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README.md Datei anzeigen

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# 原始数据和比对数据的质量控制

> Author:Ren Luyao
>
> Git: http://choppy.3steps.cn/renluyao/RNAseq_QC.git
>
> Email: 18110700050@fudan.edu.cn
>
> Date: 2020/02/09

# APP概述

本APP包含了原始数据质量控制软件FastQC和FastqScreen和比对质量控制软件Qualimap,以及对多样本数据结果整合的multiqc。

# APP输入

本APP只有一个输入即inputSamplesFile,包含了需要计算样本的fastq read1,bam和bam的index。

这个文件是一个txt,tab分隔,第一列是read1的阿里云地址,第二列是bam,第三列是bam index。每一行是一个样本。可查看模版inputSamplesFileExamples.tsv,**注意:#read1 #bam #bai这一行要删掉**。

```bash
#read1 #bam #bai
```

将准备好的inputSamplesFile文件上传至阿里云。

choppy samples文件中就填inputSamplesFile在阿里云上的地址。

```bash
# 1. 启动choppy
source activate choppy
# 2. 安装APP
choppy install renluyao/RNAseq_QC
# 3. 获得choppy samples的csv文件
choppy samples RNAseq_QC-latest --output RNAseq_qc_samples
# 4. 编辑samples文件
# samples_id,inputSamplesFile
# samples_id是choppy对workflow的编号,写阿拉伯数字就行
# 即
# 1,inputSamplesFile的阿里云地址
# 5. 提交任务
choppy batch RNAseq_QC-latest --project-name <project_name>
# 6. 查询任务
choppy query -s <workflow_id>
choppy query -s <workflow_id> -m
```



# APP输出结果

所有的结果都会整合进multiqc。从阿里云上下载multiqc模块的输出

1. **multiqc.html**
2. **glob_一大串数字的文件夹**

下载上述文件,将**glob_一大串数字的文件夹**名称改成**multiqc**,双击multiqc.html在浏览器中打开就能查看结果了。

如果需要各模块详细的结果,可下载对应结果。

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fastq_screen.conf Datei anzeigen

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# This is an example configuration file for FastQ Screen

############################
## Bowtie, Bowtie 2 or BWA #
############################
## If the Bowtie, Bowtie 2 or BWA binary is not in your PATH, you can set
## this value to tell the program where to find your chosen aligner. Uncomment
## the relevant line below and set the appropriate location. Please note,
## this path should INCLUDE the executable filename.

#BOWTIE /usr/local/bin/bowtie/bowtie
#BOWTIE2 /usr/local/bowtie2/bowtie2
#BWA /usr/local/bwa/bwa



############################################
## Bismark (for bisulfite sequencing only) #
############################################
## If the Bismark binary is not in your PATH then you can set this value to
## tell the program where to find it. Uncomment the line below and set the
## appropriate location. Please note, this path should INCLUDE the executable
## filename.

#BISMARK /usr/local/bin/bismark/bismark



############
## Threads #
############
## Genome aligners can be made to run across multiple CPU cores to speed up
## searches. Set this value to the number of cores you want for mapping reads.

THREADS 32



##############
## DATABASES #
##############
## This section enables you to configure multiple genomes databases (aligner index
## files) to search against in your screen. For each genome you need to provide a
## database name (which can't contain spaces) and the location of the aligner index
## files.
##
## The path to the index files SHOULD INCLUDE THE BASENAME of the index, e.g:
## /data/public/Genomes/Human_Bowtie/GRCh37/Homo_sapiens.GRCh37
## Thus, the index files (Homo_sapiens.GRCh37.1.bt2, Homo_sapiens.GRCh37.2.bt2, etc.)
## are found in a folder named 'GRCh37'.
##
## If, for example, the Bowtie, Bowtie2 and BWA indices of a given genome reside in
## the SAME FOLDER, a SINLGE path may be provided to ALL the of indices. The index
## used will be the one compatible with the chosen aligner (as specified using the
## --aligner flag).
##
## The entries shown below are only suggested examples, you can add as many DATABASE
## sections as required, and you can comment out or remove as many of the existing
## entries as desired. We suggest including genomes and sequences that may be sources
## of contamination either because they where run on your sequencer previously, or may
## have contaminated your sample during the library preparation step.
##
## Human - sequences available from
## ftp://ftp.ensembl.org/pub/current/fasta/homo_sapiens/dna/
#DATABASE Human /data/public/Genomes/Human_Bowtie/GRCh37/Homo_sapiens.GRCh37
##
## Mouse - sequence available from
## ftp://ftp.ensembl.org/pub/current/fasta/mus_musculus/dna/
#DATABASE Mouse /data/public/Genomes/Mouse/NCBIM37/Mus_musculus.NCBIM37
##
## Ecoli- sequence available from EMBL accession U00096.2
#DATABASE Ecoli /data/public/Genomes/Ecoli/Ecoli
##
## PhiX - sequence available from Refseq accession NC_001422.1
#DATABASE PhiX /data/public/Genomes/PhiX/phi_plus_SNPs
##
## Adapters - sequence derived from the FastQC contaminats file found at: www.bioinformatics.babraham.ac.uk/projects/fastqc
#DATABASE Adapters /data/public/Genomes/Contaminants/Contaminants
##
## Vector - Sequence taken from the UniVec database
## http://www.ncbi.nlm.nih.gov/VecScreen/UniVec.html
#DATABASE Vectors /data/public/Genomes/Vectors/Vectors

