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meng 2 年前
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version 1.0

workflow fastp {
input{
Array[String] samples
File fastq_dir
}

scatter (sample_id in samples){
call pair_end{
input:
in1 = fastq_dir+'/'+sample_id+'_1.fastq',
in2 = fastq_dir+'/'+sample_id+'_2.fastq',
sample_id = sample_id
}
}

# output {
# File clean_out1 = pair_end.out1
# File clean_out2 = pair_end.out2
# File html_report = pair_end.html_report
# File json_report = pair_end.json_report
# }

}

task pair_end {

input {
# I/O options
File in1
File in2
String sample_id

Boolean? phred64 = false
Boolean? fix_mgi_id = false

String? adapter_sequence
String? adapter_sequence_r2

Int? reads_to_process # specify how many reads/pairs to be processed. Default 0 means process all reads.

# reporting options
String json = sample_id+"fastp.json"
String html = sample_id+"fastp.html"
String report_title = "\'fastp report\'"

# excute env
Int cpu = 2
String memory = "4G"
String disks = "local-disk 50 cloud_ssd"

}

String out1_name = sample_id+'clean_1.fastq'
String out2_name = sample_id+'clean_2.fastq'

command <<<

# basic command
/opt/conda/bin/fastp \
--in1 ~{in1} \
--in2 ~{in2} \
--out1 ~{out1_name} \
--out2 ~{out2_name} \
--json ~{json} \
--html ~{html} \
--report_title ~{report_title} \
# options
~{ true="--phred64 " false="" phred64 } \
~{ "--reads_to_process " + reads_to_process } \
~{ true="--fix_mgi_id " false="" fix_mgi_id } \
~{ "--adapter_sequence " + adapter_sequence } \
~{ "--adapter_sequence_r2 " + adapter_sequence_r2 }

>>>

runtime {
cpu: cpu
memory: memory
disks: disks
docker: "registry-vpc.cn-shanghai.aliyuncs.com/easygene/fastp:v0.20.1_cv1"
}

output {
File out1 = out1_name
File out2 = out2_name
File json_report = json
File html_report = html
}

}

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