PT  - JOURNAL ARTICLE
AU  - Andrzej Zielezinski
AU  - Hani Z. Girgis
AU  - Guillaume Bernard
AU  - Chris-Andre Leimeister
AU  - Kujin Tang
AU  - Thomas Dencker
AU  - Anna K. Lau
AU  - Sophie Röhling
AU  - JaeJin Choi
AU  - Michael S. Waterman
AU  - Matteo Comin
AU  - Sung-Hou Kim
AU  - Susana Vinga
AU  - Jonas S. Almeida
AU  - Cheong Xin Chan
AU  - Benjamin T. James
AU  - Fengzhu Sun
AU  - Burkhard Morgenstern
AU  - Wojciech M. Karlowski
TI  - Benchmarking of alignment-free sequence comparison methods
AID  - 10.1101/611137
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 611137
4099  - http://biorxiv.org/content/early/2019/05/15/611137.short
4100  - http://biorxiv.org/content/early/2019/05/15/611137.full
AB  - Alignment-free (AF) sequence comparison is attracting persistent interest driven by data-intensive applications. Hence, many AF procedures have been proposed in recent years, but a lack of a clearly defined benchmarking consensus hampers their performance assessment. Here, we present a community resource (http://afproject.org) to establish standards for comparing alignment-free approaches across different areas of sequence-based research. We characterize 74 AF methods available in 24 software tools for five research applications, namely, protein sequence classification, gene tree inference, regulatory element detection, genome-based phylogenetic inference and reconstruction of species trees under horizontal gene transfer and recombination events. The interactive web service allows researchers to explore the performance of alignment-free tools relevant to their data types and analytical goals. It also allows method developers to assess their own algorithms and compare them with current state-of-the-art tools, accelerating the development of new, more accurate AF solutions.