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Related Concept Videos

Pie Chart01:04

Pie Chart

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A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
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The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
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A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
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Histogram01:05

Histogram

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The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
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Interpreting R Charts01:22

Interpreting R Charts

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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
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Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
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InCHlib - interactive cluster heatmap for web applications.

Ctibor Skuta1, Petr Bartůněk2, Daniel Svozil1

  • 1Laboratory of Informatics and Chemistry, Faculty of Chemical Technology, Institute of Chemical Technology Prague, Technická 5, CZ-166 28 Prague, Czech Republic ; CZ-OPENSCREEN, Institute of Molecular Genetics of the ASCR, v. v. i, Vídeňská 1083, CZ-142 20 Prague, Czech Republic.

Journal of Cheminformatics
|September 30, 2014
PubMed
Summary
This summary is machine-generated.

We developed InCHlib, an interactive JavaScript library for exploring cluster heatmaps. This tool visualizes hierarchical clustering results, aiding analysis of large biological and chemical datasets.

Keywords:
Big dataClient-side scriptingCluster heatmapData clusteringExplorationJavaScript libraryScientific visualizationWeb integration

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Area of Science:

  • Bioinformatics
  • Data Visualization
  • Computational Biology

Background:

  • Hierarchical clustering identifies groups of similar objects, visualized as dendrograms.
  • Cluster heatmaps display data matrices with rows/columns ordered by hierarchical clustering.
  • These visualizations are crucial for analyzing large-scale biological and chemical data.

Purpose of the Study:

  • To introduce InCHlib, an interactive JavaScript library for cluster heatmap visualization and exploration.
  • To provide a lightweight, client-side solution for enhancing the analysis of complex datasets.

Main Methods:

  • Developed InCHlib, a JavaScript library for interactive cluster heatmap visualization.
  • Included a Python utility script (inchlib_clust) for data clustering and input file preparation.
  • Enabled features like row selection, zooming, and modification of heatmap appearance.

Main Results:

  • InCHlib offers a highly interactive and lightweight cluster heatmap visualization.
  • Users can select rows, zoom into clusters, and modify heatmap appearance.
  • The library supports augmentation with metadata and interconnection with external data sources.

Conclusions:

  • InCHlib is a versatile, client-side JavaScript library for cluster heatmap exploration.
  • Easily deployable in web applications, it facilitates analysis of chemical and biological data.
  • Its application extends beyond life sciences, offering broad utility.