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.

Appreci8: A pipeline for precise variant calling integrating 8 tools

Malcovati L.;
2018-01-01

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.
2018
Information Technology & Communications Systems
Medical Research, General Topics covers a wide array of topics in medical and biomedical research, with a specific emphasis on human disease, human tissues, and all levels of research into the pathogenesis of clinically significant conditions. Specific medical fields that are characterized by the inclusion of material from several other specializations are also covered here; these include general and internal medicine, tropical medicine, pediatrics, gerontology, epidemiology, and public health. Resources dealing with specific clinical interventions are excluded and are placed in the Medical Research: Diagnosis & Treatment category. Resources that emphasize the specific disease types, or specific systems affected are also excluded and are categorized according to the pathogen or system pathophysiology.
Esperti anonimi
Inglese
Internazionale
STAMPA
34
24
4205
4212
8
Computational Biology; Humans; Myelodysplastic Syndromes; High-Throughput Nucleotide Sequencing; Polymorphism, Single Nucleotide; Software
https://academic.oup.com/bioinformatics/article/34/24/4205/5045348
14
info:eu-repo/semantics/article
262
Sandmann, S.; Karimi, M.; de Graaf, A. O.; Rohde, C.; Gollner, S.; Varghese, J.; Ernsting, J.; Walldin, G.; van der Reijden, B. A.; Muller-Tidow, C.; ...espandi
1 Contributo su Rivista::1.1 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1340754
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