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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 12, 2025

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Scalable and unsupervised discovery from raw sequencing reads using SPLASH2.

Marek Kokot¹, Roozbeh Dehghannasiri^2,3, Tavor Baharav^4,5,6

¹Department of Algorithmics and Software, Silesian University of Technology, Gliwice, Poland.

Nature Biotechnology

|September 23, 2024

Summary

This summary is machine-generated.

SPLASH2 offers a fast, scalable method for detecting sequence variations in large datasets. It enables new biological discoveries, including unannotated splicing and circular RNA detection in cancer.

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Last Updated: Jun 12, 2025

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

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Published on: June 23, 2012

Novel Sequence Discovery by Subtractive Genomics

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Published on: January 25, 2019

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Accurate detection of sequence variations is crucial for understanding biological processes and diseases.
Existing methods may face challenges with massive datasets and diverse sequencing technologies.

Purpose of the Study:

To introduce SPLASH2, a novel, efficient, and scalable implementation for sequence variation detection.
To demonstrate the utility of SPLASH2 in identifying complex biological patterns in large-scale sequencing data.

Main Methods:

Development of SPLASH2, a k-mer counting-based approach for sequence variation analysis.
Application of SPLASH2 to single-cell RNA sequencing (RNA-seq) and bulk RNA-seq datasets.

Main Results:

SPLASH2 provides a fast and scalable solution for analyzing massive sequencing datasets.
Biological discoveries include identification of unannotated alternative splicing in cancer transcriptomes.
Sensitive detection of circular RNA was achieved using SPLASH2.

Conclusions:

SPLASH2 is an effective tool for regulated sequence variation detection across various sequencing technologies and biological contexts.
The method facilitates significant biological discoveries in cancer genomics and transcriptomics.