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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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Home
Reference-free Discovery With Barcoded Single-cell Sequencing.

Home
Reference-free Discovery With Barcoded Single-cell Sequencing.

Related Experiment Video

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Reference-free discovery with barcoded single-cell sequencing.

Roozbeh Dehghannasiri¹, Marek Kokot², Alexander L Starr³

¹Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.

Nature Biotechnology

|April 22, 2026

View abstract on PubMed

Summary

This summary is machine-generated.

sc-SPLASH enables reference-free discovery in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics. This new method efficiently preprocesses barcoded data, revealing novel proteins in sponge and tunicate immune cells.

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Competitive Genomic Screens of Barcoded Yeast Libraries

Competitive Genomic Screens of Barcoded Yeast Libraries

Published on: August 11, 2011

Related Experiment Videos

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Competitive Genomic Screens of Barcoded Yeast Libraries

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Published on: August 11, 2011

Area of Science:

Genomics
Bioinformatics
Evolutionary Biology

Background:

Single-cell RNA sequencing (scRNA-seq) typically focuses on gene expression, overlooking other transcriptome variations.
Existing methods for barcoded data preprocessing are computationally intensive.

Purpose of the Study:

Introduce sc-SPLASH, a novel statistics-first, reference-free method for scRNA-seq and spatial transcriptomics.
Develop an optimized barcoded data preprocessing submodule (BKC) for enhanced efficiency.

Main Methods:

sc-SPLASH employs a statistics-first approach for reference-free analysis.
The BKC submodule accelerates barcoded data preprocessing, outperforming UMI-tools by approximately 50-fold.
Applied to immune-like cells in sponge (Spongilla) and tunicate (Ciona).

Main Results:

sc-SPLASH successfully identifies novel secreted repeat proteins.
Discovered proteins were found in immune-like cells of Spongilla (a species absent from reference databases) and Ciona.
BKC submodule significantly improves preprocessing speed.

Conclusions:

sc-SPLASH offers a powerful new tool for transcriptome variation discovery in single-cell and spatial genomics.
The BKC submodule provides a substantial speed improvement for barcoded data preprocessing.
This approach can uncover novel biological insights, even in organisms with incomplete genomic references.