gms_16S bioinformatics analysis pipeline for the EMU tool.
This Nextflow pipeline utilizes FastQC, Nanoplot, MultiQC, Porechop_ABI, Longfilt, EMU, and Krona. EMU is the tool that does the taxonomic profiling of 16S rRNA reads. The results are displayed with Krona. Built with Nextflow, it ensures portability and reproducibility across different computational infrastructures. It has been tested on Linux and on mac M1 (not recommended, quite slow). FastQC and Nanoplot performs quality control, Porechop_ABI trims adapters (optional)), Longfilt filters the fastq-files such that only reads that are close to 1500 bp are used (optional), EMU assigns taxonomic classifications, and Krona visualises the result table from EMU. The pipeline enables microbial community analysis, offering insights into the diversity in samples.
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.
Roadmap/workflow. Only the NanoPore flow is available. Minor testing has been done for PacBio and it seems to work. short read has no support yet. MultiQC collects only info from FastQC and some information about software versions and pipeline info.
Krona plot
>=22.10.1
)sample_sheet.csv
. See examples.assets/databases/emu_database
)assets/databases/krona/taxonomy
)nextflow run main.nf \
--input sample_sheet.csv
--outdir [absolute path]/gms_16S/results \
--db /[absolute path]/gms_16S/assets/databases/emu_database \
--seqtype map-ont \
-profile singularity,test \
--quality_filtering \
--longread_qc_qualityfilter_minlength 1200 \
--longread_qc_qualityfilter_maxlength 1800
You can run with or without a sample sheet. If no sample_sheet is used, the
results will be named according to the barcode. If a sample sheet is used the
results will be named after whats in the second column of the sample sheet. Note
that the --input
flag is not needed when --merge_fastq_pass
is defined.
Run without barcode sample sheet:
nextflow run main.nf \
--outdir [absolute path]/gms_16S/results \
--db /[absolute path]/gms_16S/assets/databases/emu_database \
--seqtype map-ont \
-profile singularity,test \
--quality_filtering \
--longread_qc_qualityfilter_minlength 1200 \
--longread_qc_qualityfilter_maxlength 1800 \
--merge_fastq_pass /[absolute path]/gms_16S/fastq_pass/
Run with barcode sample sheet:
nextflow run main.nf \
--outdir /[absolute path to]/gms_16S/results \
--db /[absolute path to database]/gms_16S/assets/databases/emu_database \
--seqtype map-ont \
-profile singularity,test \
--quality_filtering \
--longread_qc_qualityfilter_minlength 1200 \
--longread_qc_qualityfilter_maxlength 1800 \
--merge_fastq_pass /[absolute path to fastq_pass]/fastq_pass/ \
--barcodes_samplesheet /[absolute path to barcode sample sheet]/sample_sheet_merge.csv
There are two types of sample sheets that can be used: 1) If the fastq files
are already concatenated/merged i.e., the fastq-files in Nanopore barcode
directories have been concataned already, the --input
can be used.
--input
expects a .csv
sample sheet with 3 columns (note the header
names). It looks like this (See also the examples
directory):
sample,fastq_1,fastq_2
SAMPLE_1,/absolute_path/gms_16S/assets/test_assets/medium_Mock_dil_1_2_BC1.fastq.gz,
SAMPLE_2,/absolute_path/gms_16S/assets/test_assets/medium_Mock_dil_1_2_BC3.fastq.gz,
2) If the fastq files are separated in their respective barcode folder i.e., you
have several fastq files for each sample and they are organized in barcode
directories in a fastq_pass dir.
a) If you do not want to create a sample sheet for the barcodes, then the
results will be named according to the barcode folders. flag
--merge_fastq_pass
b) If you want your own sample names on the results, then use
--merge_fastq_pass
in combination with --barcodes_samplesheet
. This
requires a barcode sample sheet which is tab separated. Se example file
sample_sheet_merge.csv
in examples
for a demonstration.
NXF_WORK = working directory. # If the work is spread out on different nodes,
# set this to a shared place.
# export NXF_WORK=/path/to/your/working/dir
APPTAINER_TMPDIR
NXF_SINGULARITY_CACHEDIR
APPTAINER_CACHEDIR
gms_16S was originally written by @fwa93.
This pipeline is not a formal nf-core pipeline but it partly 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. In addition, references of tools and data used in this pipeline are as follows:
Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 2839>
Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354.>
Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.
Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018>
da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-R>
Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; >
Kristen D. Curry et al., “Emu: Species-Level Microbial Community Profiling of Full-Length 16S RRNA Oxford Nanopore Sequencing Data,” Nature Methods, June 30, 2022, 1–9, https://doi.org/10.1038/s41592-022-015>
An extensive list of references for the tools used by the pipeline can be found
in the CITATIONS.md
file.