@InProceedings{ mckinney-proc-scipy-2010,
  author    = { Wes McKinney },
  title     = { Data Structures for Statistical Computing in Python },
  booktitle = { Proceedings of the 9th Python in Science Conference },
  pages     = { 51 -- 56 },
  year      = { 2010 },
  editor    = { St{\'e}fan van der Walt and Jarrod Millman }
}

@article{wood2019,
	title = {Improved metagenomic analysis with {Kraken} 2},
	volume = {20},
	issn = {1474-760X},
	url = {https://doi.org/10.1186/s13059-019-1891-0},
	doi = {10.1186/s13059-019-1891-0},
	abstract = {Although Kraken’s k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85\%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed fivefold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.},
	number = {1},
	urldate = {2023-01-17},
	journal = {Genome Biology},
	author = {Wood, Derrick E. and Lu, Jennifer and Langmead, Ben},
	month = {nov},
	year = {2019},
	keywords = {Alignment-free methods, Metagenomics, Metagenomics classification, Microbiome, Minimizers, Probabilistic data structures},
	pages = {257},
}

@article{lu2017,
  title = {Bracken: Estimating Species Abundance in Metagenomics Data},
  shorttitle = {Bracken},
  author = {Lu, Jennifer and Breitwieser, Florian P. and Thielen, Peter and Salzberg, Steven L.},
  year = {2017},
  month = jan,
  journal = {PeerJ Computer Science},
  volume = {3},
  pages = {e104},
  publisher = {{PeerJ Inc.}},
  issn = {2376-5992},
  doi = {10.7717/peerj-cs.104},
}

@article{kang2019,
  title = {{{MetaBAT}} 2: {{An}} Adaptive Binning Algorithm for Robust and Efficient Genome Reconstruction from Metagenome Assemblies},
  author = {Kang, Dongwan D. and Li, Feng and Kirton, Edward and Thomas, Ashleigh and Egan, Rob and An, Hong and Wang, Zhong},
  year = {2019},
  journal = {PeerJ},
  volume = {2019},
  number = {7},
  publisher = {{PeerJ Inc.}},
  issn = {21678359},
  doi = {10.7717/peerj.7359},
  keywords = {Clustering,Metagenome binning,Metagenomics}
}

@article{menzel2016,
  title = {Fast and Sensitive Taxonomic Classification for Metagenomics with {{Kaiju}}},
  author = {Menzel, Peter and Ng, Kim Lee and Krogh, Anders},
  year = {2016},
  month = apr,
  journal = {Nature Communications},
  volume = {7},
  number = {1},
  pages = {11257},
  publisher = {{Nature Publishing Group}},
  issn = {2041-1723},
  doi = {10.1038/ncomms11257},
  keywords = {Classification and taxonomy,Metagenomics}
}

@article{manni_busco_2021,
	title = {{BUSCO} {Update}: {Novel} and {Streamlined} {Workflows} along with {Broader} and {Deeper} {Phylogenetic} {Coverage} for {Scoring} of {Eukaryotic}, {Prokaryotic}, and {Viral} {Genomes}},
	volume = {38},
	issn = {1537-1719},
	shorttitle = {{BUSCO} {Update}},
	url = {https://academic.oup.com/mbe/article/38/10/4647/6329644},
	doi = {10.1093/molbev/msab199},
	abstract = {Methods for evaluating the quality of genomic and metagenomic data are essential to aid genome assembly procedures and to correctly interpret the results of subsequent analyses. BUSCO estimates the completeness and redundancy of processed genomic data based on universal single-copy orthologs. Here, we present new functionalities and major improvements of the BUSCO software, as well as the renewal and expansion of the underlying data sets in sync with the OrthoDB v10 release. Among the major novelties, BUSCO now enables phylogenetic placement of the input sequence to automatically select the most appropriate BUSCO data set for the assessment, allowing the analysis of metagenomeassembled genomes of unknown origin. A newly introduced genome workﬂow increases the efﬁciency and runtimes especially on large eukaryotic genomes. BUSCO is the only tool capable of assessing both eukaryotic and prokaryotic species, and can be applied to various data types, from genome assemblies and metagenomic bins, to transcriptomes and gene sets.},
	language = {en},
	number = {10},
	urldate = {2023-08-09},
	journal = {Molecular Biology and Evolution},
	author = {Manni, Mosè and Berkeley, Matthew R and Seppey, Mathieu and Simão, Felipe A and Zdobnov, Evgeny M},
	editor = {Kelley, Joanna},
	month = sep,
	year = {2021},
	pages = {4647--4654},
}

@article{hyatt_prodigal_2010,
	title = {Prodigal: prokaryotic gene recognition and translation initiation site identification},
	volume = {11},
	issn = {1471-2105},
	shorttitle = {Prodigal},
	url = {https://doi.org/10.1186/1471-2105-11-119},
	doi = {10.1186/1471-2105-11-119},
	abstract = {The quality of automated gene prediction in microbial organisms has improved steadily over the past decade, but there is still room for improvement. Increasing the number of correct identifications, both of genes and of the translation initiation sites for each gene, and reducing the overall number of false positives, are all desirable goals.},
	number = {1},
	urldate = {2023-10-23},
	journal = {BMC Bioinformatics},
	author = {Hyatt, Doug and Chen, Gwo-Liang and LoCascio, Philip F. and Land, Miriam L. and Larimer, Frank W. and Hauser, Loren J.},
	month = mar,
	year = {2010},
	keywords = {Bias Score, Codon Position, Halobacterium Salinarum, Ribosomal Binding Site, Translation Initiation Site},
	pages = {119},
}

