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quartet-wgs-germline-qc
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LUYAO REN 5 years ago
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  1. +150
    -9
      README.md
  2. +60
    -0
      codescripts/D5_D6.py
  3. +50
    -0
      codescripts/how_many_samples.py
  4. +49
    -0
      tasks/D5_D6.wdl
  5. +0
    -42
      tasks/TNscope.wdl
  6. +0
    -43
      tasks/TNseq.wdl
  7. +0
    -31
      tasks/joint_variant_calling.wdl
  8. +56
    -0
      tasks/merge_family.wdl
  9. +10
    -10
      tasks/merge_mendelian.wdl
  10. +4
    -4
      tasks/multiqc.wdl
  11. +8
    -69
      tasks/split_gvcf_files.wdl
  12. +51
    -24
      workflow.wdl

+ 150
- 9
README.md View File

@@ -96,11 +96,99 @@ hap.py <truth_vcf> <query_vcf> -f <bed_file> --threads <threads> -o <output_file
vbt mendelian -ref <fasta_file> -mother <family_merged_vcf> -father <family_merged_vcf> -child <family_merged_vcf> -pedigree <ped_file> -outDir <output_directory> -out-prefix <output_directory_prefix> --output-violation-regions -thread-count <threads>
```

## App输入文件

```bash
choppy samples WGS_germline_datapotal-latest --output samples
```

####Samples文件的输入包括

**inputSamplesFile**

```bash
#read1 #read2 #sample_name
```

read1 是阿里云上fastq read1的地址

read2 是阿里云上fastq read2的地址

sample_name是指样本的命名

所有上传的文件应有规范的命名

Quartet_DNA_SequenceTech_SequenceMachine_SequenceSite_Sample_Replicate_Date.R1/R2.fastq.gz

SequenceTech是指测序平台，如ILM、BGI等

SequenceMachine是指测序仪器，如XTen、Nova、Hiseq（Illumina）、SEQ500、SEQ1000（BGI）等

SequenceSite是指测序单位的英文缩写

Sample是指LCL5、LCL6、LCL7、LCL8

Replicate是指技术重复，从1开始依次增加

Date是指数据获得日期，格式为20200710

后缀一定是R1/R2.fastq.gz，不可以随意更改，R1/R2不可以写成r1/r2，fastq.gz不可以写成fq.gz

各个缩写规范请见 https://fudan-pgx.yuque.com/docs/share/5baa851b-da97-47b9-b6c4-78f2b60595ab?# 《数据命名规范》

**project**

这个项目的名称，可以写自己可以识别的字符串，只能写英文和数字，不可以写中文

#### Quartet样本的组合问题

##### 1. 没有测LCL5和LCL6，或者没有同时测LCL5和LCL6

只给出原始数据质控、比对数据质控、与标准集的比较

##### 2. 包含LCL5和LCL6同卵双胞胎的数据，但是父母的数据不全

只给出原始数据质控、比对数据质控、与标准集的比较、同卵双胞胎一致性

##### 3. 四个quartet样本都测了

给出所有结果原始数据质控、比对数据质控、与标准集的比较、同卵双胞胎一致性，符合孟德尔遗传比例

**注意**：本app假设每个批次测的技术重复都一样，如batch 1测了LCL5、LCL6、LCL7和LCL8，batch 2 和batch 3也都测了这四个样本。本app不解决特别复杂的问题，例如batch1测了LCL5，LCL6，batch2测了LCL7和LCL8，本app只能给出原始数据质控、比对数据质控、与标准集的比较，不会把多个批次的数据合并计算孟德尔符合率和姐妹一致性。

## App输出文件

本计算会产生大量的中间结果，这里说明最后整合好的结果文件，一共5个文件。
本计算会产生大量的中间结果，这里说明最后整合好的结果文件，上述的三种情况得到的结果文件如下。

####1. 原始数据质量控制
###1. 没有测LCL5和LCL6，或者没有同时测LCL5和LCL6

####1.1 原始数据质量控制

####1.2 比对后数据质量控制

##### 输出目录

extract_multiqc

##### 输出结果文件

qualimap.final.result.txt

####1.3 突变检出数据质量控制

#####与标准集进行比较

######输出目录

extract_multiqc

######输出结果文件

benchmark.final.result.txt

###2. 包含LCL5和LCL6同卵双胞胎的数据，但是父母的数据不全

#### 2.1 原始数据质量控制

##### 输出目录

@@ -112,7 +200,7 @@ fastqc.final.result.txt

fastqscreen.final.result.txt

####2. 比对后数据质量控制
#### 2.2 比对后数据质量控制

##### 输出目录

@@ -122,19 +210,65 @@ extract_multiqc

