title: QualComp: a new lossy compressor for quality scores based on rate distortion theory.
abstract: BACKGROUND
  Next Generation Sequencing technologies have revolutionized many fields in biology by reducing the time and cost required for sequencing. As a result, large amounts of sequencing data are being generated. A typical sequencing data file may occupy tens or even hundreds of gigabytes of disk space, prohibitively large for many users. This data consists of both the nucleotide sequences and per-base quality scores that indicate the level of confidence in the readout of these sequences. Quality scores account for about half of the required disk space in the commonly used FASTQ format (before compression), and therefore the compression of the quality scores can significantly reduce storage requirements and speed up analysis and transmission of sequencing data.
  
  
  RESULTS
  In this paper, we present a new scheme for the lossy compression of the quality scores, to address the problem of storage. Our framework allows the user to specify the rate (bits per quality score) prior to compression, independent of the data to be compressed. Our algorithm can work at any rate, unlike other lossy compression algorithms. We envisage our algorithm as being part of a more general compression scheme that works with the entire FASTQ file. Numerical experiments show that we can achieve a better mean squared error (MSE) for small rates (bits per quality score) than other lossy compression schemes. For the organism PhiX, whose assembled genome is known and assumed to be correct, we show that it is possible to achieve a significant reduction in size with little compromise in performance on downstream applications (e.g., alignment).
  
  
  CONCLUSIONS
  QualComp is an open source software package, written in C and freely available for download at https://sourceforge.net/projects/qualcomp.
authors.affiliation: Department of Electrical Engineering, Stanford University, Stanford, CA, USA. iochoa@stanford.edu
authors.forename: Idoia
authors.initials: I
authors.lastname: Ochoa
authors.forename: Himanshu
authors.initials: H
authors.lastname: Asnani
authors.forename: Dinesh
authors.initials: D
authors.lastname: Bharadia
authors.forename: Mainak
authors.initials: M
authors.lastname: Chowdhury
authors.forename: Tsachy
authors.initials: T
authors.lastname: Weissman
authors.forename: Golan
authors.initials: G
authors.lastname: Yona
mesh_terms: D000465:Algorithms; D000818:Animals; D044962:Data Compression / Q000379:methods*; D016678:Genome; D023281:Genomics; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D051379:Mice; D020641:Polymorphism, Single Nucleotide; D012984:Software