SARS-CoV2_ARTIC_Illumina新冠病毒分型和突变分析

一. 本文适用于使用Artic扩增子扩增，Illumina双端测序，用于分析新冠病毒突变及分型鉴定

二. 概览：按照惯例，先上一张概览图

流程输入	SRR22216743_1.fastq.gz SRR22216743_2.fastq.gz 测试数据下载 NYC SARS-CoV-2 genome sequencing from human nasopharyngeal swabs** 1 ILLUMINA (Illumina HiSeq 2000) run: 28,721 spots, 5.8M bases, 1.8Mb downloads 使用NCBI官方工具sra-toolkit拆分成fastq.gz文件 fastq-dump SRR22216743 --split-3 --gzip 得到SRR22216743_1.fastq.gz SRR22216743_2.fastq.gz 参考文件，默认路径/opt/ref下 Artic-ncov2019 artic-ncov2019 primer&参考序列 GCF_009858895.2_ASM985889v3_genomic.gff GFF文件分析流程文件（可一键导入sliverworkspace运行）及报告文件，conda环境文件下载，导入操作
运行环境	docker image based on ubuntu21.04 Conda Mamba（默认使用清华源） ssh
分析软件	- fastp=0.23.2 - fastqc=0.11.9 - multiqc=1.13 - bwa=0.7.17 - minimap2=2.24 - samtools=1.16.1 - ivar=1.3.1 - quast=5.2.0 - pangolin=4.1.3
输出结果	multiqc_report.html 测序数据trim前后质量数据 SRR22216743.samcov.tsv reads数量，覆盖度，测序深度，baseQ mapQ quast输出分析结果：alignment_viewer.html contig_size_viewer.html （拼接序列情况）report.html 按照序列一致性组装的新冠病毒序列 SRR22216743.consensus.fa Panglin 根据组装的序列分析得出病毒分型信息 lineage_report.csv samtools,ivar 根据primertrim.bam获的新冠病毒突变信息，过滤后得到 SRR22216743_variantsfiltered.tsv

环境搭建: 为了快速完成环境搭建，节省95%以上时间。

本文使用docker + conda (mamba) 作为基础分析环境，镜像获取：docker/docker-compoes 的安装及镜像构建见《基于docker的生信基础环境镜像构建》,docker镜像基于ubuntu21.04构建，并安装有conda/mamba，ssh服务。并尝试初次运行时初始化安装所需软件下载所需文件（作为代价首次运行时间会较长，切需网络通畅），即实现自动初始化的分析流程。

备注：docker运行的操作系统，推荐为Linux，windows，macOS系统改下docker可能部分功能（网络）不能正常运行

# 拉取docker镜像
docker     pull     doujiangbaozi/sliverworkspace:latest# 查看docker 镜像
docker     images

基础环境配置，docker-compose.yml 配置文件，可以根据需要自行修改调整

version: "3"
services:SarsCov2:image: doujiangbaozi/sliverworkspace:latestcontainer_name: SarsCov2volumes:- /media/sliver/Data/data:/opt/data:rw                               #挂载原始数据，放SC2目录下- /media/sliver/Manufacture/SC2/envs:/root/mambaforge-pypy3/envs:rw  #挂载envs conda环境目录- /media/sliver/Manufacture/SC2/config:/opt/config:rw                #挂载config conda配置文件目录- /media/sliver/Manufacture/SC2/ref:/opt/ref:rw                      #挂载reference目录- /media/sliver/Manufacture/SC2/result:/opt/result:rw                #挂载中间文件和输出结果目录ports:- "9024:9024"                                                        #ssh连接端口可以按需修改environment:- TZ=Asia/Shanghai                                                   #设置时区- PS=20191124                                                        #修改默认ssh密码- PT=9024                                                            #修改默认ssh端口

基础环境运行

# docker-compose.yml 所在目录下运行
docker-compose up -d# 或者 
docker-compose up -d -f /路径/docker-compose.yaml# 查看docker是否正常运行,docker-compose.yaml目录下运行
docker-compose ps# 或者
docker ps

docker 容器使用，类似于登录远程服务器

# 登录docker，使用的是ssh服务，可以本地或者远程部署使用
ssh root@192.168.6.6 -p9024# 看到如下，显示如下提示即正常登录
(base) root@SliverWorkstation:~#

三. 分析流程

1. 变量设置

#样本编号
export sn=SRR22216743
#数据输入目录
export data=/opt/data
#数据输出、中间文件目录
export result=/opt/result
#conda安装的环境目录
export envs=/root/mambaforge-pypy3/envs	
#artic primer 版本V1,V2,V3,V4,V4.1
export artic_primer_version=V4.1
#设置可用线程数
export threads=8

2. 分析前QC，看下数据质量

#conda检测环境是否存在，首次运行不存在创建该环境并安装软件
if [ ! -d "${envs}/qc" ]; thenmamba env create -f /opt/config/qc.yaml
fisource activate qcmkdir -p ${result}/${sn}/clean mkdir -p ${result}/${sn}/qcfastqc ${data}/SC2/${sn}_1.fastq.gz ${data}/SC2/${sn}_2.fastq.gz -o ${result}/${sn}/qcfastp -i ${data}/SC2/${sn}_1.fastq.gz -I ${data}/SC2/${sn}_2.fastq.gz \-o ${result}/${sn}/clean/${sn}_1_clean.fastq.gz -O ${result}/${sn}/clean/${sn}_2_clean.fastq.gz \-h ${result}/${sn}/qc/${sn}_fastp.html -j ${result}/${sn}/qc/${sn}_fastp.json fastqc ${result}/${sn}/clean/${sn}_1_clean.fastq.gz ${result}/${sn}/clean/${sn}_2_clean.fastq.gz \-o ${result}/${sn}/qc#汇总一下之前结果，得到一个总体报告
multiqc ${result}/${sn}/qc/ -f -o ${result}/${sn}/qcsource deactivate

