title: Short clones or long clones? A simulation study on the use of paired reads in metagenomics.
abstract: BACKGROUND
  Metagenomics is the study of environmental samples using sequencing. Rapid advances in sequencing technology are fueling a vast increase in the number and scope of metagenomics projects. Most metagenome sequencing projects so far have been based on Sanger or Roche-454 sequencing, as only these technologies provide long enough reads, while Illumina sequencing has not been considered suitable for metagenomic studies due to a short read length of only 35 bp. However, now that reads of length 75 bp can be sequenced in pairs, Illumina sequencing has become a viable option for metagenome studies.
  
  
  RESULTS
  This paper addresses the problem of taxonomical analysis of paired reads. We describe a new feature of our metagenome analysis software MEGAN that allows one to process sequencing reads in pairs and makes assignments of such reads based on the combined bit scores of their matches to reference sequences. Using this new software in a simulation study, we investigate the use of Illumina paired-sequencing in taxonomical analysis and compare the performance of single reads, short clones and long clones. In addition, we also compare against simulated Roche-454 sequencing runs.
  
  
  CONCLUSIONS
  This work shows that paired reads perform better than single reads, as expected, but also, perhaps slightly less obviously, that long clones allow more specific assignments than short ones. A new version of the program MEGAN that explicitly takes paired reads into account is available from our website.
authors.affiliation: Center for Bioinformatics ZBIT, Tübingen University, Sand 14, 72076 Tübingen, Germany. mitra@informatik.uni-tuebingen.de
authors.forename: Suparna
authors.initials: S
authors.lastname: Mitra
authors.forename: Max
authors.initials: M
authors.lastname: Schubach
authors.forename: Daniel H
authors.initials: DH
authors.lastname: Huson
mesh_terms: D001483:Base Sequence; D030541:Databases, Genetic; D016678:Genome; D056186:Metagenomics / Q000379:methods*; D010802:Phylogeny; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software