DATABASE Human /cromwell_root/tmp/fastq_screen_reference/genome
DATABASE Mouse /cromwell_root/tmp/fastq_screen_reference/mouse
DATABASE ERCC /cromwell_root/tmp/fastq_screen_reference/ERCC
DATABASE EColi /cromwell_root/tmp/fastq_screen_reference/ecoli
DATABASE Adapter /cromwell_root/tmp/fastq_screen_reference/adapters
DATABASE Vector /cromwell_root/tmp/fastq_screen_reference/vector
DATABASE rRNA /cromwell_root/tmp/fastq_screen_reference/rRNARef
DATABASE Virus /cromwell_root/tmp/fastq_screen_reference/viral
DATABASE Yeast /cromwell_root/tmp/fastq_screen_reference/GCF_000146045.2_R64_genomic_modify
DATABASE Mitoch /cromwell_root/tmp/fastq_screen_reference/Human_mitoch
DATABASE Phix /cromwell_root/tmp/fastq_screen_reference/phix

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inputSamplesFileExamples.tsv Datei anzeigen

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oss://chinese-quartet/quartet-test-data/WEGENE_T7/Quartet_DNA_BGI_T7_WGE_LCL5_1_20191105_R1.fastq.gz oss://chinese-quartet/quartet-test-data/WEGENE_T7/Quartet_DNA_BGI_T7_WGE_LCL5_1_20191105_R2.fastq.gz oss://pgx-result/renluyao/quality_control/20191223_wegeneT7_sentieon/0214dda2-9408-4bc2-9e7e-322e18d488ad/call-Dedup/Quartet_DNA_BGI_T7_WGE_LCL8_1_20191105.sorted.deduped.bam oss://pgx-result/renluyao/quality_control/20191223_wegeneT7_sentieon/0214dda2-9408-4bc2-9e7e-322e18d488ad/call-Dedup/Quartet_DNA_BGI_T7_WGE_LCL8_1_20191105.sorted.deduped.bam.bai

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inputs Datei anzeigen

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{
"{{ project_name }}.qualimap.docker": "registry.cn-shanghai.aliyuncs.com/pgx-docker-registry/qualimap:2.0.0",
"{{ project_name }}.qualimap.cluster_config": "OnDemand bcs.a2.7xlarge img-ubuntu-vpc",
"{{ project_name }}.fasta": "GRCh38.d1.vd1.fa",
"{{ project_name }}.fastqc.disk_size": "150",
"{{ project_name }}.fastqscreen.cluster_config": "OnDemand bcs.b2.3xlarge img-ubuntu-vpc",
"{{ project_name }}.fastqc.cluster_config": "OnDemand bcs.b2.3xlarge img-ubuntu-vpc",
"{{ project_name }}.fastqc.docker": "registry.cn-shanghai.aliyuncs.com/pgx-docker-registry/fastqc:v0.11.5",
"{{ project_name }}.inputSamplesFile": "{{ inputSamplesFile }}",
"{{ project_name }}.fastqscreen.docker": "registry.cn-shanghai.aliyuncs.com/pgx-docker-registry/fastqscreen:0.12.0",
"{{ project_name }}.screen_ref_dir": "oss://pgx-reference-data/fastq_screen_reference/",
"{{ project_name }}.fastq_screen_conf": "oss://pgx-reference-data/fastq_screen_reference/fastq_screen.conf",
"{{ project_name }}.multiqc.cluster_config": "OnDemand bcs.b2.3xlarge img-ubuntu-vpc",
"{{ project_name }}.qualimap.disk_size": "500",
"{{ project_name }}.multiqc.docker": "registry-vpc.cn-shanghai.aliyuncs.com/pgx-docker-registry/multiqc:v1.8",
"{{ project_name }}.fastqscreen.disk_size": "100",
"{{ project_name }}.multiqc.disk_size": "100",
"{{ project_name }}.ref_dir": "oss://chinese-quartet/quartet-storage-data/reference_data/"
}