qualimap.final.result.txt

####3. 突变检出数据质量控制
#### 2.3 突变检出数据质量控制

#####3.1 与标准集进行比较
##### 2.3.1 与标准集进行比较

######输出目录
#####输出目录

extract_multiqc

######输出结果文件
#####输出结果文件

benchmark.final.result.txt

##### 3.2 通过Quartet家系设计
**2.3.2** **姐妹一致性**

##### 输出目录

D5_D6

##### 输出结果文件

${project}.sister.txt

### 3. 四个quartet样本都测了

#### 3.1 原始数据质量控制

##### 输出目录

extract_multiqc

##### 输出结果文件

fastqc.final.result.txt

fastqscreen.final.result.txt

#### 3.2 比对后数据质量控制

##### 输出目录

extract_multiqc

##### 输出结果文件

qualimap.final.result.txt

#### 3.3 突变检出数据质量控制

##### 3.3.1 与标准集进行比较

###### 输出目录

extract_multiqc

###### 输出结果文件

benchmark.final.result.txt

##### 3.3.2 通过Quartet家系设计

###### 输出目录

@@ -221,7 +355,14 @@ FastQC和FastqScreen是两个常用的原始数据质量控制软件
| Precision | 查准率 |
| Recall | 查全率 |

#####3.2 Quartet家系关系评估 ${project}.mendelian.txt
##### 3.2 姐妹一致性 ${project}.sister.txt （样本没有没有测全，但是同时测了LCL5和LCL6）

| 列名 | 说明 |
| --------------------- | ------------------------------------------------------------ |
| Family | 家庭名字，我们目前的设计是4个Quartet样本，每个三个技术重复，family_1是指rep1的4个样本组成的家庭单位，以此类推。 |
| Reproducibility_D5_D6 | Quartet-D5和Quartet-D6的一致性 |

#####3.3 Quartet家系关系评估 ${project}.mendelian.txt

| 列名 | 说明 |
| ----------------------------- | ------------------------------------------------------------ |

+ 60
- 0
codescripts/D5_D6.py View File

@@ -0,0 +1,60 @@
from __future__ import division
import pandas as pd
import sys, argparse, os


# input arguments
parser = argparse.ArgumentParser(description="this script is to calculate reproducibility between Quartet_D5 and Quartet_D6s")

parser.add_argument('-sister', '--sister', type=str, help='sister.txt', required=True)
parser.add_argument('-project', '--project', type=str, help='project name', required=True)


args = parser.parse_args()
sister_file = args.sister
project_name = args.project

# output file
output_name = project_name + '.sister.reproducibility.txt'

output_file = open(output_name,'w')

# input files
sister_dat = pd.read_table(sister_file)

sister_same = 0
sister_diff = 0

for row in sister_dat.itertuples():
# sister
if row[5] == row[6]:
if row[5] == './.':
mendelian = 'noInfo'
sister_count = "no"
elif row[5] == '0/0':
mendelian = 'Ref'
sister_count = "no"
else:
mendelian = '1'
sister_count = "yes_same"
else:
mendelian = '0'
if (row[5] == './.' or row[5] == '0/0') and (row[6] == './.' or row[6] == '0/0'):
sister_count = "no"
else:
sister_count = "yes_diff"
if sister_count == 'yes_same':
sister_same += 1
elif sister_count == 'yes_diff':
sister_diff += 1
else:
pass

sister = sister_same/(sister_same + sister_diff)
outcolumn = 'Project\tReproducibility_D5_D6\n'
outResult = project_name + '\t' + str(sister) + '\n'
output_file.write(outcolumn)
output_file.write(outResult)




+ 50
- 0
codescripts/how_many_samples.py View File

@@ -0,0 +1,50 @@
import pandas as pd
import sys, argparse, os
from operator import itemgetter

