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

Regression Analysis01:11

Regression Analysis

8.4K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.4K
Regression Toward the Mean01:52

Regression Toward the Mean

7.0K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.0K
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

1.6K
Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
1.6K
Multiple Regression01:25

Multiple Regression

4.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.0K
Correlation and Regression00:53

Correlation and Regression

3.4K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.4K
What is an Experiment?01:12

What is an Experiment?

18.3K
An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
18.3K

You might also read

Related Articles

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

Sort by
Same author

AutoZyme: An Autonomous Agentic Framework to Optimize Bioinformatics Software.

bioRxiv : the preprint server for biology·2026
Same author

SIRPα ablated iPSC-derived macrophages resist hypophagia and enhance mAb-dependent and CAR-mediated cytotoxicity of solid tumors.

Molecular therapy. Oncology·2026
Same author

simCRISPR: Modeling Experimental Complexity in Pooled CRISPR Screens.

bioRxiv : the preprint server for biology·2026
Same author

CN-RNN: a Deep Learning Framework for Copy Number Variation Detection with Exome Sequencing Data.

bioRxiv : the preprint server for biology·2026
Same author

Human neural organoid modeling of diffuse midline glioma captures the complexity of patient tumors.

Journal of neuro-oncology·2026
Same author

Aberrant immune regulation and enrichment of stem-like CD8<sup>+</sup> T cells in the pancreatic lymph node during type 1 diabetes development.

bioRxiv : the preprint server for biology·2026

Related Experiment Video

Updated: Feb 3, 2026

Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience
08:14

Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience

Published on: August 26, 2014

12.1K

Trendy: segmented regression analysis of expression dynamics in high-throughput ordered profiling experiments.

Rhonda Bacher1, Ning Leng2, Li-Fang Chu2

  • 1Department of Biostatistics, University of Florida, Gainesville, FL, USA. rbacher@ufl.edu.

BMC Bioinformatics
|October 18, 2018
PubMed
Summary
This summary is machine-generated.

Trendy, an R package, identifies gene expression dynamics in ordered experiments using segmented regression. It reveals individual gene patterns and overall transcriptome changes, aiding biological discovery in time-course and spatial-course studies.

Keywords:
Gene expressionR packageRNA-seqSegmented regressionShinyTime-course

More Related Videos

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K
High-throughput Titration of Luciferase-expressing Recombinant Viruses
08:09

High-throughput Titration of Luciferase-expressing Recombinant Viruses

Published on: September 19, 2014

13.4K

Related Experiment Videos

Last Updated: Feb 3, 2026

Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience
08:14

Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience

Published on: August 26, 2014

12.1K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K
High-throughput Titration of Luciferase-expressing Recombinant Viruses
08:09

High-throughput Titration of Luciferase-expressing Recombinant Viruses

Published on: September 19, 2014

13.4K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput expression profiling in ordered conditions (e.g., time-course, spatial-course) is crucial for studying differentiation and spatial patterns.
  • Analyzing dynamic changes at individual gene and whole transcriptome levels offers insights into gene function, pathways, and critical time points.

Purpose of the Study:

  • To introduce Trendy, an R package for analyzing gene expression dynamics in experiments with ordered conditions.
  • To provide a method for characterizing individual gene expression patterns and summarizing global transcriptome dynamics.

Main Methods:

  • Utilizes segmented regression models to identify optimal patterns for each gene.
  • Simultaneously characterizes gene-specific expression patterns and overall dynamic activity.
  • Applies methods to both microarray and RNA-sequencing (RNA-seq) datasets.

Main Results:

  • Trendy identifies the optimal segmented regression model for each gene's expression pattern.
  • Pinpoints the location and direction of dynamic expression changes.
  • Demonstrates biological relevance of results on diverse expression datasets.

Conclusions:

  • Trendy is a flexible R package for characterizing gene-specific expression and global dynamics in ordered experiments.
  • Provides a valuable tool for researchers studying complex biological processes.
  • Freely available on Bioconductor with comprehensive documentation.