- GENERAL-INFO
- INSTALL
- RUN
- OUTPUT
- FLOW-DIAGRAM
- TOOLS
- DOCKER
- CONTRIBUTORS
- REMARKS
- REFERENCE
- DISCLAIMER
- LICENSE
This github repository contains an automated pipeline dedicated to properly analyse the EasySeq SARS-CoV-2 (COVID-19) sequence sequencing data. All validation are done using 149 bp or 151 bp paired-end reads.
In short:
- Automated pipeline to analyse Illumina EasySeq COVID-19 samples to a variant report
- The pipeline cleans the Illumina sequencing data
- Uses the SARS-CoV-2 reference genome (NC_045512.2)
- Custom EasySeq Primer filtering and correction
- Mutations and deletions are measured
- Fasta consensus of the sample is created
- Lineage is determined
- Output is available in a structured way
- Full QC reports are created
- PDF and HTML report as output
- install docker on your OS
- docker pull jonovox/easyseq_covid19:latest
- download the newest release of the pipeline via https://github.com/JordyCoolen/easyseq_covid19/releases
- extract the source code
- go into the extracted/project folder
- download conda environments via: https://surfdrive.surf.nl/files/index.php/s/ggoLXzMoa5iSZYa
- extract conda.tar.gz into the project folder created at step 5
- Proceed to RUN examples
- now you have to perform the test to set everything in place
- first time running the variant pipeline will deploy more conda environments needed to successfully install the pipeline. This can take a while.
- open docker runtime container from image with write rights
sh docker/run.sh covid jonovox/easyseq_covid19:latest
- run the test sample inside the container
nextflow run COVID.nf --sampleName test -resume --outDir /workflow/output/test --reads "/workflow/input/test_OUT01_R{1,2}.fastq.gz"
- you can also execute multiple samples in non-parallel way
bash scripts/run_batch.sh <path to folders containing the fastq.gz file> <extension of files> jonovox/easyseq_covid19:latest
/workflow/output/test
|-- HV69-70
| |-- test.aln
| |-- test.frag.gz
| |-- test.fsa
| |-- test.res
| `-- test_HVdel.vcf
|-- QC
| |-- multiqc_data
| | |-- multiqc.log
| | |-- multiqc_data.json
| | |-- multiqc_fastp.txt
| | |-- multiqc_general_stats.txt
| | |-- multiqc_snpeff.txt
| | `-- multiqc_sources.txt
| |-- multiqc_report.html
| |-- test.fastp.json
| |-- test.mosdepth.global.dist.txt
| |-- test.mosdepth.summary.txt
| |-- test.per-base.bed.gz
| |-- test.per-base.bed.gz.csi
| `-- test_snpEff.csv
|-- annotation
| |-- snpEff_summary.html
| |-- test_annot_table.txt
| |-- test_snpEff.csv
| `-- test_snpEff.genes.txt
|-- lineage
| `-- lineage_report.csv
|-- mapping
| |-- test.bam
| |-- test.bam.bai
| |-- test.final.bam
| `-- test.final.bam.bai
|-- rawvcf
| `-- test.vcf.gz
|-- report
| |-- test.fasta
| |-- test.html
| `-- test.pdf
|-- uncovered
| |-- test_noncov.bed
| `-- test_ubiq.bed
|-- vcf
| |-- notpassed
| | `-- test_3G.txt
| |-- test.vcf
| |-- test_final.vcf
| `-- test_table.txt
`-- vcf_index
|-- test_concat.vcf.gz
`-- test_concat.vcf.gz.csi
- nextflow
- python
- conda/bioconda
- fastp
- BWA MEM
- samtools
- bcftools
- mosdepth
- bedtools
- snpEff
- KMA
- multiQC
- pangolin v2.1.11
cd easyseq_covid19
docker build --rm -t <image name> ./
Department of Medical Microbiology and Radboudumc Center for Infectious Diseases, Radboud university medical center, Nijmegen, The Netherlands
- J.P.M. Coolen ([email protected])
NimaGen B.V., Nijmegen, The Netherlands
- R.A. Lammerts (NimaGen B.V., Nijmegen, The Netherlands)
- J.T. Vonk (Student HAN Bioinformatics, Nijmegen, The Netherlands)
spike S
21765-21770HV 69-70 deletion
The current EasySeq design is not completly overlapping the region 21765-21770 / HV 69-70.
----> To solve this a template based strategy using KMA is applied.
<--- This method measures which template matches best. Either Wildtype (NC_045512.2) or
a variant containing the 21765-21770 / HV 69-70 deletion. The result of this strategy
is projected in the VCF to ensure correct output. This works perfect for now because no other deletions are
known on this exact location.
For citing this work please cite:
Novel SARS-CoV-2 Whole-genome sequencing technique using Reverse Complement PCR enables easy, fast and accurate outbreak analysis in hospital and community settings Femke Wolters, Jordy P.M. Coolen, Alma Tostmann, Lenneke F.J. van Groningen, Chantal P. Bleeker-Rovers, Edward C.T.H. Tan, Nannet van der Geest-Blankert, Jeannine L.A. Hautvast, Joost Hopman, Heiman F.L. Wertheim, Janette C. Rahamat-Langendoen, Marko Storch, Willem J.G. Melchers bioRxiv 2020.10.29.360578; doi: https://doi.org/10.1101/2020.10.29.360578.
Also cite the other programs used, see list of used tools
The work is currently under revision.
This is for Research Only. The code and pipeline is continuously under development. We cannot guarantee a full error free result. Especially with the fast developments in SARS-CoV-2/COVID-19 sequencing and the continuously mutating nature of the virus.