title: Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in whole-exome sequencing data.
abstract: BACKGROUND
  Detecting somatic mutations in whole exome sequencing data of cancer samples has become a popular approach for profiling cancer development, progression and chemotherapy resistance. Several studies have proposed software packages, filters and parametrizations. However, many research groups reported low concordance among different methods. We aimed to develop a pipeline which detects a wide range of single nucleotide mutations with high validation rates. We combined two standard tools - Genome Analysis Toolkit (GATK) and MuTect - to create the GATK-LODNmethod. As proof of principle, we applied our pipeline to exome sequencing data of hematological (Acute Myeloid and Acute Lymphoblastic Leukemias) and solid (Gastrointestinal Stromal Tumor and Lung Adenocarcinoma) tumors. We performed experiments on simulated data to test the sensitivity and specificity of our pipeline.
  
  
  RESULTS
  The software MuTect presented the highest validation rate (90 %) for mutation detection, but limited number of somatic mutations detected. The GATK detected a high number of mutations but with low specificity. The GATK-LODNincreased the performance of the GATK variant detection (from 5 of 14 to 3 of 4 confirmed variants), while preserving mutations not detected by MuTect. However, GATK-LODNfiltered more variants in the hematological samples than in the solid tumors. Experiments in simulated data demonstrated that GATK-LODNincreased both specificity and sensitivity of GATK results.
  
  
  CONCLUSIONS
  We presented a pipeline that detects a wide range of somatic single nucleotide variants, with good validation rates, from exome sequencing data of cancer samples. We also showed the advantage of combining standard algorithms to create the GATK-LODNmethod, that increased specificity and sensitivity of GATK results. This pipeline can be helpful in discovery studies aimed to profile the somatic mutational landscape of cancer genomes.
authors.affiliation: Department of Physics and Astronomy, University of Bologna, Bologna, Italy.|CAPES Foundation, Ministry of Education of Brazil, Brasília, DF, Brazil.
authors.forename: Ítalo Faria
authors.initials: ÍF
authors.lastname: do Valle
authors.affiliation: Department of Physics and Astronomy, University of Bologna, Bologna, Italy.
authors.forename: Enrico
authors.initials: E
authors.lastname: Giampieri
authors.affiliation: Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
authors.forename: Giorgia
authors.initials: G
authors.lastname: Simonetti
authors.affiliation: Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
authors.forename: Antonella
authors.initials: A
authors.lastname: Padella
authors.affiliation: Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Manfrini
authors.affiliation: Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
authors.forename: Anna
authors.initials: A
authors.lastname: Ferrari
authors.affiliation: Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
authors.forename: Cristina
authors.initials: C
authors.lastname: Papayannidis
authors.affiliation: Department of Physics and Astronomy, University of Bologna, Bologna, Italy.
authors.forename: Isabella
authors.initials: I
authors.lastname: Zironi
authors.affiliation: Department of Biotechnology, University of Verona, Verona, Italy.
authors.forename: Marianna
authors.initials: M
authors.lastname: Garonzi
authors.affiliation: Unit of Blood Diseases and Stem Cell Transplantation, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
authors.forename: Simona
authors.initials: S
authors.lastname: Bernardi
authors.affiliation: Department of Biotechnology, University of Verona, Verona, Italy.|Personal Genomics, Verona, Italy.
authors.forename: Massimo
authors.initials: M
authors.lastname: Delledonne
authors.affiliation: Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Martinelli
authors.affiliation: Department of Physics and Astronomy, University of Bologna, Bologna, Italy. daniel.remondini@unibo.it.
authors.forename: Daniel
authors.initials: D
authors.lastname: Remondini
authors.affiliation: Department of Physics and Astronomy, University of Bologna, Bologna, Italy.
authors.forename: Gastone
authors.initials: G
authors.lastname: Castellani
mesh_terms: D000465:Algorithms; D059472:Exome; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D009154:Mutation; D009369:Neoplasms / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D012680:Sensitivity and Specificity; D012984:Software
keywords: Cancer; Somatic single nucleotide variants; Whole exome sequencing