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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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Updated: Apr 17, 2026

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

Improved data analysis for the MinION nanopore sequencer.

Miten Jain¹, Ian T Fiddes¹, Karen H Miga¹

¹1] UC Santa Cruz Genomics Institute, Santa Cruz, California, USA. [2] Department of Biomolecular Engineering, University of California, Santa Cruz, California, USA.

|February 17, 2015

Summary

This summary is machine-generated.

Oxford Nanopore sequencing offers speed and long reads for high-throughput genomics. This study optimized the MinION platform, achieving high accuracy for single-nucleotide variant detection and resolving complex genomic regions.

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Last Updated: Apr 17, 2026

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

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Published on: March 11, 2020

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Published on: June 3, 2019

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Published on: December 14, 2017

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Nanopore sequencing technologies, like the MinION, are advancing rapidly.
Key performance metrics include read length, accuracy, and error rates.
Optimizing these metrics is crucial for reliable genomic analysis.

Purpose of the Study:

To evaluate and optimize the performance of the MinION nanopore sequencer.
To develop a robust single-nucleotide variant detection tool.
To demonstrate the utility of nanopore sequencing for resolving complex genomic structures.

Main Methods:

Performance evaluation of the MinION using M13 genomic DNA.
Application of expectation maximization for error rate estimation (insertion, deletion, substitution).
Development of a maximum-likelihood-based single-nucleotide variant detection tool.

Main Results:

Optimized error rates: 4.9% insertion, 7.8% deletion, 5.1% substitution.
Over 99% of high-quality 2D MinION reads mapped to reference with 85% mean identity.
Single-nucleotide variant detection achieved up to 99% precision and recall.
Successfully resolved copy number variation for the CT47 gene family on human chromosome Xq24.

Conclusions:

The MinION platform, when optimized, provides high accuracy for genomic analysis.
The developed variant detection tool enhances the reliability of nanopore-based variant calling.
Long reads and accurate alignment strategies enable the resolution of previously uncharacterized genomic regions.