SARS-CoV2_ARTIC_Illumina新冠病毒分型和突变分析

发布于:2022-11-09 ⋅ 阅读:(8) ⋅ 点赞:(0) ⋅ 评论:(0)

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

在这里插入图片描述

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:latest
    container_name: SarsCov2
    volumes:
      - /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

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=4.1
#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" ]; then
  mamba env create -f /opt/config/qc.yaml
fi

conda activate qc

mkdir -p ${result}/${sn}/clean mkdir -p ${result}/${sn}/qc

fastqc ${data}/SC2/${sn}_1.fastq.gz ${data}/SC2/${sn}_2.fastq.gz -o ${result}/${sn}/qc

fastp -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}/qc

conda activate

3. 比对到参考基因组上,得到bam文件并排序

mkdir -p ${result}/${sn}/aligned

if  [ ! -d "/opt/ref/artic-ncov2019" ]; then
	apt-get install -y git
    git 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" ]; then
  mamba env create -f /opt/config/SC2.yaml
fi

conda 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/${artic_primer_version}/nCoV-2019.reference.fasta.sa ]; then
	if [ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta ]; then
    	cp  -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.fasta
    fi
    bwa index /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.reference.fasta
fi

bwa 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}_1_clean.fastq.gz | \
  samtools sort | samtools view -F 4 -o ${result}/${sn}/aligned/${sn}.sorted.bam

samtools 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)

conda activate SC2

if  [ ! -f /opt/ref/artic-ncov2019/ARTIC-${artic_primer_version}.bed ]; then
  if [ ! -f /opt/ref/artic-ncov2019/primer_schemes/nCoV-2019/${artic_primer_version}/nCoV-2019.scheme.bed ]; then
  	cp  -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.bed
  fi
  perl -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
fi

ivar trim -e -i ${result}/${sn}/aligned/${sn}.sorted.bam \
  -b /opt/ref/artic-ncov2019/ARTIC-${artic_primer_version}.bed \
  -p ${result}/${sn}/aligned/${sn}.primertrim
  
conda deactivate

5. primer trim 排序

conda activate SC2

samtools sort ${result}/${sn}/aligned/${sn}.primertrim.bam \
  -o ${result}/${sn}/aligned/${sn}.primertrim.sorted.bam
  
conda deactivate

6. 获取拼接后一致性序列

conda activate SC2

samtools 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 -l

conda 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" ]; then
  mamba env create -f /opt/config/pangolin.yaml
fi

conda activate pangolin

pangolin ${result}/${sn}/${sn}.consensus.fa --outdir ${result}/${sn} 

conda deactivate

8. 获取突变信息

conda activate SC2

if [ ! -f "/opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff" ]; then
  aria2c 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/ref
  gzip -f  -d /opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff.gz
fi

samtools 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.gff

ivar filtervariants -p ${result}/${sn}/${sn}_variantsfiltered ${result}/${sn}/${sn}_variants.tsv
  
conda deactivate

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

conda activate SC2

if [ ! -f "/opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff" ]; then
  aria2c 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/ref
  gzip -f  -d /opt/ref/GCF_009858895.2_ASM985889v3_genomic.gff.gz
fi

quast ${result}/${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}/quast

samtools coverage ${result}/${sn}/aligned/${sn}.sorted.bam -o ${result}/${sn}/aligned/${sn}.samcov.tsv

conda deactivate

10. 报告(可选)

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11. 使用IGV Browser查看突变信息(可选)

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四. 参考链接

https://github.com/artic-network/artic-ncov2019

https://github.com/CDCgov/SARS-CoV-2_Sequencing/tree/master/protocols/BFX-UT_ARTIC_Illumina