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QUBIC: a bioconductor package for qualitative biclustering analysis of gene co-expression data

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Abstract 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. Supplementary information Supplementary data are available at Bioinformatics online.
Title: QUBIC: a bioconductor package for qualitative biclustering analysis of gene co-expression data
Description:
Abstract 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.
Supplementary information Supplementary data are available at Bioinformatics online.

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