title: Genome compression: a novel approach for large collections.
abstract: BACKGROUND
  Genomic repositories are rapidly growing, as witnessed by the 1000 Genomes or the UK10K projects. Hence, compression of multiple genomes of the same species has become an active research area in the past years. The well-known large redundancy in human sequences is not easy to exploit because of huge memory requirements from traditional compression algorithms.
  
  
  RESULTS
  We show how to obtain several times higher compression ratio than of the best reported results, on two large genome collections (1092 human and 775 plant genomes). Our inputs are variant call format files restricted to their essential fields. More precisely, our novel Ziv-Lempel-style compression algorithm squeezes a single human genome to ∼400 KB. The key to high compression is to look for similarities across the whole collection, not just against one reference sequence, what is typical for existing solutions.
  
  
  BACKGROUND
  http://sun.aei.polsl.pl/tgc (also as Supplementary Material) under a free license. Supplementary data: Supplementary data are available at Bioinformatics online.
authors: Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland and Computer Engineering Department, Technical University of Łódź, Al. Politechniki 11, 90-924 Łódź, Poland.
authors: Sebastian
authors: S
authors: Deorowicz
authors: Agnieszka
authors: A
authors: Danek
authors: Szymon
authors: S
authors: Grabowski
mesh_terms: D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics*; D001483:Base Sequence; D044962:Data Compression / Q000379:methods*; D030541:Databases, Genetic; D015894:Genome, Human; D018745:Genome, Plant; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D017422:Sequence Analysis, DNA / Q000379:methods