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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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BingleSeq: a user-friendly R package for bulk and single-cell RNA-Seq data analysis.

Daniel Dimitrov¹, Quan Gu¹

¹MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow, UK.

|January 4, 2021

Summary

BingleSeq offers a user-friendly solution for analyzing RNA sequencing count matrices from both bulk and single-cell experiments. This R package empowers biologists without programming skills to perform complex transcriptome analyses.

Keywords:

Differential expression Functional annotation R package RNA-Seq Rank-based consensus Single-cell RNA-Seq

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Last Updated: Nov 23, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Area of Science:

Bioinformatics and Computational Biology
Genomics and Transcriptomics

Background:

RNA sequencing (RNA-Seq) is crucial for transcriptome analysis, commonly used for differential gene expression.
Single-cell RNA sequencing (scRNA-Seq) enables transcriptome profiling at the individual cell level.
Analyzing RNA-Seq data, particularly count matrices, typically requires programming expertise, posing a barrier for many researchers.

Purpose of the Study:

To develop an intuitive and user-friendly application for analyzing count matrices from both bulk and single-cell RNA sequencing experiments.
To provide biologists with no programming experience access to advanced RNA-Seq analysis tools.

Main Methods:

BingleSeq was developed as an R package with an interactive dashboard-like user interface.
It integrates state-of-the-art software packages for both bulk and single-cell RNA-Seq analyses.
Includes features for data visualization, functional annotation, and rank-based consensus for differential gene analysis.

Main Results:

BingleSeq provides a streamlined workflow for analyzing RNA-Seq count matrices.
The application simplifies complex analyses, making them accessible to users without programming backgrounds.
It incorporates multiple powerful analysis tools into a single, easy-to-use interface.

Conclusions:

BingleSeq democratizes RNA sequencing data analysis by removing the need for programming skills.
It serves as a valuable tool for biologists seeking to explore both bulk and single-cell RNA-Seq data effectively.
The package is easily installable from GitHub, promoting widespread adoption and use.