title: A simple data-adaptive probabilistic variant calling model.
abstract: BACKGROUND
  Several sources of noise obfuscate the identification of single nucleotide variation (SNV) in next generation sequencing data. For instance, errors may be introduced during library construction and sequencing steps. In addition, the reference genome and the algorithms used for the alignment of the reads are further critical factors determining the efficacy of variant calling methods. It is crucial to account for these factors in individual sequencing experiments.
  
  
  RESULTS
  We introduce a simple data-adaptive model for variant calling. This model automatically adjusts to specific factors such as alignment errors. To achieve this, several characteristics are sampled from sites with low mismatch rates, and these are used to estimate empirical log-likelihoods. The likelihoods are then combined to a score that typically gives rise to a mixture distribution. From this we determine a decision threshold to separate potentially variant sites from the noisy background.
  
  
  CONCLUSIONS
  In simulations we show that our simple model is competitive with frequently used much more complex SNV calling algorithms in terms of sensitivity and specificity. It performs specifically well in cases with low allele frequencies. The application to next-generation sequencing data reveals stark differences of the score distributions indicating a strong influence of data specific sources of noise. The proposed model is specifically designed to adjust to these differences.
authors: Junior Research Group Transcriptome Bioinformatics, University Leipzig, Härtelstraße 16-18, Leipzig, Germany ; Interdisciplinary Center for Bioinformatics and Bioinformatics Group, University Leipzig, Härtelstraße 16-18, Leipzig, Germany ; LIFE Research Center for Civilization Diseases, University Leipzig, Härtelstraße 16-18, Leipzig, Germany.
authors: Steve
authors: S
authors: Hoffmann
authors: Interdisciplinary Center for Bioinformatics and Bioinformatics Group, University Leipzig, Härtelstraße 16-18, Leipzig, Germany ; LIFE Research Center for Civilization Diseases, University Leipzig, Härtelstraße 16-18, Leipzig, Germany ; Department of Theoretical Chemistry, University Vienna, Währinger Straße 17, Vienna, Austria ; RNomics Group, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Perlickstraße 1, Leipzig, Germany ; Max-Planck-Institute for Mathematics in the Sciences, Inselstraße 22, Leipzig, Germany ; Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, Frederiksberg, Denmark ; Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, USA.
authors: Peter F
authors: PF
authors: Stadler
authors: Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Härtelstraße 16-18, Leipzig, D-04107 Germany ; Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London W2 1PG, UK.
authors: Korbinian
authors: K
authors: Strimmer