A machine learning-based service for estimating quality of genomes using PATRIC

Parrello, Bruce; Butler, Rory; Chlenski, Philippe; Olson, Robert; Overbeek, Jamie C.; Pusch, Gordon D.; Vonstein, Veronika; Overbeek, Ross

doi:10.1186/s12859-019-3068-y

Title: A machine learning-based service for estimating quality of genomes using PATRIC

Journal Article · 03 October 2019 · BMC Bioinformatics

DOI: https://doi.org/10.1186/s12859-019-3068-y · OSTI ID:1579345

Parrello, Bruce ^[1]; Butler, Rory ^[2];

^[3]; Olson, Robert ^[2]; Overbeek, Jamie C. ^[4]; Pusch, Gordon D. ^[3]; Vonstein, Veronika ^[3]; Overbeek, Ross ^[1]

Fellowship for Interpretation of Genomes, Burr Ridge, IL (United States); Univ. of Chicago, Chicago, IL (United States)
Argonne National Lab. (ANL), Lemont, IL (United States)
Fellowship for Interpretation of Genomes, Burr Ridge, IL (United States)
Fellowship for Interpretation of Genomes, Burr Ridge, IL (United States); Argonne National Lab. (ANL), Lemont, IL (United States)

Recent advances in high-volume sequencing technology and mining of genomes from metagenomic samples call for rapid and reliable genome quality evaluation. The current release of the PATRIC database contains over 220,000 genomes, and current metagenomic technology supports assemblies of many draft-quality genomes from a single sample, most of which will be novel. We have added two quality assessment tools to the PATRIC annotation pipeline. EvalCon uses supervised machine learning to calculate an annotation consistency score. EvalG implements a variant of the CheckM algorithm to estimate contamination and completeness of an annotated genome.We report on the performance of these tools and the potential utility of the consistency score. Additionally, we provide contamination, completeness, and consistency measures for all genomes in PATRIC and in a recent set of metagenomic assemblies. EvalG and EvalCon facilitate the rapid quality control and exploration of PATRIC-annotated draft genomes.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC); National Institutes of Health (NIH) - National Institute of Allergy and Infectious Diseases (NIAID)

Grant/Contract Number:: AC02-06CH11357; HHSN272201400027C

OSTI ID:: 1579345

Journal Information:: BMC Bioinformatics, Vol. 20, Issue 1; ISSN 1471-2105

Publisher:: BioMed CentralCopyright Statement

Country of Publication:: United States

Language:: English

Citation Metrics:

Cited by: 19 works

Citation information provided by
Web of Science

References (20)

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Salinimonas marina sp. nov. Isolated from Jeju Island Marine Sediment Kim, Minji; Lee, Ki-Eun; Cha, In-Tae Current Microbiology, Vol. 78, Issue 8 https://doi.org/10.1007/s00284-021-02576-9	journal	June 2021
Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle Pasolli, Edoardo; Asnicar, Francesco; Manara, Serena Cell, Vol. 176, Issue 3 https://doi.org/10.1016/j.cell.2019.01.001	journal	January 2019
RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes Brettin, Thomas; Davis, James J.; Disz, Terry Scientific Reports, Vol. 5, Issue 1 https://doi.org/10.1038/srep08365	journal	February 2015
BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs Simão, Felipe A.; Waterhouse, Robert M.; Ioannidis, Panagiotis Bioinformatics, Vol. 31, Issue 19 https://doi.org/10.1093/bioinformatics/btv351	journal	June 2015
The Subsystems Approach to Genome Annotation and its Use in the Project to Annotate 1000 Genomes Overbeek, R. Nucleic Acids Research, Vol. 33, Issue 17 https://doi.org/10.1093/nar/gki866	journal	September 2005
PATRIC: The VBI PathoSystems Resource Integration Center Snyder, E. E.; Kampanya, N.; Lu, J. Nucleic Acids Research, Vol. 35, Issue Database https://doi.org/10.1093/nar/gkl858	journal	January 2007
The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST) Overbeek, Ross; Olson, Robert; Pusch, Gordon D. Nucleic Acids Research, Vol. 42, Issue D1 https://doi.org/10.1093/nar/gkt1226	journal	November 2013
Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center Wattam, Alice R.; Davis, James J.; Assaf, Rida Nucleic Acids Research, Vol. 45, Issue D1 https://doi.org/10.1093/nar/gkw1017	journal	November 2016
MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities Kang, Dongwan D.; Froula, Jeff; Egan, Rob PeerJ, Vol. 3 https://doi.org/10.7717/peerj.1165	journal	January 2015
Anvi’o: an advanced analysis and visualization platform for ‘omics data Eren, A. Murat; Esen, Özcan C.; Quince, Christopher PeerJ, Vol. 3 https://doi.org/10.7717/peerj.1319	journal	January 2015

Cited By (2)

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities Davis, James J.; Wattam, Alice R.; Aziz, Ramy K. Nucleic Acids Research https://doi.org/10.1093/nar/gkz943	journal	October 2019
Supervised extraction of near-complete genomes from metagenomic samples: A new service in PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe PLOS ONE, Vol. 16, Issue 4 https://doi.org/10.1371/journal.pone.0250092	journal	April 2021

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Related Subjects

59 BASIC BIOLOGICAL SCIENCES
CheckM
RAST
genome annotation
genome quality
machine learning
metagenomics
random forest
supervised learning

MOESM1 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937646 The current record is supplemented by this dataset	dataset	January 2019
MOESM1 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937646.v1 The current record is supplemented by this dataset	dataset	January 2019
MOESM2 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937652 The current record is supplemented by this dataset	dataset	January 2019
MOESM2 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937652.v1 The current record is supplemented by this dataset	dataset	January 2019
MOESM3 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937655 The current record is supplemented by this dataset	dataset	January 2019
MOESM3 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937655.v1 The current record is supplemented by this dataset	dataset	January 2019
MOESM4 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937661 The current record is supplemented by this dataset	dataset	January 2019
MOESM4 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937661.v1 The current record is supplemented by this dataset	dataset	January 2019
MOESM5 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937664 The current record is supplemented by this dataset	dataset	January 2019
MOESM5 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937664.v1 The current record is supplemented by this dataset	dataset	January 2019
MOESM6 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937670 The current record is supplemented by this dataset	dataset	January 2019
MOESM6 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937670.v1 The current record is supplemented by this dataset	dataset	January 2019
MOESM7 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937676 The current record is supplemented by this dataset	dataset	January 2019
MOESM7 of A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.9937676.v1 The current record is supplemented by this dataset	dataset	January 2019
A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.c.4687430 The current record is supplemented by this collection	collection	January 2019
A machine learning-based service for estimating quality of genomes using PATRIC Parrello, Bruce; Butler, Rory; Chlenski, Philippe https://doi.org/10.6084/m9.figshare.c.4687430.v1 The current record is supplemented by this collection	collection	January 2019