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RNA-seq

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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: Sep 6, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

ReadBouncer: precise and scalable adaptive sampling for nanopore sequencing.

Jens-Uwe Ulrich^1,2,3, Ahmad Lutfi^1,3, Kilian Rutzen⁴

¹Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, 14482 Potsdam, Germany.

Bioinformatics (Oxford, England)

|June 27, 2022

Summary

This summary is machine-generated.

ReadBouncer enhances nanopore sequencing by efficiently classifying and rejecting unwanted DNA sequences. This new adaptive sampling tool improves enrichment of low-abundance sequences, even with large reference genomes, on standard hardware.

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Last Updated: Sep 6, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

Fine-tuning the Size and Minimizing the Noise of Solid-state Nanopores

Fine-tuning the Size and Minimizing the Noise of Solid-state Nanopores

Published on: October 31, 2013

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Published on: March 11, 2020

Area of Science:

Genomics and Bioinformatics
Molecular Biology

Background:

Nanopore sequencing enables targeted DNA sequencing by rejecting unwanted sequences.
Existing adaptive sampling tools struggle with large reference sequences or require specialized hardware (GPUs).
There is a need for efficient in-silico depletion of overrepresented sequences to enrich low-abundance targets.

Purpose of the Study:

To develop a novel nanopore adaptive sampling approach for improved targeted sequencing.
To enhance the enrichment of low-abundance nucleotide sequences.
To provide an accessible and efficient tool for researchers without extensive bioinformatics expertise.

Main Methods:

Implemented a new adaptive sampling method combining fast CPU/GPU base calling with Interleaved Bloom Filters for read classification.
Developed ReadBouncer for sensitive and specific read rejection.
Ensured compatibility with large reference sequences and commodity hardware.

Main Results:

ReadBouncer demonstrates superior performance in read classification sensitivity and specificity compared to existing tools.
The approach effectively removes reads from large reference sequences.
The tool operates efficiently on standard hardware without requiring GPUs.

Conclusions:

ReadBouncer offers a robust and accessible solution for nanopore adaptive sampling.
It significantly improves the enrichment of low-abundance sequences.
The user-friendly design makes advanced targeted sequencing accessible to a wider range of researchers.