parser = argparse.ArgumentParser(description="This script is to get how many samples")

parser.add_argument('-sample', '--sample', type=str, help='quartet_sample', required=True)
parser.add_argument('-rep', '--rep', type=str, help='quartet_rep', required=True)
args = parser.parse_args()

# Rename input:
sample = args.sample
rep = args.rep

quartet_sample = pd.read_table(sample,header=None)
quartet_sample = list(quartet_sample[0])
quartet_rep = pd.read_table(rep.header=None)
quartet_rep = quartet_rep[0]

#tags
sister_tag = 'false'
quartet_tag = 'false'

quartet_rep_unique = list(set(quartet_rep))

single_rep = [i for i in range(len(quartet_rep)) if quartet_rep[i] == quartet_rep_unique[0]]
single_batch_sample = itemgetter(*single_rep)(quartet_sample)

num = len(single_batch_sample)
if num == 1:
sister_tag = 'false'
quartet_tag = 'false'
elif num == 2:
if set(single_batch_sample) == set(['LCL5','LCL6']):
sister_tag = 'true'
quartet_tag = 'false'
elif num == 3:
if ('LCL5' in single_batch_sample) and ('LCL6' in single_batch_sample):
sister_tag = 'true'
quartet_tag = 'false'
elif num == 4:
if set(single_batch_sample) == set(['LCL5','LCL6','LCL7','LCL8']):
sister_tag = 'false'
quartet_tag = 'true'

sister_outfile = open('sister_tag','w')
quartet_outfile = open('quartet_tag','w')

sister_outfile.write(sister_tag)
quartet_outfile.write(quartet_tag)

+ 49
- 0
tasks/D5_D6.wdl View File

@@ -0,0 +1,49 @@
task D5_D6 {
Array[File] splited_vcf
String project
String docker
String cluster_config
String disk_size
command <<<

mkdir -p /cromwell_root/tmp/vcf

cp ${sep=" " splited_vcf} /cromwell_root/tmp/vcf

for i in /cromwell_root/tmp/vcf/*vcf
do
for j in /cromwell_root/tmp/vcf/*vcf
do
sample_i=$(echo $i | cut -f7 -d_)
sample_j=$(echo $j | cut -f7 -d_)
rep_i=$(echo $i | cut -f8 -d_)
rep_j=$(echo $j | cut -f8 -d_)
if [[ $sample_i == "LCL5" ] && [ $sample_j == "LCL6" ] && [ $rep_i == $rep_j ]];then
cat $i | grep -v '##' | cut -f1,2,4,5,10 | cut -d ':' -f1 > LCL5.txt
cat $j | grep -v '##' | cut -f10 | cut -d ':' -f1 > LCL6.txt
paste LCL5.txt LCL6.txt > sister.txt
python /opt/D5_D6.py -sister sister.txt -project ${project}.$rep_i
fi
done
done

for i in *.reproducibility.txt
do
cat $i | sed -n '2,2p' >> sister.summary
done
sed '1i\Family\tReproducibility_D5_D6' sister.summary > ${project}.sister.txt

>>>

runtime {
docker:docker
cluster: cluster_config
systemDisk: "cloud_ssd 40"
dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
}
output {
Array[File] sister_file = glob("*.reproducibility.txt")
File sister_summary = "${project}.sister.txt"
}
}

+ 0
- 42
tasks/TNscope.wdl View File

@@ -1,42 +0,0 @@
task TNscope {

File ref_dir
File dbsnp_dir

String SENTIEON_INSTALL_DIR
String tumor_name
String normal_name
String docker
String cluster_config

String fasta
File corealigner_bam
File corealigner_bam_index
String dbsnp
String disk_size

command <<<
