Assembly and annotation of metatranscriptomic data, both prokaryotic and eukaryotic.
nf-core/metatdenovo is a bioinformatics best-practice analysis pipeline for assembly and annotation of metatranscriptomic data, both prokaryotic and eukaryotic.
The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources. The results obtained from the full-sized test can be viewed on the nf-core website.
- Read QC (
- Present QC for raw reads (
- Quality trimming and adapter removal for raw reads (
- Optional: Filter sequences with
- Optional: Normalize the sequencing depth with
- Merge trimmed, pair-end reads (
- Choice of de novo assembly programs:
- Choice of orf caller:
- Quantification of genes identified in assemblies:
- Functional annotation:
- Taxonomic annotation:
- Summary statistics table. “Collect_stats.R”
First, prepare a samplesheet with your input data that looks as follows:
Each row represents a fastq file (single-end) or a pair of fastq files (paired-end).
Now, you can run the pipeline using:
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;
To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.
summary_tables directory under the output directory are made especially for further analysis in tools like R or Python.
nf-core/metatdenovo was originally written by Danilo Di Leo (@danilodileo), Emelie Nilsson (@emnilsson) & Daniel Lundin (@erikrikarddaniel).
Contributions and Support
If you would like to contribute to this pipeline, please see the contributing guidelines.
An extensive list of references for the tools used by the pipeline can be found in the
You can cite the
nf-core publication as follows:
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.