@article{Alkhnbashi-CRISPRloci,
author = {Alkhnbashi, Omer S. and Mitrofanov, Alexander and Bonidia, Robson and Raden, Martin and Van Dinh, Tran and Eggenhofer, Florian and Shah, Shiraz A. and Öztürk, Ekrem  and Padilha, Victor A. and Sanches, Danilo S.  and de Carvalho, Andre C.P.L.F.  and Backofen, Rolf},
title = {CRISPRloci: comprehensive and accurate annotation of CRISPR-Cas system},
journal = {NAR},
year = {2021},
doi = {10.1093/nar/gkab56},
volume = {},
user = {mmann},
pages = {},
number = {},
issn = {0305-1048},
abstract = {CRISPR-Cas systems are adaptive immune systemsin prokaryotes, providing resistance against invading viruses and plasmids. The identification of CRISPR loci is currently a non-standardized, ambiguous process, requiring  the  manual  combination  of  multiple tools, where existing tools detect only parts of the CRISPR-systems, and lack quality control, annotation  and  assessment  capabilities  of  the  detected CRISPR  loci.  OurCRISPRloci server  provides  the first resource for the prediction and assessment of all possible CRISPR loci. The server integrates a series  of  advanced  Machine  Learning  tools  within  a seamless web interface featuring: (i) prediction of all CRISPR arrays in the correct orientation; (ii) definition of CRISPR leaders for each locus; and (iii) annotation of cas genes and their unambiguous classification. As a result, CRISPRloci is able to accurately determine  the  CRISPR  array  and  associated  information, such as: the Cas subtypes; cassette boundaries;  accuracy  of  the  repeat  structure,  orientation and  leader  sequence;  virus-host  interactions;  self-targeting; as well as the annotation of cas genes, all of which have been missing from existing tools. This annotation  is  presented  in  an  interactive  interface, making it easy for scientists to gain an overview of the CRISPR system in their organism of interest. Predictions are also rendered in GFF format, enabling in-depth  genome  browser  inspection.  In  summary, CRISPRloci constitutes a full suite for CRISPR-Cas system characterization that offers annotation quality previously available only after manual inspection.}
}