PT  - JOURNAL ARTICLE
AU  - Bohdan B. Khomtchouk
AU  - Claes Wahlestedt
TI  - shinyheatmap: ultra fast low memory heatmap software for big data genomics
AID  - 10.1101/076463
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 076463
4099  - http://biorxiv.org/content/early/2016/09/21/076463.short
4100  - http://biorxiv.org/content/early/2016/09/21/076463.full
AB  - Background Transcriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets. Visualizing such big data has posed technical challenges in biology, both in terms of available computational resources as well as programming acumen. Since heatmaps are used to depict high-dimensional numerical data as a colored grid of cells, efficiency and speed have often proven to be critical considerations in the process of successfully converting data into graphics. For example, rendering interactive heatmaps from large input datasets (e.g., 100k+ rows) has been computationally infeasible on both desktop computers and web browsers. In addition to memory requirements, programming skills and knowledge have frequently been barriers-to-entry for creating highly customizable heatmaps.Results We propose shinyheatmap: an advanced user-friendly heatmap software suite capable of efficiently creating highly customizable static and interactive biological heatmaps in a web browser. shinyheatmap is a low memory footprint program, making it particularly well-suited for the interactive visualization of extremely large datasets that cannot typically be computed in-memory due to size restrictions.Conclusions shinyheatmap is hosted online as a freely available web server with an intuitive graphical user interface: http://shinyheatmap.com. The methods are implemented in R, and are available as part of the shinyheatmap project at: https://github.com/Bohdan-Khomtchouk/shinyheatmap.PCAprincipal component analysisUIuser interface