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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: Feb 22, 2026

Simultaneous Mapping and Quantitation of Ribonucleotides in Human Mitochondrial DNA

Simultaneous Mapping and Quantitation of Ribonucleotides in Human Mitochondrial DNA

Published on: November 14, 2017

mmquant: how to count multi-mapping reads?

Matthias Zytnicki¹

¹MIAT, Toulouse INRA, BP 52627, Castanet-Tolosan cedex, 31326, France. matthias.zytnicki@inra.fr.

BMC Bioinformatics

|September 17, 2017

Summary

This summary is machine-generated.

This study introduces mmquant, a new tool for RNA sequencing analysis. It accurately quantifies gene expression, even for duplicated genes, overcoming limitations of current methods.

Keywords:

Multi-mapping reads Quantification RNA-Seq

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Last Updated: Feb 22, 2026

Simultaneous Mapping and Quantitation of Ribonucleotides in Human Mitochondrial DNA

Simultaneous Mapping and Quantitation of Ribonucleotides in Human Mitochondrial DNA

Published on: November 14, 2017

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Area of Science:

Bioinformatics
Genomics
Molecular Biology

Background:

RNA sequencing (RNA-Seq) is a standard method for gene transcription analysis.
Current RNA-Seq methods struggle to accurately quantify expression of duplicated genes.
Existing strategies for handling duplicated genes introduce biases in expression estimates.

Purpose of the Study:

To develop a novel computational tool, mmquant, for accurate gene expression quantification.
To address the challenge of estimating expression for duplicated genes in RNA-Seq data.
To provide an unbiased method for handling multi-mapping reads.

Main Methods:

mmquant identifies duplicated genes by detecting reads mapping to multiple positions.
The tool merges ambiguously mapping reads to create 'merged genes'.
Gene counts are computed based on both original and merged gene information.

Main Results:

mmquant accurately computes gene expression, including duplicated genes.
The tool effectively handles multi-mapping reads, a common challenge in RNA-Seq.
mmquant provides unbiased quantification where previous methods failed.

Conclusions:

mmquant offers an unbiased approach to gene expression quantification.
It serves as a direct replacement for commonly used tools like htseq-count and featureCounts.
This tool improves the accuracy of RNA-Seq analysis for genes with duplication.