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Dataset Information

Compression of genomic sequencing reads via hash-based reordering: algorithm and analysis.


ABSTRACT:

Motivation

New Generation Sequencing (NGS) technologies for genome sequencing produce large amounts of short genomic reads per experiment, which are highly redundant and compressible. However, general-purpose compressors are unable to exploit this redundancy due to the special structure present in the data.

Results

We present a new algorithm for compressing reads both with and without preserving the read order. In both cases, it achieves 1.4×-2× compression gain over state-of-the-art read compression tools for datasets containing as many as 3 billion Illumina reads. Our tool is based on the idea of approximately reordering the reads according to their position in the genome using hashed substring indices. We also present a systematic analysis of the read compression problem

SUBMITTER: Chandak S 

PROVIDER: S-EPMC5860611 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature