Reference Sequence Browser: An R application with a user-friendly GUI to rapidly query sequence databases.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 30 04 2024
accepted: 16 08 2024
medline: 1 11 2024
pubmed: 1 11 2024
entrez: 31 10 2024
Statut: epublish

Résumé

Land managers, researchers, and regulators increasingly utilize environmental DNA (eDNA) techniques to monitor species richness, presence, and absence. In order to properly develop a biological assay for eDNA metabarcoding or quantitative PCR, scientists must be able to find not only reference sequences (previously identified sequences in a genomics database) that match their target taxa but also reference sequences that match non-target taxa. Determining which taxa have publicly available sequences in a time-efficient and accurate manner currently requires computational skills to search, manipulate, and parse multiple unconnected DNA sequence databases. Our team iteratively designed a Graphic User Interface (GUI) Shiny application called the Reference Sequence Browser (RSB) that provides users efficient and intuitive access to multiple genetic databases regardless of computer programming expertise. The application returns the number of publicly accessible barcode markers per organism in the NCBI Nucleotide, BOLD, or CALeDNA CRUX Metabarcoding Reference Databases. Depending on the database, we offer various search filters such as min and max sequence length or country of origin. Users can then download the FASTA/GenBank files from the RSB web tool, view statistics about the data, and explore results to determine details about the availability or absence of reference sequences.

Identifiants

pubmed: 39480818
doi: 10.1371/journal.pone.0309707
pii: PONE-D-24-11148
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0309707

Informations de copyright

Copyright: © 2024 Ramesh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

We have no Competing Interests to report.

Auteurs

Sriram Ramesh (S)

Department of Computer Science and Engineering, University of California Santa Cruz, Santa Cruz, CA, United States of America.

Samuel Rapp (S)

Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, United States of America.

Jorge Tapias Gomez (J)

Department of Computing and Information Science, Cornell University, Ithaca, NY, United States of America.

Benjamin Levine (B)

Department Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, United States of America.

Daniel Tapias-Gomez (D)

Department of Cell and Molecular Biology, University of Texas Southwestern, Dallas, TX, United States of America.

Dickson Chung (D)

Department of Computer Science and Engineering, University of California Santa Cruz, Santa Cruz, CA, United States of America.

Zia Truong (Z)

Department Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, United States of America.

Articles similaires

Selecting optimal software code descriptors-The case of Java.

Yegor Bugayenko, Zamira Kholmatova, Artem Kruglov et al.
1.00
Software Algorithms Programming Languages
Humans Adult Male Female Video Games

Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

Yoan Martínez-López, Paulina Phoobane, Yanaima Jauriga et al.
1.00
Blood-Brain Barrier Machine Learning Humans Support Vector Machine Software
Cephalometry Humans Anatomic Landmarks Software Internet

Classifications MeSH