CALQ: compression of quality values of aligned sequencing data | Zendy

Jan Voges | Zendy; Jörn Östermann | Zendy; Mikel Hernáez | Zendy

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CALQ: compression of quality values of aligned sequencing data

Author(s) -

Jan Voges,

Jörn Östermann,

Mikel Hernáez

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx737

Subject(s) - computer science , quality (philosophy) , compression (physics) , data compression , data mining , artificial intelligence , materials science , philosophy , epistemology , composite material

Recent advancements in high-throughput sequencing technology have led to a rapid growth of genomic data. Several lossless compression schemes have been proposed for the coding of such data present in the form of raw FASTQ files and aligned SAM/BAM files. However, due to their high entropy, losslessly compressed quality values account for about 80% of the size of compressed files. For the quality values, we present a novel lossy compression scheme named CALQ. By controlling the coarseness of quality value quantization with a statistical genotyping model, we minimize the impact of the introduced distortion on downstream analyses.

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