2017
DOI: 10.1371/journal.pone.0176334
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shinyheatmap: Ultra fast low memory heatmap web interface for big data genomics

Abstract: BackgroundTranscriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets, especially across single-cell sequencing studies. 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 … Show more

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Cited by 111 publications
(67 citation statements)
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References 29 publications
(18 reference statements)
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“…The heat map was created at Shinyheatmap (http://www .shinyheatmap.com) using Euclidiean distance metrics and complete linkage algorithms (Khomtchouk et al 2017).…”
Section: Gene Expression Profile-input Datamentioning
confidence: 99%
“…The heat map was created at Shinyheatmap (http://www .shinyheatmap.com) using Euclidiean distance metrics and complete linkage algorithms (Khomtchouk et al 2017).…”
Section: Gene Expression Profile-input Datamentioning
confidence: 99%
“…A heatmap was constructed followed by cluster analysis using shiny heat map tool (Khomtchouk, Hennessy, & Wahlestedt, 2017; http://shinyheatmap.com/). The data used for heatmap construction were normalized based on Z‐scores calculated based on the following formula: z=XiX¯σwhere, X i , trueX¯ and σ stand for raw data, mean and standard deviation for each trait tested.…”
Section: Methodsmentioning
confidence: 99%
“…In recent years, the development of open-source software specially designed for the production of high-quality and interactive plots is becoming very active in various scientific fields [5][6][7]. Novel open source applications have also been developed to customize the graphical output of the Bayesian analysis [8].…”
Section: Introductionmentioning
confidence: 99%