title: GRACOMICS: software for graphical comparison of multiple results with omics data.
abstract: BACKGROUND
  Analysis of large-scale omics data has become more and more challenging due to high dimensionality. More complex analysis methods and tools are required to handle such data. While many methods already exist, those methods often produce different results. To help users obtain more appropriate results (i.e. candidate genes), we propose a tool, GRACOMICS that compares numerous analysis results visually in a more systematic way; this enables the users to easily interpret the results more comfortably.
  
  
  RESULTS
  GRACOMICS has the ability to visualize multiple analysis results interactively. We developed GRACOMICS to provide instantaneous results (plots and tables), corresponding to user-defined threshold values, since there are yet no other up-to-date omics data visualization tools that provide such features. In our analysis, we successfully employed two types of omics data: transcriptomic data (microarray and RNA-seq data) and genomic data (SNP chip and NGS data).
  
  
  CONCLUSIONS
  GRACOMICS is a graphical user interface (GUI)-based program written in Java for cross-platform computing environments, and can be applied to compare analysis results for any type of large-scale omics data. This tool can be useful for biologists to identify genes commonly found by intersected statistical methods, for further experimental validation.
authors.affiliation: Interdiciplinary of Bioinformatics Program, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Korea. nijorral@gmail.com.
authors.forename: Minseok
authors.initials: M
authors.lastname: Seo
authors.affiliation: Interdiciplinary of Bioinformatics Program, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Korea. joonyoon.jay@gmail.com.
authors.forename: Joon
authors.initials: J
authors.lastname: Yoon
authors.affiliation: Interdiciplinary of Bioinformatics Program, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Korea. tspark@stats.snu.ac.kr.|Department of Statistics, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, Korea. tspark@stats.snu.ac.kr.
authors.forename: Taesung
authors.initials: T
authors.lastname: Park
mesh_terms: D003196:Computer Graphics; D001330:Electronic Data Processing / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide; D017423:Sequence Analysis, RNA; D012984:Software