A large-scale evaluation of algorithms to calculate average nucleotide identity

2017 ◽  
Vol 110 (10) ◽  
pp. 1281-1286 ◽  
Author(s):  
Seok-Hwan Yoon ◽  
Sung-min Ha ◽  
Jeongmin Lim ◽  
Soonjae Kwon ◽  
Jongsik Chun
Keyword(s):  
Large Scale ◽  
Nucleotide Identity ◽  
Average Nucleotide Identity ◽  
Scale Evaluation

scholarly journals PaSiT: a novel approach based on short-oligonucleotide frequencies for efficient bacterial identification and typing

2020 ◽  
Vol 36 (8) ◽  
pp. 2337-2344 ◽  
Author(s):  
Gleb Goussarov ◽  
Ilse Cleenwerck ◽  
Mohamed Mysara ◽  
Natalie Leys ◽  
Pieter Monsieurs ◽  
...  
Keyword(s):  
Large Scale ◽  
Bacterial Species ◽  
Supplementary Information ◽  
Nucleotide Identity ◽  
Average Nucleotide Identity ◽  
Bacterial Genomes ◽  
Short Oligonucleotide ◽  
Novel Approach ◽  
Novel Method ◽  
Alignment Step

Abstract Motivation One of the most widespread methods used in taxonomy studies to distinguish between strains or taxa is the calculation of average nucleotide identity. It requires a computationally expensive alignment step and is therefore not suitable for large-scale comparisons. Short oligonucleotide-based methods do offer a faster alternative but at the expense of accuracy. Here, we aim to address this shortcoming by providing a software that implements a novel method based on short-oligonucleotide frequencies to compute inter-genomic distances. Results Our tetranucleotide and hexanucleotide implementations, which were optimized based on a taxonomically well-defined set of over 200 newly sequenced bacterial genomes, are as accurate as the short oligonucleotide-based method TETRA and average nucleotide identity, for identifying bacterial species and strains, respectively. Moreover, the lightweight nature of this method makes it applicable for large-scale analyses. Availability and implementation The method introduced here was implemented, together with other existing methods, in a dependency-free software written in C, GenDisCal, available as source code from https://github.com/LM-UGent/GenDisCal. The software supports multithreading and has been tested on Windows and Linux (CentOS). In addition, a Java-based graphical user interface that acts as a wrapper for the software is also available. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Sparsity-Based Audio Declipping Methods: Selected Overview, New Algorithms, and Large-Scale Evaluation

2021 ◽  
Vol 29 ◽  
pp. 1174-1187
Author(s):  
Clement Gaultier ◽  
Srdan Kitic ◽  
Remi Gribonval ◽  
Nancy Bertin
Keyword(s):  
Large Scale ◽  
Scale Evaluation ◽  
New Algorithms

Automated large scale evaluation of protein structure predictions

1999 ◽  
Vol 37 (S3) ◽  
pp. 7-14 ◽  
Author(s):  
Peter Lackner ◽  
Walter A. Koppensteiner ◽  
Francisco S. Domingues ◽  
Manfred J. Sippl
Keyword(s):  
Protein Structure ◽  
Large Scale ◽  
Scale Evaluation

scholarly journals Semi-Automated, Large-Scale Evaluation of Public Displays

2017 ◽  
Vol 34 (6) ◽  
pp. 491-505 ◽  
Author(s):  
Ville Mäkelä ◽  
Tomi Heimonen ◽  
Markku Turunen
Keyword(s):  
Large Scale ◽  
Scale Evaluation ◽  
Public Displays
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