R in DNA Barcoding

  • Asim Kumar Mahadani
  • Pradosh Mahadani
  • Goutam Sanyal


DNA barcoding bloomed as a routine application in biodiversity assessment and species identification. Several improvements have occurred in the DNA sequence analysis approaches. Recently, R language and environment for statistical computing and graphics emerged as powerful tool in sequence and phylogenetic analysis. Bioinformaticians have written several specialized packages for R to provide reading and writing data and manipulating sequence analysis, as well as several advanced DNA barcode sequence-based analysis. SeqinR package is mainly used to retrieve and analyze biological sequences, and APE packages are for construction of phylogenetic and evolutionary tree-based molecular data. However, SPIDER and BarcodingR packages are completely devoted to analyze for DNA barcode sequences. The purpose of this chapter is to provide a quick reference for DNA barcode associate researcher in sequence and phylogenetic analysis.


R language DNA barcoding APE SPIDER BarcodingR 


  1. Brown SDJ, Collins RA, Boyer S, Lefort M-C, Malumbres-Olarte J, Vink CJ, Cruickshank RH (2012) Spider: an R package for the analysis of species identity and evolution, with particular reference to DNA barcoding. Mol Ecol Resour 12:562–565CrossRefPubMedGoogle Scholar
  2. Charif D, Lobry JR (2007) SeqinR 1.0-2: a contributed package to the R project for statistical computing devoted to biological sequences retrieval and analysis. In: Structural approaches to sequence evolution: molecules, networks, populations. Springer Verlag, New York, pp 207–232CrossRefGoogle Scholar
  3. Felsenstein J (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 17:368–376CrossRefPubMedGoogle Scholar
  4. Jombart T (2008) Adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24(11):1403–1405CrossRefPubMedGoogle Scholar
  5. Paradis E, Claude J, Strimmer K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20:289–290CrossRefGoogle Scholar
  6. R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Scholar
  7. Ratnasingham S, Hebert PDN (2007) BOLD: the barcode of life data system. Mol Ecol Notes 355–364.
  8. Saitou N, Nei M (1987) The neighbor-joining method—a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425PubMedPubMedCentralGoogle Scholar
  9. Tamura K, Nei M (1993) Estimation of the number of nucleotide sub-stitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol 10(3):512–526PubMedGoogle Scholar
  10. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG (1997) The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25:4876–4882CrossRefPubMedPubMedCentralGoogle Scholar
  11. Zhang A-b, Hao M-d, Yang C-q, Shi Z-y (2016) BarcodingR: an integrated r package for species identification using DNA barcodes. Methods Ecol Evol.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Asim Kumar Mahadani
    • 1
  • Pradosh Mahadani
    • 2
  • Goutam Sanyal
    • 1
  1. 1.Department of Computer Science & EngineeringNational Institute of TechnologyDurgapurIndia
  2. 2.Crop Improvement DivisionICAR-National Rice Research InstituteCuttackIndia

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