title: Enhancing the detection of barcoded reads in high throughput DNA sequencing data by controlling the false discovery rate.
abstract: BACKGROUND
  DNA barcodes are short unique sequences used to label DNA or RNA-derived samples in multiplexed deep sequencing experiments. During the demultiplexing step, barcodes must be detected and their position identified. In some cases (e.g., with PacBio SMRT), the position of the barcode and DNA context is not well defined. Many reads start inside the genomic insert so that adjacent primers might be missed. The matter is further complicated by coincidental similarities between barcode sequences and reference DNA. Therefore, a robust strategy is required in order to detect barcoded reads and avoid a large number of false positives or negatives.For mass inference problems such as this one, false discovery rate (FDR) methods are powerful and balanced solutions. Since existing FDR methods cannot be applied to this particular problem, we present an adapted FDR method that is suitable for the detection of barcoded reads as well as suggest possible improvements.
  
  
  RESULTS
  In our analysis, barcode sequences showed high rates of coincidental similarities with the Mus musculus reference DNA. This problem became more acute when the length of the barcode sequence decreased and the number of barcodes in the set increased. The method presented in this paper controls the tail area-based false discovery rate to distinguish between barcoded and unbarcoded reads. This method helps to establish the highest acceptable minimal distance between reads and barcode sequences. In a proof of concept experiment we correctly detected barcodes in 83% of the reads with a precision of 89%. Sensitivity improved to 99% at 99% precision when the adjacent primer sequence was incorporated in the analysis. The analysis was further improved using a paired end strategy. Following an analysis of the data for sequence variants induced in the Atp1a1 gene of C57BL/6 murine melanocytes by ultraviolet light and conferring resistance to ouabain, we found no evidence of cross-contamination of DNA material between samples.
  
  
  CONCLUSIONS
  Our method offers a proper quantitative treatment of the problem of detecting barcoded reads in a noisy sequencing environment. It is based on the false discovery rate statistics that allows a proper trade-off between sensitivity and precision to be chosen.
authors.affiliation: Max Planck Research Group: Neuroanatomy & Connectivity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. tibu@cbs.mpg.de.
authors.forename: Tilo
authors.initials: T
authors.lastname: Buschmann
authors.forename: Rong
authors.initials: R
authors.lastname: Zhang
authors.forename: Douglas E
authors.initials: DE
authors.lastname: Brash
authors.forename: Leonid V
authors.initials: LV
authors.lastname: Bystrykh
mesh_terms: D000818:Animals; D004247:DNA / Q000235:genetics*; D059018:DNA Contamination; D017931:DNA Primers / Q000235:genetics; D005189:False Positive Reactions; D016678:Genome / Q000235:genetics; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods* / Q000592:standards; D051379:Mice; D012015:Reference Standards; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000592:standards; D000254:Sodium-Potassium-Exchanging ATPase / Q000235:genetics
chemical_list: D017931:DNA Primers; D004247:DNA; C497344:Atp1a1 protein, mouse; D000254:Sodium-Potassium-Exchanging ATPase
references.citation: J Comput Biol. 2000;7(3-4):503-19
references.pmid: 11108476
references.citation: Nucleic Acids Res. 2007;35(15):e97
references.pmid: 17670798
references.citation: BMC Bioinformatics. 2013 Sep 11;14:272
references.pmid: 24021088
references.citation: Bioinformatics. 2013 Jan 1;29(1):119-21
references.pmid: 23129296
references.citation: Bioinformatics. 2010 Mar 1;26(5):589-95
references.pmid: 20080505
references.citation: Genome Biol. 2009;10(10):R108
references.pmid: 19814784
references.citation: Mutat Res. 1978 Jul;51(1):85-98
references.pmid: 149923
references.citation: Bioinformatics. 2012 Jun 1;28(11):1533-5
references.pmid: 22508794
references.citation: Am J Med Genet B Neuropsychiatr Genet. 2008 Jul 5;147B(5):637-44
references.pmid: 18092307
references.citation: Science. 2009 Jan 2;323(5910):133-8
references.pmid: 19023044
references.citation: Cold Spring Harb Protoc. 2010 Jun;2010(6):pdb.prot5448
references.pmid: 20516186
references.citation: Bioessays. 2010 Jun;32(6):524-36
references.pmid: 20486139
references.citation: J Chem Inf Comput Sci. 2003 Nov-Dec;43(6):2014-8
references.pmid: 14632452
references.citation: Bioinformatics. 2003 Feb 12;19(3):368-75
references.pmid: 12584122
references.citation: PLoS One. 2012;7(5):e36852
references.pmid: 22615825
references.citation: Nucleic Acids Res. 2012 Jul;40(12):e94
references.pmid: 22434876
references.citation: Nat Methods. 2008 Oct;5(10):887-93
references.pmid: 18794863
references.citation: Bioinformatics. 2012 Feb 15;28(4):593-4
references.pmid: 22199392
references.citation: Nat Methods. 2011 Nov 27;9(1):78-80
references.pmid: 22120468
references.citation: BMC Genomics. 2012 Jul 24;13:341
references.pmid: 22827831
references.citation: Bioinformatics. 2009 Aug 15;25(16):2078-9
references.pmid: 19505943
references.citation: Nat Methods. 2010 Feb;7(2):111-8
references.pmid: 20111037
references.citation: Nucleic Acids Res. 2007;35(19):e130
references.pmid: 17932070
references.citation: Nat Methods. 2013 Jun;10(6):563-9
references.pmid: 23644548
references.citation: BMC Bioinformatics. 2008 Jul 09;9:303
references.pmid: 18613966
references.citation: BMC Bioinformatics. 2008 Mar 26;9:167
references.pmid: 18366790