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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: Mar 3, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

MarDRe: efficient MapReduce-based removal of duplicate DNA reads in the cloud.

Roberto R Expósito¹, Jorge Veiga¹, Jorge González-Domínguez¹

¹Grupo de Arquitectura de Computadores, Universidade da Coruña, Campus de A Coruña, A Coruña 15071, Spain.

Bioinformatics (Oxford, England)

|May 6, 2017

Summary

MarDRe is a new tool for removing duplicate DNA sequences from large datasets. It uses cloud computing and Big Data technologies to process data faster than existing methods.

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Last Updated: Mar 3, 2026

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

High-throughput sequencing generates massive datasets.
Efficiently processing and cleaning these datasets is crucial for downstream analysis.
Duplicate and near-duplicate reads can skew results in genomic studies.

Purpose of the Study:

To introduce MarDRe, a novel de novo tool for duplicate and near-duplicate read removal.
To leverage Big Data technologies for scalable and efficient data processing.
To provide a cloud-ready solution for FASTQ/FASTA dataset cleaning.

Main Methods:

MarDRe utilizes the MapReduce programming model.
It is built on the Apache Hadoop framework for distributed computing.
The tool is implemented in Java for cross-platform compatibility.

Main Results:

MarDRe processes single- and paired-end reads from FASTQ/FASTA files.
The tool is cloud-ready and designed for cloud-based infrastructures.
On a 16-node EC2 cluster, MarDRe demonstrated up to 8.52x speed improvement over a state-of-the-art tool.

Conclusions:

MarDRe offers a fast and scalable solution for duplicate read removal in Big Data genomics.
Its cloud-native design facilitates deployment on modern computational platforms.
The tool enhances the efficiency of genomic data preprocessing pipelines.