Alignment-free sequence analyses have been applied to problems ranging from whole-genome phylogeny to the classification of protein families, identification of horizontally transferred genes, and detection of recombined sequences. The strength of these methods makes them particularly useful for next-generation sequencing data processing and analysis. However, many researchers are unclear about how these methods work, how they compare to alignment-based methods, and what their potential is for use for their research. We address these questions and provide a guide to the currently available alignment-free sequence analysis tools.

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.

Culture-independent approaches have recently shed light on the genomic diversity of viruses of prokaryotes. One fundamental question when trying to understand their ecological roles is: which host do they infect? To tackle this issue we developed a machine-learning approach named Random Forest Assignment of Hosts (RaFAH), that uses scores to 43,644 protein clusters to assign hosts to complete or fragmented genomes of viruses of Archaea and Bacteria. RaFAH displayed performance comparable with that of other methods for virus-host prediction in three different benchmarks encompassing viruses from RefSeq, single amplified genomes, and metagenomes. RaFAH was applied to assembled metagenomic datasets of uncultured viruses from eight different biomes of medical, biotechnological, and environmental relevance. Our analyses led to the identification of 537 sequences of archaeal viruses representing unknown lineages, whose genomes encode novel auxiliary metabolic genes, shedding light on how these viruses interfere with the host molecular machinery. RaFAH is available at https://sourceforge.net/projects/rafah/.

MicroRNAs are the key post-transcriptional regulators of gene expression in development and stress responses. Thus, precisely quantifying the level of each particular microRNA is of utmost importance when studying the biology of any organism. The mirEX 2.0 web portal ( http://www.combio.pl/mirex ) provides a comprehensive platform for the exploration of microRNA expression data based on quantitative Real Time PCR and NGS sequencing experiments, covering various developmental stages, from wild-type to mutant plants. The portal includes mature and pri-miRNA expression levels detected in three plant species (Arabidopsis thaliana, Hordeum vulgare and Pellia endiviifolia), and in A. thaliana miRNA biogenesis pathway mutants. In total, the database contains information about the expression of 461 miRNAs representing 268 families. The data can be explored through the use of advanced web tools, including (i) a graphical query builder system allowing a combination of any given species, developmental stages and tissues, (ii) a modular presentation of the results in the form of thematic windows, and (iii) a number of user-friendly utilities such as a community-building discussion system and extensive tutorial documentation (e.g., tooltips, exemplary videos and presentations). All data contained within the mirEX 2.0 database can be downloaded for use in further applications in a context-based way from the result windows or from a dedicated web page. The mirEX 2.0 portal provides the plant research community with easily accessible data and powerful tools for application in multi-conditioned analyses of miRNA expression from important plant species in different biological and developmental backgrounds.

Viromics produces millions of viral genomes and fragments annually, overwhelming traditional sequence comparison methods. Here we introduce Vclust, an approach that determines average nucleotide identity by Lempel–Ziv parsing and clusters viral genomes with thresholds endorsed by authoritative viral genomics and taxonomy consortia. Vclust demonstrates superior accuracy and efficiency compared to existing tools, clustering millions of genomes in a few hours on a mid-range workstation.

Phage–Host Interaction Search Tool (PHIST) predicts prokaryotic hosts of viruses based on exact matches between viral and host genomes. It improves host prediction accuracy at species level over current alignment-based tools (on average by 3 percentage points) as well as alignment-free and CRISPR-based tools (by 14–20 percentage points). PHIST is also two orders of magnitude faster than alignment-based tools making it suitable for metagenomics studies. GNU-licensed C++ code wrapped in Python API available at: https://github.com/refresh-bio/phist. Supplementary data are available at Bioinformatics online.