title: SAG-QC: quality control of single amplified genome information by subtracting non-target sequences based on sequence compositions.
abstract: BACKGROUND
  Whole genome amplification techniques have enabled the analysis of unexplored genomic information by sequencing of single-amplified genomes (SAGs). Whole genome amplification of single bacteria is currently challenging because contamination often occurs in experimental processes. Thus, to increase the confidence in the analyses of sequenced SAGs, bioinformatics approaches that identify and exclude non-target sequences from SAGs are required. Since currently reported approaches utilize sequence information in public databases, they have limitations when new strains are the targets of interest. Here, we developed a software SAG-QC that identify and exclude non-target sequences independent of database.
  
  
  RESULTS
  In our method, "no template control" sequences acquired during WGA were used. We calculated the probability that a sequence was derived from contaminants by comparing k-mer compositions with the no template control sequences. Based on the results of tests using simulated SAG datasets, the accuracy of our method for predicting non-target sequences was higher than that of currently reported techniques. Subsequently, we applied our tool to actual SAG datasets and evaluated the accuracy of the predictions.
  
  
  CONCLUSIONS
  Our method works independently of public sequence information for distinguishing SAGs from non-target sequences. This method will be effective when employed against SAG sequences of unexplored strains and we anticipate that it will contribute to the correct interpretation of SAGs.
authors.affiliation: Department of Life Science & Medical Bioscience, Graduate School of Advanced Science & Engineering, Waseda University, 3-4-1 Okubo, Shinjuku, Tokyo, 169-8555, Japan.|Computational Bio-Big Data Open Innovation Lab., National Institute of Advanced Science and Technology, 3-4-1 Okubo, Shinjuku, Tokyo, 169-0072, Japan.
authors.forename: Toru
authors.initials: T
authors.lastname: Maruyama
authors.affiliation: Institute for Nanoscience and Nanotechnology, Waseda University, 513 Waseda-Tsurumaki-cho, Shinjuku, Tokyo, 162-0041, Japan.
authors.forename: Tetsushi
authors.initials: T
authors.lastname: Mori
authors.affiliation: Department of Life Science & Medical Bioscience, Graduate School of Advanced Science & Engineering, Waseda University, 3-4-1 Okubo, Shinjuku, Tokyo, 169-8555, Japan.
authors.forename: Keisuke
authors.initials: K
authors.lastname: Yamagishi
authors.affiliation: Department of Life Science & Medical Bioscience, Graduate School of Advanced Science & Engineering, Waseda University, 3-4-1 Okubo, Shinjuku, Tokyo, 169-8555, Japan. haruko-takeyama@waseda.jp.|Computational Bio-Big Data Open Innovation Lab., National Institute of Advanced Science and Technology, 3-4-1 Okubo, Shinjuku, Tokyo, 169-0072, Japan. haruko-takeyama@waseda.jp.|Institute for Nanoscience and Nanotechnology, Waseda University, 513 Waseda-Tsurumaki-cho, Shinjuku, Tokyo, 162-0041, Japan. haruko-takeyama@waseda.jp.
authors.forename: Haruko
authors.identifier: http://orcid.org/0000-0002-2058-8185
authors.initials: H
authors.lastname: Takeyama
mesh_terms: D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics; D056726:Genetic Association Studies; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods*; D008962:Models, Theoretical; D011786:Quality Control; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D017422:Sequence Analysis, DNA; D012984:Software
chemical_list: D012336:RNA, Ribosomal, 16S
keywords: Decontamination; GUI software; Single-cell genomics