supraHex: An R/Bioconductor package for tabular omics data analysis using a supra-hexagonal map

Highlights • supraHex is an open-source R/Bioconductor package for tabular omics data analysis.• A supra-hexagonal map is designed to self-organise omics data.• The supraHex map analyses both genes and samples at the same time.• The supraHex map can be overlaid by additional data for multilayer omics data comparisons.• supraHex can tell inherent relations between replication timing, CpG and expression.

[1]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[2]  Sean R Eddy,et al.  What is dynamic programming? , 2004, Nature Biotechnology.

[3]  Jean YH Yang,et al.  Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.

[4]  Raymond K. Auerbach,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[5]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[6]  Lutgarde M. C. Buydens,et al.  Self- and Super-organizing Maps in R: The kohonen Package , 2007 .

[7]  Ying Jin,et al.  Transcriptome analysis of early organogenesis in human embryos. , 2010, Developmental cell.

[8]  D. Lockhart,et al.  Expression monitoring by hybridization to high-density oligonucleotide arrays , 1996, Nature Biotechnology.

[9]  Data production leads,et al.  An integrated encyclopedia of DNA elements in the human genome , 2012 .

[10]  T. Mikkelsen,et al.  Genome-wide maps of chromatin state in pluripotent and lineage-committed cells , 2007, Nature.

[12]  Esa Alhoniemi,et al.  Self-organizing map in Matlab: the SOM Toolbox , 1999 .

[13]  J. Mesirov,et al.  Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[14]  Bernadett Papp,et al.  Genome-wide dynamics of replication timing revealed by in vitro models of mouse embryogenesis. , 2010, Genome research.

[15]  John Quackenbush Microarray data normalization and transformation , 2002, Nature Genetics.

[16]  Juha Vesanto,et al.  Distance Matrix Based Clustering of the Self-Organizing Map , 2002, ICANN.

[17]  M. Cloutier,et al.  Genome-Wide Analysis Reveals Gene Expression and Metabolic Network Dynamics during Embryo Development in Arabidopsis1[W][OA] , 2011, Plant Physiology.

[18]  S Miyano,et al.  Open source clustering software. , 2004, Bioinformatics.

[19]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[20]  M. Gerstein,et al.  RNA-Seq: a revolutionary tool for transcriptomics , 2009, Nature Reviews Genetics.

[21]  Hanlee P. Ji,et al.  Next-generation DNA sequencing , 2008, Nature Biotechnology.

[22]  Satoru Miyano,et al.  Open source clustering software , 2004 .

[23]  Young-Seuk Park,et al.  Self-Organizing Map , 2008 .