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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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Related Experiment Video

Updated: Jun 28, 2025

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing.

Yi Xie¹, Huimei Chen¹, Vasuki Ranjani Chellamuthu²

¹Programme in Cardiovascular and Metabolic Disorders and Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore.

International Journal of Molecular Sciences

|April 13, 2024

Summary

This study compares single-cell RNA sequencing (scRNA-seq) methods, with and without sample multiplexing. Parse Biosciences

Keywords:

10x PBMC SPLiT-seq multiplexing single-cell RNA sequencing

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Last Updated: Jun 28, 2025

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

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Published on: March 12, 2021

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

Published on: January 19, 2017

Area of Science:

Genomics
Molecular Biology
Biotechnology

Background:

Single-cell RNA sequencing (scRNA-seq) is crucial for understanding cellular heterogeneity.
Sample multiplexing in scRNA-seq enhances throughput and reduces costs and batch effects.
A direct comparison of multiplexing and non-multiplexing scRNA-seq platforms is needed.

Purpose of the Study:

To benchmark and compare scRNA-seq methods from Parse Biosciences (with multiplexing) and 10x Genomics (without multiplexing).
To evaluate data quality, cell type identification, and gene detection sensitivity between platforms.
To provide guidance for selecting scRNA-seq methodologies for high-throughput studies.

Main Methods:

Peripheral blood mononuclear cells (PBMCs) from two healthy donors were analyzed.
scRNA-seq was performed using Parse Biosciences (sample multiplexing) and 10x Genomics (no sample multiplexing) platforms.
Demultiplexed data from Parse was compared against 10x data for cell type frequencies and gene detection.

Main Results:

Demultiplexed Parse data showed comparable cell type frequencies to non-multiplexed 10x data.
Parse exhibited higher sensitivity in detecting rare cell types like plasmablasts and dendritic cells.
Comparative transcript quantification revealed platform-specific gene length and GC content distributions.

Conclusions:

Parse Biosciences' multiplexing approach provides comparable cell type resolution to 10x Genomics.
Parse demonstrates superior sensitivity for rare cell type detection.
Findings aid researchers in choosing appropriate scRNA-seq platforms for high-throughput applications.