Wochenende — modular and flexible alignment-based shotgun metagenome analysis
Wochenende — modular and flexible alignment-based shotgun metagenome analysis
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England: BioMed Central Ltd
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English
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England: BioMed Central Ltd
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Shotgun metagenome analysis provides a robust and verifiable method for comprehensive microbiome analysis of fungal, viral, archaeal and bacterial taxonomy, particularly with regard to visualization of read mapping location, normalization options, growth dynamics and functional gene repertoires. Current read classification tools use non-standard output formats, or do not fully show information on mapping location. As reference datasets are not perfect, portrayal of mapping information is critical for judging results effectively.
Our alignment-based pipeline, Wochenende, incorporates flexible quality control, trimming, mapping, various filters and normalization. Results are completely transparent and filters can be adjusted by the user. We observe stringent filtering of mismatches and use of mapping quality sharply reduces the number of false positives. Further modules allow genomic visualization and the calculation of growth rates, as well as integration and subsequent plotting of pipeline results as heatmaps or heat trees. Our novel normalization approach additionally allows calculation of absolute abundance profiles by comparison with reads assigned to the human host genome.
Wochenende has the ability to find and filter alignments to all kingdoms of life using both short and long reads, and requires only good quality reference genomes. Wochenende automatically combines multiple available modules ranging from quality control and normalization to taxonomic visualization. Wochenende is available at https://github.com/MHH-RCUG/nf_wochenende ....
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Wochenende — modular and flexible alignment-based shotgun metagenome analysis
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TN_cdi_doaj_primary_oai_doaj_org_article_b2aa351c00e04f0fa3f87c0c3e21731c
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b2aa351c00e04f0fa3f87c0c3e21731c
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ISSN
1471-2164
E-ISSN
1471-2164
DOI
10.1186/s12864-022-08985-9