1 介绍
PennCNV是一个免费软件工具，可从SNP基因分型阵列检测拷贝数变异（CNV）。目前，它可以处理来自Illumina和Affymetrix阵列的信号强度数据。通过适当准备文件格式，它还可以处理其他类型的SNP阵列和寡核苷酸阵列。PennCNV实现了一个隐藏的马尔可夫模型（HMM），该模型集成了多种信息源，以推断单个基因型样本的CNV调用。官网为：http://penncnv.openbioinformatics.org/en/latest/
2 安装准备
华为云购买一台鲲鹏服务器
本文以云服务器KC1实例搭建，云服务器配置如表1-1所示。
表1-1 云服务器配置
项目
说明
规格
kc1.large.2 | 4vCPUs | 8GB
磁盘
系统盘：高IO（40GB）
操作系统要求如表1-2所示。
表1-2 操作系统要求
项目
说明
下载地址
CentOS
7.6
在公共镜像中已提供。
Kernel
4.14.0
在公共镜像中已提供。
3 配置编译环境
安装依赖包。
yum install perl-devel perl-devel -y
配置perl环境
在文件/etc/profile末尾添加如下内容。
export C_INCLUDE_PATH=$C_INCLUDE_PATH: /usr/lib64/perl5/CORE
2. 按Esc，并且输入wq!保存退出。
3. 输入如下命令，使环境变量生效。
source /etc/profile
4 安装PennCNV
安装
配置PennCNV环境
在文件/etc/profile末尾添加如下内容。
export PATH=$PATH:/usr/local/src/PennCNV-1.0.5
按Esc，并且输入wq!保存退出。
输入如下命令，使环境变量生效。
source /etc/profile
5 运行和验证
1）进入example目录。
cd /usr/local/src/PennCNV-1.0.5/example
2）执行程序runex.pl。
当系统回显类似如下信息时，表示PennCNV安装成功。
[root@ecs example]# perl runex.pl Usage: runex.pl <1|2|3|4|5|6|7|8|9|10|11|12|13|14|15|16> Optional arguments: -v, --verbose use verbose output -h, --help print help message -m, --man print complete documentation --path_detect_cnv path to detect_cnv.pl --path_visualize_cnv path to visualize_cnv.pl --path_convert_cnv path to convert_cnv.pl --path_filter_cnv path to filter_cnv.pl --path_compare_cnv path to compare_cnv.pl Function: test-drive PennCNV and related scripts in your system Example: runex.pl 1 (run PennCNV to call CNV on three signal files) runex.pl 2 (run posterior CNV calling algorithm on a trio) runex.pl 3 (run PennCNV with GCmodel adjustment of signal intensity) runex.pl 4 (validation-based CNV calling on a candidate region) runex.pl 5 (validation-based CNV calling on all candidate regions in a file) runex.pl 6 (run joint CNV calling on a trio) runex.pl 7 (convert CNV call to BED format) runex.pl 8 (convert CNV call to tab-delimited format) runex.pl 9 (convert tab-delimited calls to PennCNV format) runex.pl 10 (filter CNV and print out a subset of calls) runex.pl 11 (compare CNV calls on duplicated samples) runex.pl 12 (compare CNV calls on same sample called by different algorithms) runex.pl 13 (generate CNV-based genotype calls) runex.pl 14 (validate de novo CNV calls and assign a P-value) runex.pl 15 (convert Canary CNV calls to PennCNV format) runex.pl 16 (plot signal intensity for CNV calls in JPG formats)
3、用户可以尝试一一运行这些示例，并对PennCNV可以做什么以及如何使用命令行选项有所了解。 例如，让我们先尝试第一个示例：
[root@ecs example]# perl runex.pl 1 Exercise 1: individual-based calling and write the output to ex1.rawcnv Running command ****************************************************************************** NOTICE: All program notification/warning messages that appear in STDERR will be also written to log file ex1.log NOTICE: Reading marker coordinates and population frequency of B allele (PFB) from ../lib/hh550.hg18.pfb ... Done with 566108 records (178 records in chr M,XY were discarded) NOTICE: Reading LRR and BAF values for from father.txt ... Done with 93129 records in 4 chromosomes NOTICE: Data from chromosome X will not be used in analysis NOTICE: Median-adjusting LRR values for all autosome markers from father.txt by 0.0221 NOTICE: Median-adjusting BAF values for all autosome markers from father.txt by 0.0029 NOTICE: quality summary for father.txt: LRR_mean=0.0027 LRR_median=0.0000 LRR_SD=0.1335 BAF_mean=0.5063 BAF_median=0.5000 BAF_SD=0.0390 BAF_DRIFT=0.000037 WF=0.0184 GCWF=0.0136 NOTICE: Reading LRR and BAF values for from mother.txt ... Done with 93129 records in 4 chromosomes NOTICE: Data from chromosome X will not be used in analysis NOTICE: Median-adjusting LRR values for all autosome markers from mother.txt by -0.0199 NOTICE: Median-adjusting BAF values for all autosome markers from mother.txt by 0.0324 NOTICE: quality summary for mother.txt: LRR_mean=0.0039 LRR_median=0.0000 LRR_SD=0.1374 BAF_mean=0.5044 BAF_median=0.5000 BAF_SD=0.0418 BAF_DRIFT=0.000140 WF=0.0100 GCWF=0.0028 NOTICE: Reading LRR and BAF values for from offspring.txt ... Done with 93129 records in 4 chromosomes NOTICE: Data from chromosome X will not be used in analysis NOTICE: Median-adjusting LRR values for all autosome markers from offspring.txt by -0.0087 NOTICE: Median-adjusting BAF values for all autosome markers from offspring.txt by 0.0260 NOTICE: quality summary for offspring.txt: LRR_mean=0.0028 LRR_median=0.0000 LRR_SD=0.1263 BAF_mean=0.5045 BAF_median=0.5000 BAF_SD=0.0429 BAF_DRIFT=0.000293 WF=-0.0171 GCWF=-0.0100 ******************************************************************************
6 故障排除
问题：编译报“error: 'off64_t' does not name a type”错误
问题描述：
进入“PennCNV-1.0.5/kext”目录，执行make时，提示信息如图所示。
问题原因：
off64_t属于c++的类型，编译时候需要用g++，而不是gcc。
解决方法：
修改Makefile，将编译标志gcc改为g++，然后重新编译。Makefile修改后如下：
CC = g++
LD = g++
基因测序 鲲鹏
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