scholarly journals Comprehensive Human Virus Screening Using High-Throughput Sequencing with a User-Friendly Representation of Bioinformatics Analysis: a Pilot Study

2014 ◽  
Vol 52 (9) ◽  
pp. 3351-3361 ◽  
Author(s):  
Tom J. Petty ◽  
Samuel Cordey ◽  
Ismael Padioleau ◽  
Mylène Docquier ◽  
Lara Turin ◽  
...  
2011 ◽  
Vol 56 (27) ◽  
pp. 2916-2921 ◽  
Author(s):  
AiYou Huang ◽  
GuangCe Wang ◽  
LinWen He ◽  
JianFeng Niu ◽  
BaoYu Zhang

2016 ◽  
Vol 173 (3) ◽  
pp. 413-420 ◽  
Author(s):  
Yann Ferret ◽  
Aurélie Caillault ◽  
Shéhérazade Sebda ◽  
Marc Duez ◽  
Nathalie Grardel ◽  
...  

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Carlos A. Ruiz-Perez ◽  
Roth E. Conrad ◽  
Konstantinos T. Konstantinidis

Abstract Background High-throughput sequencing has increased the number of available microbial genomes recovered from isolates, single cells, and metagenomes. Accordingly, fast and comprehensive functional gene annotation pipelines are needed to analyze and compare these genomes. Although several approaches exist for genome annotation, these are typically not designed for easy incorporation into analysis pipelines, do not combine results from different annotation databases or offer easy-to-use summaries of metabolic reconstructions, and typically require large amounts of computing power for high-throughput analysis not available to the average user. Results Here, we introduce MicrobeAnnotator, a fully automated, easy-to-use pipeline for the comprehensive functional annotation of microbial genomes that combines results from several reference protein databases and returns the matching annotations together with key metadata such as the interlinked identifiers of matching reference proteins from multiple databases [KEGG Orthology (KO), Enzyme Commission (E.C.), Gene Ontology (GO), Pfam, and InterPro]. Further, the functional annotations are summarized into Kyoto Encyclopedia of Genes and Genomes (KEGG) modules as part of a graphical output (heatmap) that allows the user to quickly detect differences among (multiple) query genomes and cluster the genomes based on their metabolic similarity. MicrobeAnnotator is implemented in Python 3 and is freely available under an open-source Artistic License 2.0 from https://github.com/cruizperez/MicrobeAnnotator. Conclusions We demonstrated the capabilities of MicrobeAnnotator by annotating 100 Escherichia coli and 78 environmental Candidate Phyla Radiation (CPR) bacterial genomes and comparing the results to those of other popular tools. We showed that the use of multiple annotation databases allows MicrobeAnnotator to recover more annotations per genome compared to faster tools that use reduced databases and is computationally efficient for use in personal computers. The output of MicrobeAnnotator can be easily incorporated into other analysis pipelines while the results of other annotation tools can be seemingly incorporated into MicrobeAnnotator to generate summary plots.


PLoS ONE ◽  
2012 ◽  
Vol 7 (11) ◽  
pp. e49811 ◽  
Author(s):  
Frank Guzman ◽  
Mauricio P. Almerão ◽  
Ana P. Körbes ◽  
Guilherme Loss-Morais ◽  
Rogerio Margis

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