We have developed a new method for frameshift detection, a combination of ab initio and alignment-based algorithms, that can serve as a useful tool for sequencing quality control in the next generation sequencing. We evaluated the method's accuracy on test sets of annotated genomic sequences with artificial frameshifts in protein coding regions. These tests have shown that the new method performs comparably to the earlier developed FrameD. On the sets of sequences produced by 454 pyrosequencing with sequence errors recovered by Sanger re-sequencing the accuracy of the method was shown to hold at the same level.

Original languageEnglish
Pages (from-to)458-477
Number of pages20
JournalInternational Journal of Bioinformatics Research and Applications
Volume5
Issue number4
DOIs
StatePublished - Jul 2009

    Research areas

  • Frameshift, Genomics, Hidden Markov model, HMM, Machine learning, Markov chains, Pyrosequencing, Sensitivity, Sn, Sp, Specificity

    Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Clinical Biochemistry
  • Health Information Management

ID: 90033587