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Updated: Dec 20, 2025

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

ENANO: Encoder for NANOpore FASTQ files.

Guillermo Dufort Y Álvarez¹, Gadiel Seroussi^1,2, Pablo Smircich^3,4

¹Facultad de Ingeniería, Universidad de la República, Montevideo 11300, Uruguay.

Bioinformatics (Oxford, England)

|May 30, 2020

Summary

This summary is machine-generated.

ENANO is a new lossless compression algorithm for nanopore sequencing FASTQ files. It significantly improves compression of genomic data, outperforming existing tools like SPRING and pigz.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Genomic data generation is rapidly increasing, necessitating efficient processing, storage, and transmission solutions.
Existing compression tools primarily target short-read sequencing data, leaving a gap for emerging nanopore technologies.
Nanopore sequencing offers advantages like larger reads, lower costs, and portability, driving its adoption and increasing the need for specialized compression.

Purpose of the Study:

To introduce ENANO (Encoder for NANOpore), a novel lossless compression algorithm specifically designed for nanopore sequencing FASTQ files.
To address the growing need for efficient compression of the large volumes of data generated by nanopore sequencing.
To optimize the compression of quality scores, which constitute a significant portion of FASTQ file size.

Main Methods:

ENANO was developed as a lossless compression algorithm tailored for FASTQ files from nanopore sequencing.
The algorithm focuses on compressing quality scores, a major contributor to file size.
ENANO offers two operational modes: Maximum Compression and Fast (default), balancing compression efficiency and speed.

Main Results:

ENANO demonstrated superior compression performance across multiple nanopore datasets compared to SPRING and pigz.
The algorithm achieved an average compression improvement of over 24.7% compared to pigz and 6.3% compared to SPRING.
ENANO exhibited faster encoding (2.9x) and decoding (1.7x) speeds than SPRING, with low memory consumption (up to 0.2 GB).

Conclusions:

ENANO provides a significant advancement in lossless compression for nanopore sequencing data.
The algorithm offers a compelling solution for managing the increasing data output from nanopore sequencing technologies.
ENANO is freely available, promoting its adoption and further development in the bioinformatics community.