Motivation: Biclustering is widely used to identify co-expressed genes under subsets of all the conditions in a large-scale transcriptomic dataset. The program, QUBIC, is recognized as one of the most efficient and effective biclustering methods for biological data interpretation. However, its availability is limited to a C implementation and to a low-throughput web interface.
Results: An R implementation of QUBIC is presented here with two unique features: (i) a 82% average improved efficiency by refactoring and optimizing the source C code of QUBIC; and (ii) a set of comprehensive functions to facilitate biclustering-based biological studies, including the qualitative representation (discretization) of expression data, query-based biclustering, bicluster expanding, biclusters comparison, heatmap visualization of any identified biclusters and co-expression networks elucidation.
Availability and implementation: The package is implemented in R (as of version 3.3) and is available from Bioconductor at the URL: http://bioconductor.org/packages/QUBIC, where installation and usage instructions can be found.
Contact: qin.ma@sdstate.edu
Supplimentary information: Supplementary data are available at Bioinformatics online.