Click-qPCR: A Simple Tool for Interactive qPCR Data Analysis

Real-time quantitative PCR (qPCR) is a pivotal technique for analyzing gene expression and DNA copy number variations. However, the limited availability of user-friendly software tools for qPCR data analysis presents a significant challenge for experimental biologists with limited computational skills. To address this issue, we developed Click-qPCR, a user-friendly and web-based Shiny application for qPCR data analysis. Click-qPCR streamlines ΔCq and ΔΔCq calculations using user-uploaded CSV data files. The interactive interface of the application allows users to select genes and experimental groups and perform Welch's <i>t</i>-tests and one-way analysis of variance with Dunnett's post-hoc test for pairwise and multi-group comparisons, respectively. Results are visualized via interactive bar plots (mean ± standard deviation with individual data points) and can be downloaded as publication-quality images, along with summary statistics. Click-qPCR empowers researchers to efficiently process, interpret, and visualize qPCR data regardless of their programming experience, thereby facilitating routine analysis tasks. Click-qPCR Shiny application is available at https://kubo-azu.shinyapps.io/Click-qPCR/, while its source code and user guide are available at https://github.com/kubo-azu/Click-qPCR. Key features • A simple browser-based interface that enables biologists without coding experience to perform qPCR data analysis. • Provides integrated data analysis workflows for ΔCq/ΔΔCq calculations and one-way analysis of variance, with appropriate statistical tests and generation of publication-ready visualizations. • Designed for experimental contexts that require quick and reproducible comparisons of gene expression across various conditions, treatments, and reference genes. • Open-source and freely accessible online, supporting transparency, reproducibility, and broad adoption within molecular biology and biomedical research communities.

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Publication Details

Journal
BIO-PROTOCOL
Published
2025-01-01
DOI
https://doi.org/10.21769/bioprotoc.5513
Citations
1
Primary Topic
Molecular Biology Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.81
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article

Click-qPCR: A Simple Tool for Interactive qPCR Data Analysis

Azusa Kubota, Atsushi Tajima
1 citations
BIO-PROTOCOL
Molecular Biology Techniques and Applications
0.81
article

Click-qPCR: A Simple Tool for Interactive qPCR Data Analysis

Azusa Kubota, Atsushi Tajima
article en
1 citations

Abstract

Real-time quantitative PCR (qPCR) is a pivotal technique for analyzing gene expression and DNA copy number variations. However, the limited availability of user-friendly software tools for qPCR data analysis presents a significant challenge for experimental biologists with limited computational skills. To address this issue, we developed Click-qPCR, a user-friendly and web-based Shiny application for qPCR data analysis. Click-qPCR streamlines ΔCq and ΔΔCq calculations using user-uploaded CSV data files. The interactive interface of the application allows users to select genes and experimental groups and perform Welch's <i>t</i>-tests and one-way analysis of variance with Dunnett's post-hoc test for pairwise and multi-group comparisons, respectively. Results are visualized via interactive bar plots (mean ± standard deviation with individual data points) and can be downloaded as publication-quality images, along with summary statistics. Click-qPCR empowers researchers to efficiently process, interpret, and visualize qPCR data regardless of their programming experience, thereby facilitating routine analysis tasks. Click-qPCR Shiny application is available at https://kubo-azu.shinyapps.io/Click-qPCR/, while its source code and user guide are available at https://github.com/kubo-azu/Click-qPCR. Key features • A simple browser-based interface that enables biologists without coding experience to perform qPCR data analysis. • Provides integrated data analysis workflows for ΔCq/ΔΔCq calculations and one-way analysis of variance, with appropriate statistical tests and generation of publication-ready visualizations. • Designed for experimental contexts that require quick and reproducible comparisons of gene expression across various conditions, treatments, and reference genes. • Open-source and freely accessible online, supporting transparency, reproducibility, and broad adoption within molecular biology and biomedical research communities.

BIO-PROTOCOLVol. 15(1384)
Kanazawa University (JP)
Openalex Percentile: Top 22%
Molecular Biology Techniques and Applications
0.81
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