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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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Updated: May 26, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow.

Ali Hamraoui^1,2, Laurent Jourdren¹, Morgane Thomas-Chollier^1,2

¹GenomiqueENS, Institut de Biologie de l'ENS (IBENS), Département de biologie, École normale supérieure, CNRS, INSERM, Université PSL, Paris 75005, France.

Bioinformatics (Oxford, England)

|February 22, 2025

Summary

This summary is machine-generated.

Researchers developed AsaruSim, a novel workflow for simulating single-cell long-read Nanopore sequencing data. This tool aids in evaluating and optimizing methods for isoform detection in complex single-cell transcriptomics studies.

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Last Updated: May 26, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

Nanopore DNA Sequencing for Metagenomic Soil Analysis

Nanopore DNA Sequencing for Metagenomic Soil Analysis

Published on: December 14, 2017

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Long-read sequencing (Oxford Nanopore) combined with single-cell RNA sequencing (scRNAseq) offers deep transcriptomic insights, including full-length cDNA isoform detection.
Current simulation tools inadequately capture the complexities of scRNAseq long-read data, hindering method development.
Advanced simulation is crucial for validating and improving isoform detection algorithms in single-cell long-read studies.

Purpose of the Study:

To develop a sophisticated simulation tool for single-cell long-read Nanopore datasets.
To address the limitations of existing tools in mimicking real experimental data complexities.
To facilitate the advancement of isoform detection methods for single-cell genomics.

Main Methods:

AsaruSim workflow simulates synthetic single-cell long-read Nanopore data.
Includes steps for synthetic count matrix creation, perfect read generation, optional PCR amplification, and sequencing error simulation.
Incorporates comprehensive quality control reporting.

Main Results:

AsaruSim accurately mimics experimental read characteristics, as demonstrated on human peripheral blood mononuclear cell data.
The workflow effectively simulates key features of real single-cell long-read Nanopore datasets.
Validated the tool's ability to reproduce experimental data properties.

Conclusions:

AsaruSim provides a valuable resource for the single-cell genomics community.
Enables robust evaluation and optimization of isoform detection tools for long-read scRNAseq data.
Facilitates further research in transcriptomic complexity analysis at the single-cell level.