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Related Experiment Video

Updated: Feb 26, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

FSG: Fast String Graph Construction for De Novo Assembly.

Paola Bonizzoni¹, Gianluca Della Vedova¹, Yuri Pirola¹

¹Dipartimento di Informatica Sistemistica e Comunicazione, Università degli Studi di Milano-Bicocca , Milan, Italy .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|July 18, 2017

Summary

This summary is machine-generated.

A new method computes string graphs using the FM-index, accelerating de novo genome assembly. This fast string graph (FSG) approach is faster than existing methods while using less memory.

Keywords:

Burrows and Wheeler Transform genome assembly string graph

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Last Updated: Feb 26, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

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Published on: August 20, 2021

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A Customizable Protocol for String Assembly gRNA Cloning STAgR

A Customizable Protocol for String Assembly gRNA Cloning STAgR

Published on: December 26, 2018

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

String graphs are crucial for de novo genome assembly using the overlap-layout-consensus paradigm.
Existing methods for string graph construction can be computationally intensive.

Purpose of the Study:

To develop a novel and efficient algorithm for constructing string graphs.
To improve the speed and memory efficiency of de novo genome assemblers.

Main Methods:

Utilized the FM-index and Burrows-Wheeler Transform for string graph computation.
Developed a standalone module for string graph construction without direct read access.
Integrated the new module into the string graph assembler (SGA).

Main Results:

The new fast string graph (FSG) method significantly outperforms SGA in speed.
FSG maintains moderate main memory usage.
Demonstrated practical advantages of FSG when run on multiple threads.
Analyzed the impact of coverage rates on algorithm performance.

Conclusions:

The FM-index based approach offers a faster and memory-efficient alternative for string graph construction.
FSG presents a significant advancement for de novo genome assembly pipelines.
The method shows promise for scalable and efficient genomic data analysis.