GitHub - athril/runibic: UniBic Biclustering algorithm for R (original) (raw)
runibic: UniBic biclustering algorithm for R
This package contains implementation of UniBic biclustering algorithm for gene expression data [Wang2016] The algorithm tries to locate trend-preserving biclusters within complex and noisy data.
Functions
This package provides the following main functions:
BCUnibic
/runibic
- parallel UniBic for continuous dataBCUnibicD
- parallel UniBic for discrete data
The package provides some additional functions:
pairwiseLCS
- calculates Longest Common Subsequence (LCS) between two vectorscalculateLCS
- calculates LCSes between all pairs of the input datasetbacktrackLCS
- recovers LCS from the dynamic programming matrixcluster
- main part of UniBic algorithm (biclusters seeding and expanding)unisort
- returns matrix of indexes based on the increasing order in each rowdiscretize
- performs discretization using Fibonacci heap (sorting method used originally in UniBic) or standard sorting
Installation
The package may be installed as follows:
install.packages("devtools") devtools::install_github("athril/runibic")
Example
Gene expression dataset
This example presents how to use runibic package on gene expression dataset:
library(runibic) library(biclust) data(BicatYeast) res <- biclust(method=BCUnibic(),BicatYeast) drawHeatmap(BicatYeast, res, 1) parallelCoordinates(BicatYeast,res,1)
Summarized experiment
This example presents how to use runibic package on SummarizedExperiment:
library(runibic) library(biclust) library(SummarizedExperiment) data(airway, package="airway") se <- airway[1:20,] res<- runibic(se) parallelCoordinates(assays(se)[[1]], res[[1]], 2)
Tutorial
Please check runibic tutorial
Citation
For the original sequential version of the UniBic please use the following citation:
Zhenjia Wang, Guojun Li, Robert W. Robinson, Xiuzhen Huang_UniBic: Sequential row-based biclustering algorithm for analysis of gene expression data_Scientific Reports 6, 2016; 23466, doi: https://doi:10.1038/srep23466
If you use in your work this package with parallel version of UniBic please use the following citation:
Patryk Orzechowski, Artur Pańszczyk, Xiuzhen Huang Jason H. Moore:_runibic: a Bioconductor package for parallel row-based biclustering of gene expression data_bioRxiv, 2017; 210682, doi: https://doi.org/10.1101/210682
BibTex entry:
@article{orzechowski2018runibic,
author = {Orzechowski, Patryk and Pańszczyk, Artur and Huang, Xiuzhen and Moore, Jason H},
title = {runibic: a Bioconductor package for parallel row-based biclustering of gene expression data},
journal = {Bioinformatics},
volume = {},
number = {},
pages = {bty512},
year = {2018},
doi = {10.1093/bioinformatics/bty512},
URL = {http://dx.doi.org/10.1093/bioinformatics/bty512},
eprint = {/oup/backfile/content_public/journal/bioinformatics/pap/10.1093_bioinformatics_bty512/4/bty512.pdf}
}
References
- [Wang2016] Wang, Zhenjia, et al. "UniBic: Sequential row-based biclustering algorithm for analysis of gene expression data." Scientific reports 6 (2016): 23466.