runibic: a Bioconductor package for parallel row-based biclustering of gene expression data.

Motivation: Biclustering is an unsupervised technique of simultaneous clustering of rows and columns of input matrix. With multiple biclustering algorithms proposed, UniBic remains one of the most accurate methods developed so far.

Results: In this paper we introduce a Bioconductor package called runibic with parallel implementation of UniBic. For the convenience the algorithm was reimplemented, parallelized, and wrapped within an R package called runibic. The package includes: (1) a couple of times faster parallel version of the original sequential algorithm, (2) much more efficient memory management, (3) modularity which allows to build new methods on top of the provided one, and (4) integration with the modern Bioconductor packages such as SummarizedExperiment, ExpressionSet and biclust.

Availability: The package is implemented inR(3.4) and is available from Bioconductor (3.6) at the following URL https://bioconductor.org/packages/runibic with installation instructions and tutorial.

Supplementary information: Supplementary informations are available in vignette of the package.