references.bib

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@article{assembling_improve,
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@article{motus,
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@misc{amplicon_and_metagen,
	author = {Lee, Mike},
	title = {{A}mplicon and metagenomics overview --- astrobiomike.github.io},
	howpublished = {\url{https://astrobiomike.github.io/misc/amplicon_and_metagen}},
	year = {},
	note = {[Accessed 18-12-2024]},
}

@misc{whatisamplicon,
	author = {},
	title = { 	{A}mplicon {S}equencing  --- eurofinsgenomics.eu},
	howpublished = {\url{https://eurofinsgenomics.eu/en/eurofins-genomics/material-and-methods/amplicon-sequencing/}},
	year = {},
	note = {[Accessed 18-12-2024]},
}

@article{rescript,
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@article{silva1,
    author = {Pruesse, Elmar and Quast, Christian and Knittel, Katrin and Fuchs, Bernhard M. and Ludwig, Wolfgang and Peplies, Jörg and Glöckner, Frank Oliver},
    title = {SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB},
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    number = {21},
    pages = {7188-7196},
    year = {2007},
    month = {10},
    abstract = { Sequencing ribosomal RNA (rRNA) genes is currently the method of choice for phylogenetic reconstruction, nucleic acid based detection and quantification of microbial diversity. The ARB software suite with its corresponding rRNA datasets has been accepted by researchers worldwide as a standard tool for large scale rRNA analysis. However, the rapid increase of publicly available rRNA sequence data has recently hampered the maintenance of comprehensive and curated rRNA knowledge databases. A new system, SILVA (from Latin silva , forest), was implemented to provide a central comprehensive web resource for up to date, quality controlled databases of aligned rRNA sequences from the Bacteria, Archaea and Eukarya domains. All sequences are checked for anomalies, carry a rich set of sequence associated contextual information, have multiple taxonomic classifications, and the latest validly described nomenclature. Furthermore, two precompiled sequence datasets compatible with ARB are offered for download on the SILVA website: (i) the reference (Ref) datasets, comprising only high quality, nearly full length sequences suitable for in-depth phylogenetic analysis and probe design and (ii) the comprehensive Parc datasets with all publicly available rRNA sequences longer than 300 nucleotides suitable for biodiversity analyses. The latest publicly available database release 91 (August 2007) hosts 547 521 sequences split into 461 823 small subunit and 85 689 large subunit rRNAs. },
    issn = {0305-1048},
    doi = {10.1093/nar/gkm864},
    url = {https://doi.org/10.1093/nar/gkm864},
    eprint = {https://academic.oup.com/nar/article-pdf/35/21/7188/7041501/gkm864.pdf},
}

@article{silva2,
    author = {Quast, Christian and Pruesse, Elmar and Yilmaz, Pelin and Gerken, Jan and Schweer, Timmy and Yarza, Pablo and Peplies, Jörg and Glöckner, Frank Oliver},
    title = {The SILVA ribosomal RNA gene database project: improved data processing and web-based tools},
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    number = {D1},
    pages = {D590-D596},
    year = {2012},
    month = {11},
    abstract = {SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.},
    issn = {0305-1048},
    doi = {10.1093/nar/gks1219},
    url = {https://doi.org/10.1093/nar/gks1219},
    eprint = {https://academic.oup.com/nar/article-pdf/41/D1/D590/3690367/gks1219.pdf},
}
@article{zackular,
  title={The human gut microbiome as a screening tool for colorectal cancer},
  author={Zackular, Joseph P and Rogers, Mary AM and Ruffin IV, Mack T and Schloss, Patrick D},
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  number={11},
  pages={1112--1121},
  year={2014},
  publisher={AACR}
}
@article{dada2,
  title={DADA2: High-resolution sample inference from Illumina amplicon data},
  author={Callahan, Benjamin J and McMurdie, Paul J and Rosen, Michael J and Han, Andrew W and Johnson, Amy Jo A and Holmes, Susan P},
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  number={7},
  pages={581--583},
  year={2016},
  publisher={Nature Publishing Group US New York}
}