Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

758
Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
758
Overview of Microsoft Excel as a Data Analysis Tool01:13

Overview of Microsoft Excel as a Data Analysis Tool

1.6K
Microsoft Excel is a cornerstone tool for data analysis and statistical operations, offering a wide array of functionalities to manage, analyze, and visualize data efficiently. Recognized for its versatility, Excel facilitates the performance of basic to complex statistical operations, serving as an indispensable asset for analysts, researchers, and students alike. Excel's significance in data analysis emanates from its spreadsheet environment, where data can be organized in rows and...
1.6K
Performing a Simple Data Analysis using MS-Excel Function01:17

Performing a Simple Data Analysis using MS-Excel Function

1.1K
Microsoft Excel offers a suite of functions and tools ideal for statistical analysis, making it accessible to students and researchers. This article outlines fundamental Excel functions pivotal for data analysis.
SUM: This function calculates the total sum of a range of values. It's the foundation for aggregating data, essential for determining overall trends and totals in datasets.
AVERAGE: It computes the mean value of a given set of numbers, providing a quick insight into the central...
1.1K
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.6K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.6K
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

335
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
335
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

44.8K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
44.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Machine learning-driven QSAR modeling combined with single cell transcriptomics identifies novel drug targets for lung cancer.

Journal of translational medicine·2026
Same author

scAED: a framework for mapping the enhancer state at single-cell resolution.

Briefings in bioinformatics·2025
Same author

ScRDAVis: An R shiny application for single-cell transcriptome data analysis and visualization.

PLoS computational biology·2025
Same author

GAIN-BRCA: a graph-based AI-net framework for breast cancer subtype classification using multiomics data.

Bioinformatics advances·2025
Same author

Identification of Potential Prophylactic Medical Countermeasures Against Acute Radiation Syndrome (ARS).

International journal of molecular sciences·2025
Same author

Defining molecular signatures of the solid/pseudopapillary and pseudoglandular patterns in so-called "solid-tubulocystic intrahepatic cholangiocarcinoma vs. NIPBL::NACC1 fusion hepatic carcinoma".

Pathology, research and practice·2025
Same journal

MOREshiny: a user-friendly application for the inference of phenotype-specific multi-omic regulatory networks.

Bioinformatics advances·2026
Same journal

spammR: an R package designed for analysis and integration of spatial multi-omic measurements.

Bioinformatics advances·2026
Same journal

Interpretable prediction and generation of ASC-speck aptamers using multiscale deep biological learning models.

Bioinformatics advances·2026
Same journal

vClassifier: a toolkit for high-resolution phylogenetic classification of prokaryotic viruses.

Bioinformatics advances·2026
Same journal

GWAIS-Web: a free and secure web service for ultra-fast and large-scale genome-wide association interaction studies.

Bioinformatics advances·2026
Same journal

Folding the unfoldable 2: using AlphaFold and ESMFold to explore spurious proteins.

Bioinformatics advances·2026
See all related articles

Related Experiment Video

Updated: Feb 6, 2026

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis
07:40

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

968

VST-DAVis: an R Shiny application and web-browser for spatial transcriptomics data analysis and visualization.

Sankarasubramanian Jagadesan1, Chittibabu Guda1,2

  • 1Department of Genetics, Cell Biology and Anatomy, 985805 Nebraska Medical Center, University of Nebraska Medical Center, Omaha, NE 68198-5805, United States.

Bioinformatics Advances
|February 5, 2026
PubMed
Summary
This summary is machine-generated.

Visium HD Spatial Transcriptomics Data Analysis and Visualization (VST-DAVIS) is a user-friendly R Shiny application for analyzing spatial transcriptomics data. It offers comprehensive tools for researchers, simplifying complex analyses and visualization for single or multiple samples.

More Related Videos

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

781
High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.8K

Related Experiment Videos

Last Updated: Feb 6, 2026

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis
07:40

Spatially Compact Arrangement of Larval Zebrafish Sections for Spatial Transcriptomic Analysis

Published on: May 16, 2025

968
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
10:16

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

781
High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.8K

Area of Science:

  • Spatial Transcriptomics
  • Bioinformatics
  • Computational Biology

Background:

  • Spatial transcriptomics technologies like 10x Genomics Visium HD generate complex datasets.
  • Analyzing these datasets requires specialized bioinformatics expertise and tools.
  • Existing tools may lack user-friendliness or comprehensive analytical capabilities.

Purpose of the Study:

  • To develop an interactive R Shiny application named VST-DAVIS for intuitive spatial transcriptomics data analysis.
  • To provide a user-friendly, end-to-end solution for researchers, including those without programming expertise.
  • To support both single and multiple sample analyses for comparative studies.

Main Methods:

  • Developed VST-DAVIS as an R Shiny application and web browser.
  • Integrated popular R packages (Seurat, Monocle3, CellChat, hdWGCNA) for diverse analytical tasks.
  • Designed a streamlined graphical interface for intuitive data handling and visualization.

Main Results:

  • VST-DAVIS enables comprehensive spatial transcriptomics analysis from quality control to network reconstruction.
  • The application supports various input formats and outputs high-quality graphics.
  • It facilitates comparative analyses across multiple samples and biological conditions.

Conclusions:

  • VST-DAVIS makes advanced spatial transcriptomics data analysis accessible to a broader research community.
  • The tool enhances the usability of Visium HD data for researchers with varying technical skills.
  • It provides a robust platform for exploring spatial gene expression, cell communication, and co-expression networks.