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Related Experiment Video

Updated: May 9, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

Optimal assembly for high throughput shotgun sequencing.

Guy Bresler¹, Ma'ayan Bresler, David Tse

¹Department of EECS, UC Berkeley, California, USA. gbresler@eecs.berkeley.edu.

BMC Bioinformatics

|August 2, 2013

Summary

This summary is machine-generated.

This study introduces optimal assembly algorithms for shotgun sequencing, establishing minimum read length and coverage for complete genome reconstruction. The de Bruijn graph approach achieves near-optimal results for diverse genomes.

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Last Updated: May 9, 2026

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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

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Shotgun sequencing is a common method for genome assembly.
Complete genome reconstruction requires overcoming challenges posed by repetitive DNA sequences.
Existing assembly algorithms may not guarantee complete reconstruction.

Purpose of the Study:

To develop a framework for designing optimal assembly algorithms for shotgun sequencing.
To establish theoretical lower bounds for read length and coverage depth necessary for complete genome reconstruction.
To design an algorithm that approaches these theoretical bounds.

Main Methods:

Derivation of lower bounds based on genome repeat statistics.
Development of a de Bruijn graph-based assembly algorithm.
Analysis of necessary and sufficient conditions for reconstruction.

Main Results:

A framework for optimal assembly algorithm design is presented.
Theoretical lower bounds for read length and coverage were derived.
A de Bruijn graph algorithm demonstrated near-optimal performance on various datasets, including GAGE.
Identified conditions for reconstruction analogous to Sequencing by Hybridization.

Conclusions:

The proposed framework and algorithm provide a robust approach to complete genome reconstruction.
The derived conditions offer theoretical insights into the requirements for successful genome assembly.
The algorithm's performance validates the theoretical findings across diverse genomic datasets.