set -o pipefail
set -e
export SENTIEON_LICENSE=192.168.0.55:8990
nt=$(nproc)
${SENTIEON_INSTALL_DIR}/bin/sentieon driver -r ${ref_dir}/${fasta} -t $nt -i ${corealigner_bam} --algo TNscope --tumor_sample ${tumor_name} --normal_sample ${normal_name} --dbsnp ${dbsnp_dir}/${dbsnp} ${sample}.TNscope.TN.vcf
>>>

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

output {
File TNscope_vcf= "${sample}.TNscope.TN.vcf"
File TNscope_vcf_index = "${sample}.TNscope.TN.vcf.idx"
}

}

+ 0
- 43
tasks/TNseq.wdl View File

@@ -1,43 +0,0 @@
task TNseq {
File ref_dir
File dbsnp_dir

String SENTIEON_INSTALL_DIR
String tumor_name
String normal_name
String docker
String cluster_config

String fasta
File corealigner_bam
File corealigner_bam_index
String dbsnp
String disk_size

command <<<
set -o pipefail
set -e
export SENTIEON_LICENSE=192.168.0.55:8990
nt=$(nproc)
${SENTIEON_INSTALL_DIR}/bin/sentieon driver -r ${ref_dir}/${fasta} -t $nt -i ${corealigner_bam} --algo TNhaplotyper --tumor_sample ${tumor_name} --normal_sample ${normal_name} --dbsnp ${dbsnp_dir}/${dbsnp} ${sample}.TNseq.TN.vcf
>>>

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

output {
File TNseq_vcf= "${sample}.TNseq.TN.vcf"
File TNseq_vcf_index = "${sample}.TNseq.TN.vcf.idx"
}

}



+ 0
- 31
tasks/joint_variant_calling.wdl View File

@@ -1,31 +0,0 @@
task joint_variant_calling {
File merged_bed
String sample
String docker
String disk_size
String cluster_config

command <<<
sentieon driver -r REFERENCE --algo GVCFtyper -v s1_VARIANT_GVCF \ -v s2_VARIANT_GVCF -v s3_VARIANT_GVCF VARIANT_VCF

>>>

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

output {
File consensus_bed = "${sample}.27consensus.bed"
File filtered_bed = "${sample}.filtered.bed"
}
}





+ 56
- 0
tasks/merge_family.wdl View File

@@ -0,0 +1,56 @@
task merge_family {
Array[File] splited_vcf
String project
String docker
String cluster_config
String disk_size
command <<<

mkdir -p /cromwell_root/tmp/vcf

cp ${sep=" " splited_vcf} /cromwell_root/tmp/vcf

for a in /cromwell_root/tmp/vcf/*vcf
do
for b in /cromwell_root/tmp/vcf/*vcf
do
for c in /cromwell_root/tmp/vcf/*vcf
do
for d in /cromwell_root/tmp/vcf/*vcf
do
sample_a=$(echo $a | cut -f7 -d_)
sample_b=$(echo $b | cut -f7 -d_)
sample_c=$(echo $c | cut -f7 -d_)
sample_d=$(echo $d | cut -f7 -d_)
rep_a=$(echo $a | cut -f8 -d_)
rep_b=$(echo $b | cut -f8 -d_)
rep_c=$(echo $c | cut -f8 -d_)
rep_d=$(echo $d | cut -f8 -d_)
if [ $sample_a == "LCL5" ] && [ $sample_b == "LCL6" ] && [ $sample_c == "LCL7" ] && [ $sample_d == "LCL8" ] && [ $rep_a == $rep_b ] && [ $rep_c == $rep_d ] && [ $rep_b == $rep_c ];then
cat $a | grep -v '#' > LCL5.body
cat $b | grep -v '#' | cut -f 10 > LCL6.body
cat $c | grep -v '#' | cut -f 10 > LCL7.body
cat $d | grep -v '#' | cut -f 10 > LCL8.body
echo -e "#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO\tFORMAT\tLCL5\tLCL6\tLCL7\tLCL8" > header_name
