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Silencing the Spark: CRISPR/Cas9 Genome Editing in Weakly Electric Fish

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Published on: October 27, 2019

Genetically improved BarraCUDA.

W B Langdon¹, Brian Yee Hong Lam²

¹Department of Computer Science, University College London, Gower Street, London, WC1E 6BT UK.

|August 9, 2017

Summary

This summary is machine-generated.

Genetic Improvement optimized BarraCUDA, a DNA sequencing alignment tool, making it significantly faster and more accurate. This enhanced open-source program accelerates next-generation sequencing analysis on GPUs.

Keywords:

Double-ended DNA sequence GPGPU Genetic improvement Nextgen NGS Parallel computing

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

BarraCUDA is an open-source C program utilizing the BWA algorithm with nVidia CUDA for parallel alignment of next-generation DNA sequences.
The program's source code underwent optimization using a "Genetic Improvement" approach.

Purpose of the Study:

To evaluate the performance enhancements of BarraCUDA after source code optimization using Genetic Improvement.
To compare the speed and accuracy of the optimized BarraCUDA against its original version and other standard tools.

Main Methods:

Implementation of Genetic Improvement techniques to optimize the BarraCUDA source code.
Benchmarking the performance of the genetically improved (GI) BarraCUDA using paired-end reads from The 1000 Genomes Project and the BioPlanet.com GCAT alignment benchmark.
Comparison of alignment speeds using a K80 Tesla GPU against a 12-core server running the standard BWA algorithm.

Main Results:

The genetically improved BarraCUDA demonstrated up to three times faster performance on short paired-end reads.
The GI code achieved 60% greater accuracy on the BioPlanet.com GCAT alignment benchmark.
BarraCUDA running on a single K80 Tesla GPU achieved alignment speeds up to ten times faster than BWA on a 12-core server.

Conclusions:

The significant speed improvements of the genetically improved BarraCUDA led to its adoption.
The optimized version has been consistently downloaded from SourceForge for over 12 months, indicating its utility and acceptance in the research community.