DendroX: multi-level multi-cluster selection in dendrograms
Rattachement africain : cn. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
BACKGROUND: Cluster heatmaps are widely used in biology and other fields to uncover clustering patterns in data matrices. Most cluster heatmap packages provide utility functions to divide the dendrograms at a certain level to obtain clusters, but it is often difficult to locate the appropriate cut in the dendrogram to obtain the clusters seen in the heatmap or computed by a statistical method. Multiple cuts are required if the clusters locate at different levels in the dendrogram. RESULTS: We developed DendroX, a web app that provides interactive visualization of a dendrogram where users can divide the dendrogram at any level and in any number of clusters and pass the labels of the identified clusters for functional analysis. Helper functions are provided to extract linkage matrices from cluster heatmap objects in R or Python to serve as input to the app. A graphic user interface was also developed to help prepare input files for DendroX from data matrices stored in delimited text files. The app is scalable and has been tested on dendrograms with tens of thousands of leaf nodes. As a case study, we clustered the gene expression signatures of 297 bioactive chemical compounds in the LINCS L1000 dataset and visualized them in DendroX. Seventeen biologically meaningful clusters were identified based on the structure of the dendrogram and the expression patterns in the heatmap. We found that one of the clusters consisting of mostly naturally occurring compounds is not previously reported and has its members sharing broad anticancer, anti-inflammatory and antioxidant activities. CONCLUSIONS: DendroX solves the problem of matching visually and computationally determined clusters in a cluster heatmap and helps users navigate among different parts of a dendrogram. The identification of a cluster of naturally occurring compounds with shared bioactivities implicates a convergence of biological effects through divergent mechanisms.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- DendroX: multi-level multi-cluster selection in dendrograms
- Date Crossref
- 02/02/2024
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Second Military Medical University pays non établi dans la noticeUniversité ou école supérieure
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Eastern Hepatobiliary Surgery Hospital Department of Biliary Tract Surgery I pays non établi dans la noticeÉtablissement de santé
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Inc. (China) pays non établi dans la noticeEntreprise
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Nanjing General Hospital of Nanjing Military Command pays non établi dans la noticeÉtablissement de santé
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Nanjing Medical University pays non établi dans la noticeUniversité ou école supérieure
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Nanjing University Research Institute of General Surgery pays non établi dans la noticeUniversité ou école supérieure
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Department of Clinical and Translational Medicine pays non établi dans la noticeÉtablissement de santé
Second Military Medical University, Department of Biliary Tract Surgery I — Eastern Hepatobiliary Surgery Hospital et Inc. (China), avec 4 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.