cat $a | grep '##' | cat - header_name > header
paste LCL5.body LCL6.body LCL7.body LCL8.body > family.body
cat header family.body > ${project}.$rep_a.family.vcf
fi
done
done
done
done

>>>

runtime {
docker:docker
cluster: cluster_config
systemDisk: "cloud_ssd 40"
dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
}
output {
Array[File] family_vcf = glob("*.family.vcf")
}
}

+ 10
- 10
tasks/merge_mendelian.wdl View File

@@ -11,14 +11,14 @@ task merge_mendelian {
cat ${D5_trio_vcf} | grep -v '##' > ${family_name}.D5.txt
cat ${D6_trio_vcf} | grep -v '##' > ${family_name}.D6.txt
cat ${family_vcf} | grep -v '##' | awk '
BEGIN { OFS = "\t" }
NF > 2 && FNR > 1 {
for ( i=9; i<=NF; i++ ) {
split($i,a,":") ;$i = a[1];
}
}
{ print }
' > ${family_name}.consensus.txt
BEGIN { OFS = "\t" }
NF > 2 && FNR > 1 {
for ( i=9; i<=NF; i++ ) {
split($i,a,":") ;$i = a[1];
}
}
{ print }
' > ${family_name}.consensus.txt
python /opt/merge_two_family_with_genotype.py -LCL5 ${family_name}.D5.txt -LCL6 ${family_name}.D6.txt -genotype ${family_name}.consensus.txt -family ${family_name}
>>>

@@ -29,7 +29,7 @@ task merge_mendelian {
dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
}
output {
File project_mendelian = "${family_name}.mendelian.txt"
File project_mendelian_summary = "${family_name}.mendelian.summary.txt"
File project_mendelian = "${family_name}.txt"
File project_mendelian_summary = "${family_name}.summary.txt"
}
}

+ 4
- 4
tasks/multiqc.wdl View File

@@ -31,10 +31,10 @@ task multiqc {

multiqc /cromwell_root/tmp/

cp multiqc_data/multiqc_general_stats.txt > multiqc_general_stats.txt
cp multiqc_data/multiqc_fastqc.txt > multiqc_fastqc.txt
cp multiqc_data/multiqc_fastq_screen.txt > multiqc_fastq_screen.txt
cp multiqc_data/multiqc_happy_data.json > multiqc_happy_data.json
cat multiqc_data/multiqc_general_stats.txt > multiqc_general_stats.txt
cat multiqc_data/multiqc_fastqc.txt > multiqc_fastqc.txt
cat multiqc_data/multiqc_fastq_screen.txt > multiqc_fastq_screen.txt
cat multiqc_data/multiqc_happy_data.json > multiqc_happy_data.json
>>>


+ 8
- 69
tasks/split_gvcf_files.wdl View File

@@ -1,4 +1,4 @@
task split_gvcf_files {
task split_gvcf_files {
File gvcf
String project
String docker
@@ -18,7 +18,6 @@ task split_gvcf_files {
cat body | grep -w '^chr1\|^chr2\|^chr3\|^chr4\|^chr5\|^chr6\|^chr7\|^chr8\|^chr9\|^chr10\|^chr11\|^chr12\|^chr13\|^chr14\|^chr15\|^chr16\|^chr17\|^chr18\|^chr19\|^chr20\|^chr21\|^chr22\|^chrX' > body.filtered
cat header body.filtered > ${project}.filtered.g.vcf


for i in $(seq 10 $ncol); do cat ${project}.filtered.g.vcf | cut -f1-9,$i > $i.splited.vcf; done

ls *splited.vcf | sort -n | paste - name > rename
@@ -26,62 +25,13 @@ task split_gvcf_files {
cat rename | while read a b
do
mv $a $b.splited.vcf
if [[ $b.vcf =~ "LCL5_1" ]];then
cp $b.splited.vcf ${project}.LCL5_1.vcf
elif [[ $b.vcf =~ "LCL5_2" ]]; then
cp $b.splited.vcf ${project}.LCL5_2.vcf
