The application of Next Generation Sequencing to Whole GenomeSequencing is still showing enhanced advantages in many research fields suchas medical diagnostics. Here we conducted a comparative assessment ofGATK3-HaplotypeCaller, FreeBayes and Samtools-mpileup, three state ofthe art variant calling algorithms, on a "gold standard" benchmark. Theanalyses were performed exploiting the high performance computing technologyof ReCaS datacenter. Our results indicated that Samtools-mpileup was themost conservative with the highest precision, followed by FreeBayes andGATK3-HaplotypeCaller, which presented the highest sensitivity. Moreover,the merged call-set resulted in lower sensitivity and precision, suggestingadditional testing using different merging methods followed by wet-labvalidations. Despite some limitations, these results provide important insightsfor the development and refinement of novel bioinformatics tools and workflows.
Variant Calling Algorithms Benchmark Using High Performance Computing
Bachir Balech
;Monica Santamaria;Graziano Pesole
2020
Abstract
The application of Next Generation Sequencing to Whole GenomeSequencing is still showing enhanced advantages in many research fields suchas medical diagnostics. Here we conducted a comparative assessment ofGATK3-HaplotypeCaller, FreeBayes and Samtools-mpileup, three state ofthe art variant calling algorithms, on a "gold standard" benchmark. Theanalyses were performed exploiting the high performance computing technologyof ReCaS datacenter. Our results indicated that Samtools-mpileup was themost conservative with the highest precision, followed by FreeBayes andGATK3-HaplotypeCaller, which presented the highest sensitivity. Moreover,the merged call-set resulted in lower sensitivity and precision, suggestingadditional testing using different merging methods followed by wet-labvalidations. Despite some limitations, these results provide important insightsfor the development and refinement of novel bioinformatics tools and workflows.File | Dimensione | Formato | |
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