ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

Abstract

The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/.

Salivary metals, age, and gender correlate with cultivable oral Candida carriage levels

“…Statistical analyses were performed using GraphPad Prism or SAS 9.4 software [31]. Principle component analysis was applied using the ClustVis data visualization web tool [32], and correlation matrix plots were generated with the software, R [33]. …”

MethSurv: A Web Tool to Perform Multivariable Survival Analysis Using DNA Methylation Data

“…The default clustering option utilizes average linkage method using correlation distance (correlation subtracted from 1). Seamless integration of MethSurv with ClustVis [23] maximum, Manhattan and Canberra can be explored. For PCA calculations, singular value decomposition, NIPALS PCA and probabilistic PCA can be used in ClustVis.…”

Biphasic Study to Characterize Agricultural Biogas Plants by High-Throughput 16S rRNA Gene Amplicon Sequencing and Microscopic Analysis

“…The ClustVis [30] and metagenomeSeq tools [31] were used to detect differentially abundant features in the datasets analyzed using Principal Component Analysis (PCA) as described recently [30]. Furthermore, to gain an overview on the biodiversity of the studied microbial communities, the Shannon index was computed based on 16S rRNA fragments classified on rank genus as described previously [8].…”

“…Finally, to compare the microbial community structures of the analyzed BGPs, PCA with the program ClustVis [30] was conducted. Results for each independent technical replicate are shown in Fig.…”

“…1) using HT 16S rRNA gene amplicon sequencing revealed that 4% to 8% of all classified 16S rRNA gene sequences were assigned to the superkingdom Archaea. The ClustVis program [30] was applied to detect differentially abundant features in samples representing three mesophilic microbial communities (BGP1, BGP2, and BGP3) and one thermophilic microbiome (BGP4). Two independent technical replicates for each BGP sample are shown (e.g., BGP1.1, first replicate of the BGP1 sample).…”