elif [[ $b.vcf =~ "LCL5_3" ]]; then
cp $b.splited.vcf ${project}.LCL5_3.vcf
elif [[ $b.vcf =~ "LCL6_1" ]]; then
cp $b.splited.vcf ${project}.LCL6_1.vcf
elif [[ $b.vcf =~ "LCL6_2" ]]; then
cp $b.splited.vcf ${project}.LCL6_2.vcf
elif [[ $b.vcf =~ "LCL6_3" ]]; then
cp $b.splited.vcf ${project}.LCL6_3.vcf
elif [[ $b.vcf =~ "LCL7_1" ]]; then
cp $b.splited.vcf ${project}.LCL7_1.vcf
elif [[ $b.vcf =~ "LCL7_2" ]]; then
cp $b.splited.vcf ${project}.LCL7_2.vcf
elif [[ $b.vcf =~ "LCL7_3" ]]; then
cp $b.splited.vcf ${project}.LCL7_3.vcf
elif [[ $b.vcf =~ "LCL8_1" ]]; then
cp $b.splited.vcf ${project}.LCL8_1.vcf
elif [[ $b.vcf =~ "LCL8_2" ]]; then
cp $b.splited.vcf ${project}.LCL8_2.vcf
elif [[ $b.vcf =~ "LCL8_3" ]]; then
cp $b.splited.vcf ${project}.LCL8_3.vcf
fi
sample=$(echo $b | cut -f6 -d_)
rep=$(echo $b | cut -f7 -d_)
echo $sample >> quartet_sample
echo $rep >> quartet_rep
done

cat ${project}.LCL5_1.vcf | grep -v '#' > LCL5_1.body
cat ${project}.LCL5_2.vcf | grep -v '#' > LCL5_2.body
cat ${project}.LCL5_3.vcf | grep -v '#' > LCL5_3.body

cat ${project}.LCL6_1.vcf | grep -v '#' | cut -f 10 > LCL6_1.body
cat ${project}.LCL6_2.vcf | grep -v '#' | cut -f 10 > LCL6_2.body
cat ${project}.LCL6_3.vcf | grep -v '#' | cut -f 10 > LCL6_3.body

cat ${project}.LCL7_1.vcf | grep -v '#' | cut -f 10 > LCL7_1.body
cat ${project}.LCL7_2.vcf | grep -v '#' | cut -f 10 > LCL7_2.body
cat ${project}.LCL7_3.vcf | grep -v '#' | cut -f 10 > LCL7_3.body

cat ${project}.LCL8_1.vcf | grep -v '#' | cut -f 10 > LCL8_1.body
cat ${project}.LCL8_2.vcf | grep -v '#' | cut -f 10 > LCL8_2.body
cat ${project}.LCL8_3.vcf | grep -v '#' | cut -f 10 > LCL8_3.body

echo -e "#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO\tFORMAT\tLCL5\tLCL6\tLCL7\tLCL8" > header_name

cat ${project}.LCL5_1.vcf | grep '##' | cat - header_name > header

paste LCL5_1.body LCL6_1.body LCL7_1.body LCL8_1.body > family_1.body
paste LCL5_2.body LCL6_2.body LCL7_2.body LCL8_2.body > family_2.body
paste LCL5_3.body LCL6_3.body LCL7_3.body LCL8_3.body > family_3.body

cat header family_1.body > ${project}.1.family.vcf
cat header family_2.body > ${project}.2.family.vcf
cat header family_3.body > ${project}.3.family.vcf


python /opt/how_many_samples.py -sample quartet_sample -rep quartet_rep


>>>
@@ -94,18 +44,7 @@ task split_gvcf_files {
}
output {
Array[File] splited_vcf = glob("*.splited.vcf")
Array[File] family_vcf = glob("*.family.vcf")
File LCL5_1 = "${project}.LCL5_1.vcf"
File LCL5_2 = "${project}.LCL5_2.vcf"
File LCL5_3 = "${project}.LCL5_3.vcf"
File LCL6_1 = "${project}.LCL6_1.vcf"
File LCL6_2 = "${project}.LCL6_2.vcf"
File LCL6_3 = "${project}.LCL6_3.vcf"
File LCL7_1 = "${project}.LCL7_1.vcf"
File LCL7_2 = "${project}.LCL7_2.vcf"
File LCL7_3 = "${project}.LCL7_3.vcf"
File LCL8_1 = "${project}.LCL8_1.vcf"
File LCL8_2 = "${project}.LCL8_2.vcf"
File LCL8_3 = "${project}.LCL8_3.vcf"
