MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps

BackgroundHeatmaps are an indispensible visualization tool for examining large-scale snapshots of genomic activity across various types of next-generation sequencing datasets. However, traditional heatmap software do not typically offer multi-scale insight across multiple layers of genomic analysis (e.g., differential expression analysis, principal component analysis, gene ontology analysis, and network analysis) or multiple types of next-generation sequencing datasets (e.g., ChIP-seq and RNA-seq). As such, it is natural to want to interact with a heatmap’s contents using an extensive set of integrated analysis tools applicable to a broad array of genomic data types.ResultsWe propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network analysis.ConclusionsMicroScope is hosted online as an R Shiny web application based on the D3 JavaScript library: http://microscopebioinformatics.org/. The methods are implemented in R, and are available as part of the MicroScope project at: https://github.com/Bohdan-Khomtchouk/Microscope.

[1]  David S. Wishart,et al.  Heatmapper: web-enabled heat mapping for all , 2016, Nucleic Acids Res..

[2]  Jie Zhang,et al.  Practical Guidelines for the Comprehensive Analysis of ChIP-seq Data , 2013, PLoS Comput. Biol..

[3]  Hanspeter Pfister,et al.  Characterizing Cancer Subtypes Using Dual Analysis in Caleydo StratomeX , 2014, IEEE Computer Graphics and Applications.

[4]  Daniel Svozil,et al.  InCHlib – interactive cluster heatmap for web applications , 2014, Journal of Cheminformatics.

[5]  Wolfgang Huber,et al.  RNA-Seq workflow: gene-level exploratory analysis and differential expression , 2015, F1000Research.

[6]  Bernhard Wünsch,et al.  Development of cannabinoid receptor (CB 2 R) ligands for application in PET studies - where to attach the radiolabel? , 2014, Journal of Cheminformatics.

[7]  Tal Galili,et al.  Interactive Heat Maps Using 'htmlwidgets' and 'D3.js' , 2015 .

[8]  Alain Calvet,et al.  Molecular Property eXplorer: A Novel Approach to Visualizing SAR Using Tree-Maps and Heatmaps , 2005, J. Chem. Inf. Model..

[9]  Peter J. van der Spek,et al.  HeatMapper: powerful combined visualization of gene expression profile correlations, genotypes, phenotypes and sample characteristics , 2006, BMC Bioinformatics.

[10]  Chun-Houh Chen,et al.  GAP: A graphical environment for matrix visualization and cluster analysis , 2010, Comput. Stat. Data Anal..

[11]  Nuria Lopez-Bigas,et al.  Gitools: Analysis and Visualisation of Genomic Data Using Interactive Heat-Maps , 2011, PloS one.

[12]  José Luís Oliveira,et al.  TrigNER: automatically optimized biomedical event trigger recognition on scientific documents , 2014, Source Code for Biology and Medicine.

[13]  Derek J. Van Booven,et al.  HeatmapGenerator: high performance RNAseq and microarray visualization software suite to examine differential gene expression levels using an R and C++ hybrid computational pipeline , 2014, Source Code for Biology and Medicine.

[14]  Daniel J. Gaffney,et al.  A survey of best practices for RNA-seq data analysis , 2016, Genome Biology.

[15]  Matthew D. Young,et al.  Gene ontology analysis for RNA-seq: accounting for selection bias , 2010, Genome Biology.

[16]  C. Tyler-Smith,et al.  Ancient DNA and the rewriting of human history: be sparing with Occam’s razor , 2016, Genome Biology.

[17]  Mark D. Robinson,et al.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..

[18]  Charlotte Soneson,et al.  A comparison of methods for differential expression analysis of RNA-seq data , 2013, BMC Bioinformatics.

[19]  Christopher Gandrud,et al.  D3 JavaScript Network Graphs from R , 2015 .

[20]  A I Saeed,et al.  TM4: a free, open-source system for microarray data management and analysis. , 2003, BioTechniques.

[21]  Jason Chuang,et al.  RNA sequencing reveals a diverse and dynamic repertoire of the Xenopus tropicalis transcriptome over development , 2012, Genome research.

[22]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[23]  Jaak Vilo,et al.  ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap , 2015, Nucleic Acids Res..

[24]  Gilles Caraux,et al.  PermutMatrix: a graphical environment to arrange gene expression profiles in optimal linear order , 2005, Bioinform..

[25]  J. Mesirov,et al.  GenePattern 2.0 , 2006, Nature Genetics.

[26]  Tao Liu,et al.  Computational methodology for ChIP-seq analysis , 2013, Quantitative Biology.

[27]  Alok J. Saldanha,et al.  Java Treeview - extensible visualization of microarray data , 2004, Bioinform..

[28]  Michael I. Love,et al.  RNA-Seq workflow: gene-level exploratory analysis and differential expression [version 2; referees: 2 approved] , 2016 .

[29]  Roger E Bumgarner,et al.  MeV+R: using MeV as a graphical user interface for Bioconductor applications in microarray analysis , 2008, Genome Biology.