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InCHlib – interactive cluster heatmap for web applications
BACKGROUND: Hierarchical clustering is an exploratory data analysis method that reveals the groups (clusters) of similar objects. The result of the hierarchical clustering is a tree structure called dendrogram that shows the arrangement of individual clusters. To investigate the row/column hierarchi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173117/ https://www.ncbi.nlm.nih.gov/pubmed/25264459 http://dx.doi.org/10.1186/s13321-014-0044-4 |
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author | Škuta, Ctibor Bartůněk, Petr Svozil, Daniel |
author_facet | Škuta, Ctibor Bartůněk, Petr Svozil, Daniel |
author_sort | Škuta, Ctibor |
collection | PubMed |
description | BACKGROUND: Hierarchical clustering is an exploratory data analysis method that reveals the groups (clusters) of similar objects. The result of the hierarchical clustering is a tree structure called dendrogram that shows the arrangement of individual clusters. To investigate the row/column hierarchical cluster structure of a data matrix, a visualization tool called ‘cluster heatmap’ is commonly employed. In the cluster heatmap, the data matrix is displayed as a heatmap, a 2-dimensional array in which the colour of each element corresponds to its value. The rows/columns of the matrix are ordered such that similar rows/columns are near each other. The ordering is given by the dendrogram which is displayed on the side of the heatmap. RESULTS: We developed InCHlib (Interactive Cluster Heatmap Library), a highly interactive and lightweight JavaScript library for cluster heatmap visualization and exploration. InCHlib enables the user to select individual or clustered heatmap rows, to zoom in and out of clusters or to flexibly modify heatmap appearance. The cluster heatmap can be augmented with additional metadata displayed in a different colour scale. In addition, to further enhance the visualization, the cluster heatmap can be interconnected with external data sources or analysis tools. Data clustering and the preparation of the input file for InCHlib is facilitated by the Python utility script inchlib_clust. CONCLUSIONS: The cluster heatmap is one of the most popular visualizations of large chemical and biomedical data sets originating, e.g., in high-throughput screening, genomics or transcriptomics experiments. The presented JavaScript library InCHlib is a client-side solution for cluster heatmap exploration. InCHlib can be easily deployed into any modern web application and configured to cooperate with external tools and data sources. Though InCHlib is primarily intended for the analysis of chemical or biological data, it is a versatile tool which application domain is not limited to the life sciences only. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-014-0044-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4173117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-41731172014-09-26 InCHlib – interactive cluster heatmap for web applications Škuta, Ctibor Bartůněk, Petr Svozil, Daniel J Cheminform Software BACKGROUND: Hierarchical clustering is an exploratory data analysis method that reveals the groups (clusters) of similar objects. The result of the hierarchical clustering is a tree structure called dendrogram that shows the arrangement of individual clusters. To investigate the row/column hierarchical cluster structure of a data matrix, a visualization tool called ‘cluster heatmap’ is commonly employed. In the cluster heatmap, the data matrix is displayed as a heatmap, a 2-dimensional array in which the colour of each element corresponds to its value. The rows/columns of the matrix are ordered such that similar rows/columns are near each other. The ordering is given by the dendrogram which is displayed on the side of the heatmap. RESULTS: We developed InCHlib (Interactive Cluster Heatmap Library), a highly interactive and lightweight JavaScript library for cluster heatmap visualization and exploration. InCHlib enables the user to select individual or clustered heatmap rows, to zoom in and out of clusters or to flexibly modify heatmap appearance. The cluster heatmap can be augmented with additional metadata displayed in a different colour scale. In addition, to further enhance the visualization, the cluster heatmap can be interconnected with external data sources or analysis tools. Data clustering and the preparation of the input file for InCHlib is facilitated by the Python utility script inchlib_clust. CONCLUSIONS: The cluster heatmap is one of the most popular visualizations of large chemical and biomedical data sets originating, e.g., in high-throughput screening, genomics or transcriptomics experiments. The presented JavaScript library InCHlib is a client-side solution for cluster heatmap exploration. InCHlib can be easily deployed into any modern web application and configured to cooperate with external tools and data sources. Though InCHlib is primarily intended for the analysis of chemical or biological data, it is a versatile tool which application domain is not limited to the life sciences only. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13321-014-0044-4) contains supplementary material, which is available to authorized users. Springer International Publishing 2014-09-17 /pmc/articles/PMC4173117/ /pubmed/25264459 http://dx.doi.org/10.1186/s13321-014-0044-4 Text en © Skuta et al.; licensee Chemistry Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Software Škuta, Ctibor Bartůněk, Petr Svozil, Daniel InCHlib – interactive cluster heatmap for web applications |
title | InCHlib – interactive cluster heatmap for web applications |
title_full | InCHlib – interactive cluster heatmap for web applications |
title_fullStr | InCHlib – interactive cluster heatmap for web applications |
title_full_unstemmed | InCHlib – interactive cluster heatmap for web applications |
title_short | InCHlib – interactive cluster heatmap for web applications |
title_sort | inchlib – interactive cluster heatmap for web applications |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173117/ https://www.ncbi.nlm.nih.gov/pubmed/25264459 http://dx.doi.org/10.1186/s13321-014-0044-4 |
work_keys_str_mv | AT skutactibor inchlibinteractiveclusterheatmapforwebapplications AT bartunekpetr inchlibinteractiveclusterheatmapforwebapplications AT svozildaniel inchlibinteractiveclusterheatmapforwebapplications |