title: Glimma: interactive graphics for gene expression analysis.
abstract: BACKGROUND
  graphics for RNA-sequencing and microarray gene expression analyses may contain upwards of tens of thousands of points. Details about certain genes or samples of interest are easily obscured in such dense summary displays. Incorporating interactivity into summary plots would enable additional information to be displayed on demand and facilitate intuitive data exploration.
  
  
  RESULTS
  The open-source Glimma package creates interactive graphics for exploring gene expression analysis with a few simple R commands. It extends popular plots found in the limma package, such as multi-dimensional scaling plots and mean-difference plots, to allow individual data points to be queried and additional annotation information to be displayed upon hovering or selecting particular points. It also offers links between plots so that more information can be revealed on demand. Glimma is widely applicable, supporting data analyses from a number of well-established Bioconductor workflows ( limma , edgeR and DESeq2 ) and uses D3/JavaScript to produce HTML pages with interactive displays that enable more effective data exploration by end-users. Results from Glimma can be easily shared between bioinformaticians and biologists, enhancing reporting capabilities while maintaining reproducibility.
  
  
  METHODS
  The Glimma R package is available from http://bioconductor.org/packages/Glimma/ .
  
  
  BACKGROUND
  su.s@wehi.edu.au , law@wehi.edu.au or mritchie@wehi.edu.au.
authors.affiliation: Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia.
authors.forename: Shian
authors.initials: S
authors.lastname: Su
authors.affiliation: Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia.|Department of Medical Biology, The University of Melbourne, Parkville 3010, Australia.
authors.forename: Charity W
authors.initials: CW
authors.lastname: Law
authors.affiliation: Department of Medical Biology, The University of Melbourne, Parkville 3010, Australia.|ACRF Stem Cells and Cancer Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia.
authors.forename: Casey
authors.initials: C
authors.lastname: Ah-Cann
authors.affiliation: Department of Medical Biology, The University of Melbourne, Parkville 3010, Australia.|ACRF Stem Cells and Cancer Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia.
authors.forename: Marie-Liesse
authors.initials: ML
authors.lastname: Asselin-Labat
authors.affiliation: Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia.|Department of Medical Biology, The University of Melbourne, Parkville 3010, Australia.
authors.forename: Marnie E
authors.initials: ME
authors.lastname: Blewitt
authors.affiliation: Molecular Medicine Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3052, Australia.|Department of Medical Biology, The University of Melbourne, Parkville 3010, Australia.|School of Mathematics and Statistics, The University of Melbourne, Parkville 3010, Australia.
authors.forename: Matthew E
authors.initials: ME
authors.lastname: Ritchie
mesh_terms: D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods*; D051379:Mice; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software