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appreci8: a pipeline for precise variant calling integrating 8 tools.

Bioinformatics. 2018 12 15;34(24):4205-4212

Authors: Sandmann S, Karimi M, de Graaf AO, Rohde C, Göllner S, Varghese J, Ernsting J, Walldin G, van der Reijden BA, Müller-Tidow C, Malcovati L, Hellström-Lindberg E, Jansen JH, Dugas M

Abstract
Motivation: The application of next-generation sequencing in research and particularly in clinical routine requires valid variant calling results. However, evaluation of several commonly used tools has pointed out that not a single tool meets this requirement. False positive as well as false negative calls necessitate additional experiments and extensive manual work. Intelligent combination and output filtration of different tools could significantly improve the current situation.
Results: We developed appreci8, an automatic variant calling pipeline for calling single nucleotide variants and short indels by combining and filtering the output of eight open-source variant calling tools, based on a novel artifact- and polymorphism score. Appreci8 was trained on two data sets from patients with myelodysplastic syndrome, covering 165 Illumina samples. Subsequently, appreci8's performance was tested on five independent data sets, covering 513 samples. Variation in sequencing platform, target region and disease entity was considered. All calls were validated by re-sequencing on the same platform, a different platform or expert-based review. Sensitivity of appreci8 ranged between 0.93 and 1.00, while positive predictive value ranged between 0.65 and 1.00. In all cases, appreci8 showed superior performance compared to any evaluated alternative approach.
Availability and implementation: Appreci8 is freely available at https://hub.docker.com/r/wwuimi/appreci8/. Sequencing data (BAM files) of the 678 patients analyzed with appreci8 have been deposited into the NCBI Sequence Read Archive (BioProjectID: 388411; https://www.ncbi.nlm.nih.gov/bioproject/PRJNA388411).
Supplementary information: Supplementary data are available at Bioinformatics online.

PMID: 29945233 [PubMed - indexed for MEDLINE]