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DIDA: Distributed Indexing Dispatched Alignment.

Hamid Mohamadi¹, Benjamin P Vandervalk², Anthony Raymond²

¹Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC, Canada; Department of Bioinformatics, University of British Columbia, Vancouver, BC, Canada; Intel Health and Life Sciences, Intel Corporation, Hillsboro, OR, US.

|April 30, 2015

Summary

This summary is machine-generated.

We introduce DIDA, a novel framework for scalable sequence alignment. DIDA distributes indexing and alignment tasks across compute nodes, improving efficiency for large datasets in bioinformatics.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

High-throughput sequencing generates vast amounts of data, challenging computational tasks like sequence alignment.
Existing indexing methods struggle with non-static targets, such as de novo assembly contigs, requiring re-computation for each run.
Scalability issues arise from numerous queries and large target datasets in sequence alignment.

Purpose of the Study:

To present DIDA, a novel distributed framework for efficient sequence alignment.
To address the computational challenges posed by large-scale sequencing data.
To provide a scalable and cost-effective solution for sequence alignment in bioinformatics.

Main Methods:

DIDA framework distributes indexing and alignment tasks into subtasks across a compute cluster.
Implements a workflow that extends beyond standard embarrassingly parallel approaches.
Designed for efficient memory usage and runtime.

Main Results:

DIDA offers a cost-effective, scalable, and modular solution for sequence alignment.
The framework improves performance in terms of memory usage and runtime.
Demonstrates applicability to large-scale alignments, including draft genomes and de novo assembly.

Conclusions:

DIDA provides a robust solution for the sequence alignment problem, particularly for dynamic and large-scale datasets.
The framework enhances computational efficiency in bioinformatics workflows.
DIDA is freely available for academic use, promoting its adoption in research.