NOJAH: NOt Just Another Heatmap for genome-wide cluster analysis

• Published in: PloS one Vol. 14; no. 3; p. e0204542
• Main Authors: Rupji, Manali, Dwivedi, Bhakti, Kowalski, Jeanne
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 28.03.2019; Public Library of Science (PLoS)
• Subjects: Adaptation; Algorithms; Analysis; Big Data; Bioinformatics; Biology and Life Sciences; Biomarkers, Tumor - genetics; Breast cancer; Breast Neoplasms - genetics; Cancer; Cluster Analysis; Computer Graphics; Construction; Data processing; DNA Copy Number Variations; DNA Methylation; Female; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Gene sequencing; Genes; Genetic aspects; Genetic diversity; Genetic research; Genomes; Genomics; Genomics - methods; High-Throughput Nucleotide Sequencing - methods; Humans; Medicine and Health Sciences; Next-generation sequencing; Physical Sciences; Principal components analysis; Replication; Research and Analysis Methods; Samples; Sequence Analysis, DNA - methods; Software; Source code; Statistical methods; Statistical significance; Statistics; Survival analysis; Technology; Workflow; Workflow software; Atlanta Georgia; United States > US; Georgia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0204542

Since their inception, several tools have been developed for cluster analysis and heatmap construction. The application of such tools to the number and types of genome-wide data available from next generation sequencing (NGS) technologies requires the adaptation of statistical concepts, such as in defining a most variable gene set, and more intricate cluster analyses method to address multiple omic data types. Additionally, the growing number of publicly available datasets has created the desire to estimate the statistical significance of a gene signature derived from one dataset to similarly group samples based on another dataset. The currently available number of tools and their combined use for generating heatmaps, along with the several adaptations of statistical concepts for addressing the higher dimensionality of genome-wide NGS-derived data, has created a further challenge in the ability to replicate heatmap results. We introduce NOJAH (NOt Just Another Heatmap), an interactive tool that defines and implements a workflow for genome-wide cluster analysis and heatmap construction by creating and combining several tools into a single user interface. NOJAH includes several newly developed scripts for techniques that though frequently applied are not sufficiently documented to allow for replicability of results. These techniques include: defining a most variable gene set (a.k.a., 'core genes'), estimating the statistical significance of a gene signature to separate samples into clusters, and performing a result merging integrated cluster analysis. With only a user uploaded dataset, NOJAH provides as output, among other things, the minimum documentation required for replicating heatmap results. Additionally, NOJAH contains five different existing R packages that are connected in the interface by their functionality as part of a defined workflow for genome-wide cluster analysis. The NOJAH application tool is available at http://bbisr.shinyapps.winship.emory.edu/NOJAH/ http://shinygispa.winship.emory.edu/shinyGISPA/ with corresponding source code available at https://github.com/bbisr-shinyapps/NOJAH/.