This pipeline takes gzipped fastq files and outputs .bam files aligned to NC_045512.2 as well as consensus fastas. Notably this pipeline incorporates primerclip, and can handle both Swift and QiaSeq primersets. Without specifying any additional options, default input files are paired-end fastq files that cover the 116-255 bp amplicons produced from the Swift Amplicon SARS-CoV-2 Panel. --SINGLE_END
can also be specified for single end reads. This pipeline can also be run without the primerclip option by specifying --NO_CLIPPING
for consensus generation of non-Swift or non-QiaSeq SARS-CoV-2 samples.
Command | Description |
---|---|
--INPUT | (Required) Input folder where gzipped fastqs are located. For current directory, ./ can be used. |
--OUTDIR | (Required) Output folder where .bams and consensus fastas will be piped into. |
--SINGLE_END | (Optional) Flag to indicate input reads are single end. By default this pipeline expects paired end reads. |
--NO_CLIPPING | (Optional) Skip primerclip option for shotgun runs. |
--SGRNA_COUNT | (Optional) Add extra step to count sgRNAs. |
--PRIMERS | (Optional) Specify which primerset to use (e.g. --PRIMERS qiaseq ). Default: Swift V2. Options: qiaseq ,artic_v3 , artic_v4 , artic_v4.1 . |
--MIN_LEN | (Optional) Set minimum length for trimming. Default: 75. |
--DOWNSAMPLE | (Optional) Downsample to a number or a fraction of reads using seqtk. |
-with-docker ubuntu:18.04 | (Required) Runs command with Ubuntu docker. |
-resume | (Recommended) nextflow will pick up where it left off if the previous command was interrupted for some reason. |
-with-trace | (Recommended) Outputs a trace.txt that shows which processes end up in which work/ directories. |
-with-report | (Recommended) Outputs a report.html that gives basic stats and work directories for each process. |
-latest | (Recommended) Pulls the most recent github version. |
-profile | (Recommended) Picks which profile in nextflow.config to run (e.g. -profile cloud_big ). If running on AWS, recommended to run with profile cloud_big and for more memory-intensive runs, with profile cloud_bigger ). |
Example paired fastqs are provided in the example/ folder. These can be run with the command:
- Example command for example fastqs:
nextflow run greninger-lab/covid_swift_pipeline -r master -latest --INPUT example/ --OUTDIR output/ -with-trace -with-docker ubuntu:18.04