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

Introduction to R01:11

Introduction to R

5.1K
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
5.1K
Interpreting R Charts01:22

Interpreting R Charts

382
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...
382
Introduction to Test of Independence01:21

Introduction to Test of Independence

3.0K
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
3.0K
Goodness-of-Fit Test01:16

Goodness-of-Fit Test

9.3K
The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
9.3K
Protein Folding Quality Check in the RER01:29

Protein Folding Quality Check in the RER

5.3K
ER is the primary site for the maturation and folding of soluble and transmembrane secretory proteins. The calnexin cycle is a specific chaperone system that folds and assesses the confirmation of N-glycosylated proteins before they can exit the ER lumen. The primary players of this quality check pipeline are the lectins, ER-resident chaperones, and a glucosyl transferase enzyme. In case the calnexin system in the lumen fails to salvage a misfolded protein, it is transported to the cytoplasm...
5.3K
Overview of Minitab01:11

Overview of Minitab

776
Minitab is a statistical software package designed for data analysis. With its origins in the 1970s and development at Pennsylvania State University, Minitab has grown significantly in its capabilities and applications. It plays a crucial role in quality management projects, especially in Six Sigma initiatives, by offering tools for process improvement and statistical analysis. Minitab's significance lies in its user-friendly interface, making complex statistical analysis accessible to...
776

You might also read

Related Articles

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

Sort by
Same author

MX2 Mediates Collapse of the HIV-1 Capsid.

bioRxiv : the preprint server for biologyĀ·2026
Same author

Mesoscale transport of enveloped viruses.

The Journal of chemical physicsĀ·2026
Same author

Infographic. The race to reduce injury and illness in professional road cycling.

British journal of sports medicineĀ·2025
Same author

Single-molecule localisation microscopy approaches reveal envelope glycoprotein clusters in single-enveloped viruses: a potential functional role?

Biochemical Society transactionsĀ·2025
Same author

Molecular subtyping of hypertensive disorders of pregnancy.

Nature communicationsĀ·2025
Same author

"Beyond the Finish Line" the Epidemiology of Injury and Illness in Professional Cycling: Insights from a Year-Long Prospective Study.

Sports (Basel, Switzerland)Ā·2025
Same journal

The genome sequence of the darkling beetle, <i>Phaleria cadaverina</i> (Fabricius, 1792) (Coleoptera: Tenebrionidae).

Wellcome open researchĀ·2026
Same journal

The genome sequence of the Orange Underwing, <i>Archiearis parthenias</i> (Linnaeus, 1761) (Lepidoptera: Geometridae).

Wellcome open researchĀ·2026
Same journal

The genome sequence of a hoverfly , <i>Neoascia tenur</i> (Harris, 1780) (Diptera: Syrphidae).

Wellcome open researchĀ·2026
Same journal

The genome sequence of <i>Adonis annua</i> L., 1753 (Ranunculales: Ranunculaceae).

Wellcome open researchĀ·2026
Same journal

Mature adipocytes lack functional Aryl Hydrocarbon Receptor - a study investigating its role in diet-induced obesity in mice.

Wellcome open researchĀ·2026
Same journal

The genome sequence of <i>Polygonum maritimum</i> L., 1753 (Caryophyllales: Polygonaceae).

Wellcome open researchĀ·2026
See all related articles

Related Experiment Video

Updated: Feb 25, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.7K

exampletestr-An easy start to unit testing R packages.

Rory Nolan1, Sergi Padilla-Parra1,2

  • 1Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.

Wellcome Open Research
|July 28, 2017
PubMed
Summary
This summary is machine-generated.

Most R package developers neglect unit tests. The exampletestr tool simplifies unit test creation by generating test shells from package documentation examples, ensuring code correctness and aiding comprehensive test suite development.

Keywords:
Rcovrexampletestrtesttestingtestthatunit

More Related Videos

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.8K
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

1.1K

Related Experiment Videos

Last Updated: Feb 25, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.7K
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.8K
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

1.1K

Area of Science:

  • Computer Science
  • Software Engineering

Background:

  • Unit tests are crucial for software quality but are underutilized by R package developers.
  • Existing methods for creating unit tests can be time-consuming and complex.

Purpose of the Study:

  • To simplify the process of writing unit tests for R packages.
  • To encourage greater adoption of unit testing practices among R developers.

Main Methods:

  • Developed the exampletestr R package to automatically generate unit test skeletons.
  • Leveraged existing examples from R package documentation as a basis for test creation.
  • Integrated exampletestr with the covr package for comprehensive test coverage analysis.

Main Results:

  • exampletestr successfully creates functional unit test shells from package documentation examples.
  • The generated tests verify the correctness of the documented examples.
  • Combining exampletestr and covr significantly reduces the effort required for comprehensive R package unit testing.

Conclusions:

  • exampletestr lowers the barrier to entry for R package unit testing.
  • Automating test generation from examples enhances code quality and developer efficiency.
  • This approach facilitates the creation of robust and well-tested R packages.