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pictures/.DS_Store Datei anzeigen


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tasks/fastqc.wdl Datei anzeigen

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task fastqc {
File read1
String docker
String cluster_config
String disk_size

command <<<
set -o pipefail
set -e
nt=$(nproc)
fastqc -t $nt -o ./ ${read1}
>>>

runtime {
docker:docker
cluster: cluster_config
systemDisk: "cloud_ssd 40"
dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
}
output {
File read1_html = sub(basename(read1), "\\.(fastq|fq)\\.gz$", "_fastqc.html")
File read1_zip = sub(basename(read1), "\\.(fastq|fq)\\.gz$", "_fastqc.zip")
}
}

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tasks/fastqscreen.wdl Datei anzeigen

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task fastq_screen {
File read1
File read2
File screen_ref_dir
File fastq_screen_conf
String read1name = basename(read1,".fastq.gz")
String read2name = basename(read2,".fastq.gz")
String docker
String cluster_config
String disk_size

command <<<
set -o pipefail
set -e
nt=$(nproc)
mkdir -p /cromwell_root/tmp
cp -r ${screen_ref_dir} /cromwell_root/tmp/
fastq_screen --aligner bowtie2 --conf ${fastq_screen_conf} --top 100000 --threads $nt ${read1}
fastq_screen --aligner bowtie2 --conf ${fastq_screen_conf} --top 100000 --threads $nt ${read2}
>>>

runtime {
docker:docker
cluster: cluster_config
systemDisk: "cloud_ssd 40"
dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
}
output {
File png1 = "${read1name}_screen.png"
File txt1 = "${read1name}_screen.txt"
File html1 = "${read1name}_screen.html"
File png2 = "${read2name}_screen.png"
File txt2 = "${read2name}_screen.txt"
File html2 = "${read2name}_screen.html"
}
}

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tasks/multiqc.wdl Datei anzeigen

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task multiqc {

Array[File] read1_zip

Array[File] txt1

Array[File] zip

String docker
String cluster_config
String disk_size

command <<<
set -o pipefail
set -e
mkdir -p /cromwell_root/tmp/fastqc
mkdir -p /cromwell_root/tmp/fastqscreen
mkdir -p /cromwell_root/tmp/bamqc

cp ${sep=" " read1_zip} /cromwell_root/tmp/fastqc
cp ${sep=" " txt1} /cromwell_root/tmp/fastqscreen
for i in ${sep=" " zip}
do
tar -zxvf $i -C /cromwell_root/tmp/bamqc
done

multiqc /cromwell_root/tmp/
>>>

runtime {
docker:docker
cluster:cluster_config
systemDisk:"cloud_ssd 40"
dataDisk:"cloud_ssd " + disk_size + " /cromwell_root/"
}

output {
File multiqc_html = "multiqc_report.html"
Array[File] multiqc_txt = glob("multiqc_data/*")
}
}

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tasks/qualimap.wdl Datei anzeigen

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task qualimap {
File bam
File bai
String bamname = basename(bam,".bam")
String docker
String cluster_config
String disk_size

command <<<
set -o pipefail
set -e
nt=$(nproc)
/opt/qualimap/qualimap bamqc -bam ${bam} -outformat PDF:HTML -nt $nt -outdir ${bamname} --java-mem-size=32G
tar -zcvf ${bamname}_qualimap.zip ${bamname}
>>>

runtime {
docker:docker
cluster:cluster_config
systemDisk:"cloud_ssd 40"
dataDisk:"cloud_ssd " + disk_size + " /cromwell_root/"
}

output {
File zip = "${bamname}_qualimap.zip"
}
}

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workflow.wdl Datei anzeigen

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import "./tasks/fastqc.wdl" as fastqc
import "./tasks/fastqscreen.wdl" as fastqscreen
import "./tasks/qualimap.wdl" as qualimap
import "./tasks/multiqc.wdl" as multiqc

workflow {{ project_name }} {

File inputSamplesFile
Array[Array[File]] inputSamples = read_tsv(inputSamplesFile)
File screen_ref_dir
File fastq_screen_conf
File ref_dir
String fasta

scatter (sample in inputSamples) {
call fastqc.fastqc as fastqc {
input:
read1=sample[0]
}

call fastqscreen.fastq_screen as fastqscreen {
input:
read1=sample[0],
screen_ref_dir=screen_ref_dir,
fastq_screen_conf=fastq_screen_conf
}

call qualimap.qualimap as qualimap {
input:
bam=sample[1],
bai=sample[2]
}

}

call multiqc.multiqc as multiqc {
input:
read1_zip=fastqc.read1_zip,
txt1=fastqscreen.txt1,
zip=qualimap.zip
}

}


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