3. 比对到参考基因组上，得到bam文件并排序

mkdir -p ${result}/${sn}/alignedif  [ ! -d "/opt/ref/artic-ncov2019" ]; thenapt-get install -y gitgit clone https://github.com/artic-network/artic-ncov2019.git "/opt/ref/artic-ncov2019"
fi#conda检测环境是否存在，首次运行不存在创建该环境并安装软件
if [ ! -d "${envs}/SC2" ]; thenmamba env create -f /opt/config/SC2.yaml
fisource activate SC2#如果没有索引，创建索引
if  [ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta.amb ] ||[ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta.ann ] ||[ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta.bwt ] ||[ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta.pac ] ||[ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta.sa ]; thenif [ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta ]; thencp  -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/SARS-CoV-2.reference.fasta \/opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fastafibwa index /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta
fibwa mem -t ${threads} \/opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta \${result}/${sn}/clean/${sn}_1_clean.fastq.gz ${result}/${sn}/clean/${sn}_2_clean.fastq.gz | \samtools sort | samtools view -F 4 -o ${result}/${sn}/aligned/${sn}.sorted.bamsamtools index ${result}/${sn}/aligned/${sn}.sorted.bam
mv  ${result}/${sn}/aligned/${sn}.sorted.bam.bai ${result}/${sn}/aligned/${sn}.sorted.bai
conda  deactivate

4. 去除artic primer （primer trim）

source activate SC2if  [ ! -f /opt/ref/artic-ncov2019/ARTIC-${artic_primer_version}.bed ]; thenif [ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.scheme.bed ]; thencp  -r /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/SARS-CoV-2.scheme.bed \/opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.scheme.bedfiperl -ne 'my @x=split m/\t/; print join("\t",@x[0..3], 60, $x[3]=~m/LEFT/?"+":"-"),"\n";' \< /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.scheme.bed  \> /opt/ref/artic-ncov2019/ARTIC-${artic_primer_version}.bed
fiivar trim -e -i ${result}/${sn}/aligned/${sn}.sorted.bam \-b /opt/ref/artic-ncov2019/ARTIC-${artic_primer_version}.bed \-p ${result}/${sn}/aligned/${sn}.primertrimconda  deactivate

5. primer trim 排序

source activate SC2samtools sort ${result}/${sn}/aligned/${sn}.primertrim.bam \-o ${result}/${sn}/aligned/${sn}.primertrim.sorted.bamconda  deactivate

6. 获取拼接后一致性序列

source activate SC2samtools mpileup -A -d 1000 -B -Q 0 \--reference /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta \${result}/${sn}/aligned/${sn}.primertrim.sorted.bam | ivar consensus -p ${result}/${sn}/${sn}.consensus -n N -i ${sn}grep -v ">" ${result}/${sn}/${sn}.consensus.fa | grep -o -E "C|A|T|G" | wc -lconda  deactivate

7. 使用Pangolin获取序列分型信息

#conda检测环境是否存在，首次运行不存在创建该环境并安装软件
if [ ! -d "${envs}/pangolin" ]; thenmamba env create -f /opt/config/pangolin.yaml
fisource activate pangolinpangolin ${result}/${sn}/${sn}.consensus.fa --outdir ${result}/${sn} conda  deactivate

8. 获取突变信息

source activate SC2if [ ! -f "/opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff" ]; thenaria2c https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/009/858/895/GCF_009858895.2_ASM985889v3/GCF_009858895.2_ASM985889v3_genomic.gff.gz -d /opt/refgzip -f  -d /opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff.gz
fisamtools mpileup -aa -A -d 0 -B -Q 0 \--reference /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta \${result}/${sn}/aligned/${sn}.primertrim.sorted.bam | \ivar variants -p ${result}/${sn}/${sn}_variants -q 30 -t 0.01 -m 0 \-r /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta \-g /opt/ref/GCF_009858895.2_ASM985889v3_genomic.gffivar filtervariants -p ${result}/${sn}/${sn}_variantsfiltered ${result}/${sn}/${sn}_variants.tsvconda  deactivate

9. 获取quast报告及bam覆盖度、测序深度、baseQ、mapQ等质控信息

source activate SC2if [ ! -f "/opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff" ]; thenaria2c https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/009/858/895/GCF_009858895.2_ASM985889v3/GCF_009858895.2_ASM985889v3_genomic.gff.gz -d /opt/refgzip -f  -d /opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff.gz
fiquast ${result}/${sn}/${sn}.consensus.fa \-r /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta \--features /opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff \--ref-bam  ${result}/${sn}/aligned/${sn}.sorted.bam \--output-dir ${result}/${sn}/quastsamtools coverage ${result}/${sn}/aligned/${sn}.sorted.bam -o ${result}/${sn}/aligned/${sn}.samcov.tsvconda  deactivate