title: Mycofier: a new machine learning-based classifier for fungal ITS sequences.
abstract: BACKGROUND
  The taxonomic and phylogenetic classification based on sequence analysis of the ITS1 genomic region has become a crucial component of fungal ecology and diversity studies. Nowadays, there is no accurate alignment-free classification tool for fungal ITS1 sequences for large environmental surveys. This study describes the development of a machine learning-based classifier for the taxonomical assignment of fungal ITS1 sequences at the genus level.
  
  
  RESULTS
  A fungal ITS1 sequence database was built using curated data. Training and test sets were generated from it. A Naïve Bayesian classifier was built using features from the primary sequence with an accuracy of 87 % in the classification at the genus level.
  
  
  CONCLUSIONS
  The final model was based on a Naïve Bayes algorithm using ITS1 sequences from 510 fungal genera. This classifier, denoted as Mycofier, provides similar classification accuracy compared to BLASTN, but the database used for the classification contains curated data and the tool, independent of alignment, is more efficient and contributes to the field, given the lack of an accurate classification tool for large data from fungal ITS1 sequences. The software and source code for Mycofier are freely available at https://github.com/ldelgado-serrano/mycofier.git .
authors: Bioinformatics & Computational Biology, Corporación CorpoGen, Bogotá, DC, Colombia.|Department of Biological Sciences, Universidad de Los Andes, Bogotá, DC, Colombia.
authors: Luisa
authors: L
authors: Delgado-Serrano
authors: Department of Biological Sciences, Universidad de Los Andes, Bogotá, DC, Colombia.
authors: Silvia
authors: S
authors: Restrepo
authors: Bioinformatics & Computational Biology, Corporación CorpoGen, Bogotá, DC, Colombia.
authors: Jose Ricardo
authors: JR
authors: Bustos
authors: Bioinformatics & Computational Biology, Corporación CorpoGen, Bogotá, DC, Colombia.
authors: Maria Mercedes
authors: MM
authors: Zambrano
authors: Bioinformatics & Computational Biology, Corporación CorpoGen, Bogotá, DC, Colombia. juan.anzola@corpogen.org.
authors: Juan Manuel
authors: JM
authors: Anzola
mesh_terms: D001483:Base Sequence; D001499:Bayes Theorem; D021903:DNA, Ribosomal Spacer / Q000235:genetics*; D030541:Databases, Genetic; D005658:Fungi / Q000235:genetics*; D000069550:Machine Learning; D008957:Models, Genetic; D012984:Software
chemical_list: D021903:DNA, Ribosomal Spacer
keywords: Fungal ITS1; Fungal diversity; Fungi; Naive Bayes classifier