Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials

Statistical Software for Data Analysis and Clinical Trials

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...

Introduction to R

Introduction to R

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...

Statgraphics

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...

You might also read

Related Articles

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

Sort by

Same author

Optimization of experimental designs for biological rhythm discovery.

PLoS computational biology·2025

Same author

Epigenetic age oscillates during the day.

Aging cell·2024

Same author

One-pot trimodal mapping of unmethylated, hydroxymethylated, and open chromatin sites unveils distinctive 5hmC roles at dynamic chromatin loci.

Cell chemical biology·2023

Same author

Diurnal oscillations of MRI metrics in the brains of male participants.

Nature communications·2023

Same author

Selective chemical tracking of Dnmt1 catalytic activity in live cells.

Molecular cell·2022

Same author

Distribution and regulatory roles of oxidized 5-methylcytosines in DNA and RNA of the basidiomycete fungi <i>Laccaria bicolor</i> and <i>Coprinopsis cinerea</i>.

Open biology·2022

Search research articles

Related Experiment Video

Updated: Jul 21, 2025

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

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

Published on: January 16, 2019

Scikick: A sidekick for workflow clarity and reproducibility during extensive data analysis.

Matthew Carlucci^1,2, Tadas Bareikis^1,2, Karolis Koncevičius²

¹The Krembil Family Epigenetics Laboratory, The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.

|July 27, 2023

Summary

Reproducibility in science is enhanced by Scikick, a new tool simplifying computational analysis workflows. It standardizes project structure and tracks data analysis steps for transparent research findings.

More Related Videos

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

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

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

Published on: April 18, 2025

Related Experiment Videos

Last Updated: Jul 21, 2025

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

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

Published on: January 16, 2019

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

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

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

Published on: April 18, 2025

Area of Science:

Computational science
Data science
Scientific reproducibility

Background:

Reproducibility is vital for scientific progress but implementing clear data analysis workflows is difficult.
A lack of detailed computational step records hinders the validation of research findings.

Purpose of the Study:

To introduce Scikick, a software tool designed to simplify the configuration, execution, and presentation of scientific computational analyses.
To address the challenges in maintaining transparent and reproducible data analysis workflows.

Main Methods:

Scikick utilizes notebooks as the primary units for workflow execution.
It establishes a standardized project structure and automatically tracks dependencies between analysis steps.
The tool includes methods for compiling diverse research results into a unified final report.

Main Results:

Scikick facilitates the creation of transparent data analysis workflows.
It transforms the complex management of computational analyses into a standardized and manageable practice.
The software provides utilities to ensure the traceability of computational steps.

Conclusions:

Scikick offers a practical solution for enhancing the reproducibility of scientific research.
The tool promotes transparency and standardization in computational data analysis.
Scikick is available as open-source software with comprehensive documentation.