File sister_tag = "sister_tag"
File quartet_tag = "quartet_tag"
}
}

+ 51
- 24
workflow.wdl View File

@@ -16,6 +16,9 @@ import "./tasks/fastqc.wdl" as fastqc
import "./tasks/fastqscreen.wdl" as fastqscreen
import "./tasks/qualimap.wdl" as qualimap
import "./tasks/extract_multiqc.wdl" as extract_multiqc
import "./tasks/D5_D6.wdl" as D5_D6
import "./tasks/merge_family.wdl" as merge_family


workflow {{ project_name }} {

@@ -191,12 +194,13 @@ workflow {{ project_name }} {
call split_gvcf_files.split_gvcf_files as split_gvcf_files {
input:
gvcf=GVCFtyper.gvcf,
docker=BENCHMARKdocker,
docker=DIYdocker,
project=project,
cluster_config=SMALLcluster_config,
disk_size=disk_size
}


Array[File] single_gvcf = split_gvcf_files.splited_vcf

scatter (idx in range(length(single_gvcf))) {
@@ -236,39 +240,62 @@ workflow {{ project_name }} {
disk_size=disk_size
}

Array[File] family_vcfs = split_gvcf_files.family_vcf
Boolean sister_tag = read_boolean(split_gvcf_files.sister_tag)
Boolean quartet_tag = read_boolean(split_gvcf_files.quartet_tag)

scatter (idx in range(length(family_vcfs))) {
call mendelian.mendelian as mendelian {
if (sister_tag) {
call D5_D6.D5_D6 as D5_D6 {
input:
family_vcf=family_vcfs[idx],
ref_dir=ref_dir,
fasta=fasta,
docker=MENDELIANdocker,
cluster_config=BIGcluster_config,
disk_size=disk_size
splited_vcf=split_gvcf_files.splited_vcf,
project=project,
docker=DIYdocker,
cluster_config=SMALLcluster_config,
disk_size=disk_size,
}
}

call merge_mendelian.merge_mendelian as merge_mendelian {
if (quartet_tag) {
call merge_family.merge_family as merge_family {
input:
D5_trio_vcf=mendelian.D5_trio_vcf,
D6_trio_vcf=mendelian.D6_trio_vcf,
family_vcf=family_vcfs[idx],
splited_vcf=split_gvcf_files.splited_vcf,
project=project,
docker=DIYdocker,
cluster_config=SMALLcluster_config,
disk_size=disk_size
disk_size=disk_size,
}
}

call quartet_mendelian.quartet_mendelian as quartet_mendelian {
input:
project_mendelian_summary=merge_mendelian.project_mendelian_summary,
project=project,
docker=DIYdocker,
cluster_config=SMALLcluster_config,
disk_size=disk_size
}
Array[File] family_vcfs = merge_family.family_vcf
scatter (idx in range(length(family_vcfs))) {
call mendelian.mendelian as mendelian {
input:
family_vcf=family_vcfs[idx],
ref_dir=ref_dir,
fasta=fasta,
docker=MENDELIANdocker,
cluster_config=BIGcluster_config,
disk_size=disk_size
}

call merge_mendelian.merge_mendelian as merge_mendelian {
input:
D5_trio_vcf=mendelian.D5_trio_vcf,
D6_trio_vcf=mendelian.D6_trio_vcf,
family_vcf=family_vcfs[idx],
docker=DIYdocker,
cluster_config=SMALLcluster_config,
disk_size=disk_size
}
}

call quartet_mendelian.quartet_mendelian as quartet_mendelian {
input:
project_mendelian_summary=merge_mendelian.project_mendelian_summary,
project=project,
docker=DIYdocker,
cluster_config=SMALLcluster_config,
disk_size=disk_size
}
}
}



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