Vectoral and alignment-free approaches to biological sequence representation have been explored in bioinformatics to efficiently handle big data. Even so, most current methods involve sequence comparisons via alignment-based heuristics and fail when applied to the analysis of large data sets. Here, we present "Spaced Words Projection (SWeeP)", a method for representing biological sequences using relatively small vectors while preserving intersequence comparability. SWeeP uses spaced-words by scanning the sequences and generating indices to create a higher-dimensional vector that is later projected onto a smaller randomly oriented orthonormal base. We constructed phylogenetic trees for all organisms with mitochondrial and bacterial protein data in the NCBI database. SWeeP quickly built complete and accurate trees for these organisms with low computational cost. We compared SWeeP to other alignment-free methods and Sweep was 10 to 100 times quicker than the other techniques. A tool to build SWeep vectors is available at https://sourceforge.net/projects/spacedwordsprojection/.

The RepeatsDB database (URL: https://repeatsdb.org/) provides annotations and classification for protein tandem repeat structures from the Protein Data Bank (PDB). Protein tandem repeats are ubiquitous in all branches of the tree of life. The accumulation of solved repeat structures provides new possibilities for classification and detection, but also increasing the need for annotation. Here we present RepeatsDB 3.0, which addresses these challenges and presents an extended classification scheme. The major conceptual change compared to the previous version is the hierarchical classification combining top levels based solely on structural similarity (Class > Topology > Fold) with two new levels (Clan > Family) requiring sequence similarity and describing repeat motifs in collaboration with Pfam. Data growth has been addressed with improved mechanisms for browsing the classification hierarchy. A new UniProt-centric view unifies the increasingly frequent annotation of structures from identical or similar sequences. This update of RepeatsDB aligns with our commitment to develop a resource that extracts, organizes and distributes specialized information on tandem repeat protein structures.

The rSWeeP package is an R implementation of the SWeeP model, designed to handle Big Data. rSweeP meets to the growing demand for efficient methods of heuristic representation in the field of Bioinformatics, on platforms accessible to the entire scientific community. We explored the implementation of rSWeeP using a dataset containing 31,386 viral proteomes, performing phylogenetic and principal component analysis. As a case study we analyze the viral strains closest to the SARS-CoV, responsible for the current pandemic of COVID-19, confirming that rSWeeP can accurately classify organisms taxonomically. rSWeeP package is freely available at https://bioconductor.org/packages/release/bioc/html/rSWeeP.html.

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