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

Scatter Plot01:15

Scatter Plot

7.1K
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:
7.1K
Boxplot01:12

Boxplot

8.6K
Box plots (also called box-and-whisker plots or box-whisker plots) give an excellent graphical image of the concentration of the data. They also show how far the extreme values are from most data. A box plot is constructed from five values: the minimum value, the first quartile, the median, the third quartile, and the maximum value. We use these values to compare how close other data values are to them. To construct a box plot, use a horizontal or vertical number line and a rectangular box. The...
8.6K
Multiple Bar Graph01:07

Multiple Bar Graph

5.4K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
5.4K
Modified Boxplots00:57

Modified Boxplots

9.9K
A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...
9.9K
Pie Chart01:04

Pie Chart

14.3K
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.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
14.3K
Interpreting R Charts01:22

Interpreting R Charts

94
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.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
94

You might also read

Related Articles

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

Sort by
Same author

Short RNA chaperones promote aggregation-resistant TDP-43 conformers to mitigate neurodegeneration.

Science (New York, N.Y.)·2026
Same author

Meta-unstable mRNAs in activated CD8<sup>+</sup> T cells are defined by interlinked AU-rich elements and m<sup>6</sup>A mRNA methylation.

Nature communications·2026
Same author

LAMP1 and LAMP2A localise to axonal organelles with distinct motility dynamics and partially overlapping molecular signatures in human neurons.

Journal of cell science·2026
Same author

CAR-SPLASH identifies nascent pre-mRNA structures implicated in kinetic coupling and alternative splicing.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Collective homeostasis of condensation-prone proteins via their mRNAs.

Nature·2025
Same author

The complete mitogenome of an unidentified <i>Oikopleura</i> species.

F1000Research·2025
Same journal

Optimized tRNA structure-seq reveals robust tRNA secondary structures in <i>S. cerevisiae</i> under mild stress conditions.

RNA (New York, N.Y.)·2026
Same journal

SERIPH: A Two-Step Extraction Protocol for Selective Enrichment of Semi-Extractable RNAs.

RNA (New York, N.Y.)·2026
Same journal

Reduced Sensitivity to RNA Structural Differences Distinguishes Eukaryotic Pus4 from Bacterial TruB.

RNA (New York, N.Y.)·2026
Same journal

Puf3 contributes to changes in mRNA solubility, translation elongation dynamics at rare arginine codons and loss of protein homeostasis in cells lacking Not4.

RNA (New York, N.Y.)·2026
Same journal

RBM38 Regulates HORMAD1 Splicing to Enhances MEK Inhibitor Sensitivity in Breast Cancer.

RNA (New York, N.Y.)·2026
Same journal

EF-P Inhibits Ribosomal α-Hydroxy Acid Incorporation: Strategic tRNA Body Selection for Co-incorporating α-Hydroxy Acids and Nonproteinogenic Amino Acids into Depsipeptides.

RNA (New York, N.Y.)·2026
See all related articles

Related Experiment Video

Updated: Aug 7, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.5K

clipplotr-a comparative visualization and analysis tool for CLIP data.

Anob M Chakrabarti1, Charlotte Capitanchik2, Jernej Ule2,3

  • 1The Francis Crick Institute, London, NW1 4AT, United Kingdom anob.chakrabarti@crick.ac.uk.

RNA (New York, N.Y.)
|March 9, 2023
PubMed
Summary
This summary is machine-generated.

The clipplotr tool simplifies the visualization and comparison of RNA-protein interaction data. It integrates CLIP data with annotations and functional genomics for biological insights.

Keywords:
CLIP technologiesRNA–protein interactionsdata integrationdata visualization

More Related Videos

Rapid Analysis and Exploration of Fluorescence Microscopy Images
11:41

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Published on: March 19, 2014

12.4K
Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:50

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

343

Related Experiment Videos

Last Updated: Aug 7, 2025

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.5K
Rapid Analysis and Exploration of Fluorescence Microscopy Images
11:41

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Published on: March 19, 2014

12.4K
Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:50

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

343

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Cross-linked immunoprecipitation (CLIP) technologies are crucial for studying RNA-protein interactions, generating extensive public datasets.
  • Analyzing CLIP data requires visual inspection and comparison across conditions or datasets, often necessitating further data processing.
  • Integrating CLIP signals with genomic annotations and functional data (e.g., RNA-seq) is essential for deriving biological insights.

Purpose of the Study:

  • To develop a user-friendly command-line tool, clipplotr, for enhanced visualization and comparative analysis of CLIP data.
  • To enable seamless integration of CLIP data with reference annotations and orthogonal functional genomic data.
  • To provide normalization and smoothing options for CLIP data to facilitate robust analysis.

Main Methods:

  • Developed clipplotr, a command-line tool written in R.
  • Implemented options for data normalization and smoothing.
  • Designed the tool to accept various input file formats for CLIP data, annotations, and functional genomics data.

Main Results:

  • clipplotr facilitates visual comparative and integrative analyses of CLIP data.
  • The tool generates publication-quality figures by combining CLIP signals with annotation and functional genomic tracks.
  • clipplotr is versatile, runnable on laptops and high-performance clusters, and supports diverse data inputs.

Conclusions:

  • clipplotr simplifies the exploration and interpretation of CLIP-seq datasets.
  • The tool enhances the ability to perform comparative and integrative analyses, aiding biological discovery.
  • clipplotr is freely available with source code and documentation, promoting accessibility and reproducibility.