516f4bd263400000b82'
mv: cannot stat 'binning_results.eps': No such file or directory
mv: cannot stat 'binning_results.eps': No such file or directory
6.BLAST报错
blobology步骤，BLAST版本与已下载的nt数据库（下载的是version 5，最新版数据库）版本不符，报错：BLAST Database error: Error: Not a valid version 4 database.
解决方法：更新BLAST版本。
#下载并解压新版BLAST软件 wget https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/ncbi-blast-2.12.0+-x64-linux.tar.gz tar -xzvf ncbi-blast-2.12.0+-x64-linux.tar.gz #替换掉conda镜像中的BLAST mkdir /opt/conda/envs/metawrap-env/bin/bak for i in $(ls);do mv /opt/conda/envs/metawrap-env/bin/$i /opt/conda/envs/metawrap-env/bin/bak;cp $i /opt/conda/envs/metawrap-env/bin;done
7.prokka报错
（1）安装不成功，报错
prokka软件用于注释组装好的基因组，是一个perl脚本，conda安装失败，完全打不开
（1）不识别blast版本，报错
prokka对软件blastp及makeblastdb的要求为版本大于2.8及以上，但此处判断条件有点问题，识别不了我的blast 2.12.0（认为版本2.12小于2.8……）。
不懂perl语言，没法优化，只好把MINVER都改成了2.1：
'blastp' => {
GETVER => "blastp -version",
REGEXP => qr/blastp:\s+($BIDEC)/,
MINVER => "2.1",
NEEDED => 1,
},
'makeblastdb' => {
GETVER => "makeblastdb -version",
REGEXP => qr/makeblastdb:\s+($BIDEC)/,
MINVER => "2.1",
NEEDED => 0, # only if --proteins used
},