title: Characterizing and measuring bias in sequence data.
abstract: BACKGROUND
  DNA sequencing technologies deviate from the ideal uniform distribution of reads. These biases impair scientific and medical applications. Accordingly, we have developed computational methods for discovering, describing and measuring bias.
  
  
  RESULTS
  We applied these methods to the Illumina, Ion Torrent, Pacific Biosciences and Complete Genomics sequencing platforms, using data from human and from a set of microbes with diverse base compositions. As in previous work, library construction conditions significantly influence sequencing bias. Pacific Biosciences coverage levels are the least biased, followed by Illumina, although all technologies exhibit error-rate biases in high- and low-GC regions and at long homopolymer runs. The GC-rich regions prone to low coverage include a number of human promoters, so we therefore catalog 1,000 that were exceptionally resistant to sequencing. Our results indicate that combining data from two technologies can reduce coverage bias if the biases in the component technologies are complementary and of similar magnitude. Analysis of Illumina data representing 120-fold coverage of a well-studied human sample reveals that 0.20% of the autosomal genome was covered at less than 10% of the genome-wide average. Excluding locations that were similar to known bias motifs or likely due to sample-reference variations left only 0.045% of the autosomal genome with unexplained poor coverage.
  
  
  CONCLUSIONS
  The assays presented in this paper provide a comprehensive view of sequencing bias, which can be used to drive laboratory improvements and to monitor production processes. Development guided by these assays should result in improved genome assemblies and better coverage of biologically important loci.
authors.forename: Michael G
authors.initials: MG
authors.lastname: Ross
authors.forename: Carsten
authors.initials: C
authors.lastname: Russ
authors.forename: Maura
authors.initials: M
authors.lastname: Costello
authors.forename: Andrew
authors.initials: A
authors.lastname: Hollinger
authors.forename: Niall J
authors.initials: NJ
authors.lastname: Lennon
authors.forename: Ryan
authors.initials: R
authors.lastname: Hegarty
authors.forename: Chad
authors.initials: C
authors.lastname: Nusbaum
authors.forename: David B
authors.initials: DB
authors.lastname: Jaffe
mesh_terms: D000465:Algorithms; D001482:Base Composition; D016680:Genome, Bacterial; D015894:Genome, Human; D018503:Genome, Protozoan; D023281:Genomics / Q000379:methods; D006801:Humans; D011401:Promoter Regions, Genetic; D017422:Sequence Analysis, DNA / Q000295:instrumentation / Q000379:methods*