Chiara Matteo, Zambelli Federico, Tangaro Marco Antonio, Mandreoli Pietro, Horner David S, Pesole Graziano
Department of Biosciences, University of Milan, 20133 Milan, Italy.
Institute of Biomembranes, Bioenergetics and Molecular Biotechnology, National Research Council, 70126 Bari, Italy.
Bioinformatics. 2021 Apr 1;36(22-23):5522-5523. doi: 10.1093/bioinformatics/btaa1047.
While over 200 000 genomic sequences are currently available through dedicated repositories, ad hoc methods for the functional annotation of SARS-CoV-2 genomes do not harness all currently available resources for the annotation of functionally relevant genomic sites. Here, we present CorGAT, a novel tool for the functional annotation of SARS-CoV-2 genomic variants. By comparisons with other state of the art methods we demonstrate that, by providing a more comprehensive and rich annotation, our method can facilitate the identification of evolutionary patterns in the genome of SARS-CoV-2.
Galaxy.
http://corgat.cloud.ba.infn.it/galaxy; software: https://github.com/matteo14c/CorGAT/tree/Revision_V1; docker: https://hub.docker.com/r/laniakeacloud/galaxy_corgat.
Supplementary data are available at Bioinformatics online.
虽然目前通过专门的数据库可获得超过20万条基因组序列,但用于严重急性呼吸综合征冠状病毒2(SARS-CoV-2)基因组功能注释的临时方法并未利用所有当前可用资源来注释功能相关的基因组位点。在此,我们展示了CorGAT,这是一种用于SARS-CoV-2基因组变异功能注释的新型工具。通过与其他现有技术方法进行比较,我们证明,通过提供更全面和丰富的注释,我们的方法可以促进SARS-CoV-2基因组进化模式的识别。
Galaxy。
补充数据可在《生物信息学》在线获取。