kherronism/rewarewaannotation is a bioinformatics pipeline built in Nextflow, originally developed for the annotation of the rewarewa (Knightia excelsa) genome. The pipeline takes paired-end RNA-seq reads as input and conducts QC, trimming and alignment. The target genome is repeat masked prior to both the genome and RNA-seq evidence being given as input to BRAKER3.
Default steps in the pipeline:
- Merge re-sequenced FastQ files (
cat
) - Read QC (
FastQC
) - Adapter and quality trimming (
Trim Galore!
) - Trimmed read QC (
FastQC
) - OPTIONAL:
- a. Hardtrimming (
Trim Galore!
) - b. Hardtrimmed read QC (
FastQC
)
- a. Hardtrimming (
- Alignment (
STAR
) - Alignment summary metrics (
picard CollectAlignmentSummaryMetrics
) - Assembly QC (
BUSCO
) - Build custom repeat database (
RepeatModeler
) - Mask repeats in genome assembly (
RepeatMasker
) - Genome annotation (
BRAKER3
) - Annotation QC (
BUSCO
) - Annotation summary metrics (
agat spstatistics
) - Present QC for raw reads, alignment and annotation (
MultiQC
)
Note If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with
-profile test
before running the workflow on actual data.
Pipeline usage is covered more comprehensively on this page.
In brief:
Prepare a samplesheet with your input data that looks as follows:
samplesheet.csv
:
sample_id,file1,file2
SAMPLE_1,SAMPLE_1_R1.fastq.gz,SAMPLE_1_R2.fastq.gz,
SAMPLE_2,SAMPLE_2_R1.fastq.gz,SAMPLE_2_R2.fastq.gz,
<...>
Each row represents a pair of fastq files (paired end). This pipeline only accepts paired-end reads. Input files can be compressed or uncompressed. Re-sequenced samples will be merged into a single fastq file at the start of the pipeline.
Now, you can run the pipeline using:
nextflow run kherronism/rewarewaannotation \
-profile <docker/singularity/.../institute> \
--input samplesheet.csv \
--assembly <ASSEMBLY_FILE> \
--assembly_name <ASSEMBLY_NAME> \
--outdir <OUTDIR>
You can also git clone
this repository and then run the pipeline locally:
nextflow run main.nf \
-profile <docker/singularity/.../institute> \
--input samplesheet.csv \
--assembly <ASSEMBLY_FILE> \
--assembly_name <ASSEMBLY_NAME> \
--outdir <OUTDIR>
For a full breakdown of available params for the pipeline see this page.
To resume a run, add the -resume
flag and Nextflow will take care of the rest.
To re-run the pipeline with the parameters used for rewarewa (example samplesheet.csv and params file given in test-datasets/kniExce
folder):
nextflow run kherronism/rewarewaannotation \
-profile <docker/singularity/.../institute> \
-params-file test-datasets/kniExec/rewarewa_params.config
Also included in test-datasets/kniExce
are a few helper files:
environment.yml
: For creating a conda environment for Nextflow and nf-core.rewarewa_params.yml
: A params file containing the parameters for reproducing the rewarewa annotation.rewarewa_slurm.sh
: Example of how to submit the pipeline run as a job on a slurm cluster. However, this does require giving Nextflow an additional config file, which is dependent on the set-up of the institutional cluster. See this page and nf-core/configs for more details.- As an example, the
sonic.config
file intest-datasets/kniExce
is a config file for the Sonic HPC cluster.
- As an example, the
Warning: Please provide pipeline parameters via the CLI or Nextflow
-params-file
option. Custom config files including those provided by the-c
Nextflow option can be used to provide any configuration except for parameters; see docs.
For a breakdown of the outputs of the pipeline see this page.
Pipeline originally written and implemented by Ann McCartney and ported to Nextflow by Katie Herron.
An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md
file.
This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.
The nf-core framework for community-curated bioinformatics pipelines.
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.