title: ERGC: an efficient referential genome compression algorithm.
abstract: BACKGROUND
  Genome sequencing has become faster and more affordable. Consequently, the number of available complete genomic sequences is increasing rapidly. As a result, the cost to store, process, analyze and transmit the data is becoming a bottleneck for research and future medical applications. So, the need for devising efficient data compression and data reduction techniques for biological sequencing data is growing by the day. Although there exists a number of standard data compression algorithms, they are not efficient in compressing biological data. These generic algorithms do not exploit some inherent properties of the sequencing data while compressing. To exploit statistical and information-theoretic properties of genomic sequences, we need specialized compression algorithms. Five different next-generation sequencing data compression problems have been identified and studied in the literature. We propose a novel algorithm for one of these problems known as reference-based genome compression.
  
  
  RESULTS
  We have done extensive experiments using five real sequencing datasets. The results on real genomes show that our proposed algorithm is indeed competitive and performs better than the best known algorithms for this problem. It achieves compression ratios that are better than those of the currently best performing algorithms. The time to compress and decompress the whole genome is also very promising.
  
  
  METHODS
  The implementations are freely available for non-commercial purposes. They can be downloaded from http://engr.uconn.edu/∼rajasek/ERGC.zip.
  
  
  BACKGROUND
  rajasek@engr.uconn.edu.
authors.affiliation: Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA.
authors.forename: Subrata
authors.initials: S
authors.lastname: Saha
authors.affiliation: Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA.
authors.forename: Sanguthevar
authors.initials: S
authors.lastname: Rajasekaran
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping; D044962:Data Compression / Q000379:methods*; D016208:Databases, Factual; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D016247:Information Storage and Retrieval; D017422:Sequence Analysis, DNA / Q000379:methods*