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/2019/04/16/611137.short
4100  - http://biorxiv.org/content/early/2019/04/16/611137.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 AF methods 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 AF tools relevant to their data types and analytical goals. It also allows method developers to assess their own algorithms and compare them with the current state-of-the art tools, accelerating the development of new, more accurate AF solutions.