CALQ: compression of quality values of aligned sequencing data.
Bioinformatics
; 34(10): 1650-1658, 2018 05 15.
Article
en En
| MEDLINE
| ID: mdl-29186284
ABSTRACT
Motivation 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. Results:
We analyze the performance of several lossy compressors for quality values in terms of trade-off between the achieved compressed size (in bits per quality value) and the Precision and Recall achieved after running a variant calling pipeline over sequencing data of the well-known NA12878 individual. By compressing and reconstructing quality values with CALQ, we observe a better average variant calling performance than with the original data while achieving a size reduction of about one order of magnitude with respect to the state-of-the-art lossless compressors. Furthermore, we show that CALQ performs as good as or better than the state-of-the-art lossy compressors in terms of variant calling Recall and Precision for most of the analyzed datasets. Availability and implementation CALQ is written in C ++ and can be downloaded from https//github.com/voges/calq. Contact voges@tnt.uni-hannover.de or mhernaez@illinois.edu. Supplementary information Supplementary data are available at Bioinformatics online.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Programas Informáticos
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Genómica
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Compresión de Datos
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Secuenciación de Nucleótidos de Alto Rendimiento
Tipo de estudio:
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2018
Tipo del documento:
Article
País de afiliación:
Alemania