Dataset Information

OTG-snpcaller: an optimized pipeline based on TMAP and GATK for SNP calling from ion torrent data.

ABSTRACT: Because the new Proton platform from Life Technologies produced markedly different data from those of the Illumina platform, the conventional Illumina data analysis pipeline could not be used directly. We developed an optimized SNP calling method using TMAP and GATK (OTG-snpcaller). This method combined our own optimized processes, Remove Duplicates According to AS Tag (RDAST) and Alignment Optimize Structure (AOS), together with TMAP and GATK, to call SNPs from Proton data. We sequenced four sets of exomes captured by Agilent SureSelect and NimbleGen SeqCap EZ Kit, using Life Technology's Ion Proton sequencer. Then we applied OTG-snpcaller and compared our results with the results from Torrent Variants Caller. The results indicated that OTG-snpcaller can reduce both false positive and false negative rates. Moreover, we compared our results with Illumina results generated by GATK best practices, and we found that the results of these two platforms were comparable. The good performance in variant calling using GATK best practices can be primarily attributed to the high quality of the Illumina sequences.

SUBMITTER: Zhu P

PROVIDER: S-EPMC4019570 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

OTG-snpcaller: an optimized pipeline based on TMAP and GATK for SNP calling from ion torrent data.

Zhu Pengyuan P He Lingyu L Li Yaqiao Y Huang Wenpan W Xi Feng F Lin Lin L Zhi Qihuan Q Zhang Wenwei W Tang Y Tom YT Geng Chunyu C Lu Zhiyuan Z Xu Xun X

PloS one 20140513 5

Because the new Proton platform from Life Technologies produced markedly different data from those of the Illumina platform, the conventional Illumina data analysis pipeline could not be used directly. We developed an optimized SNP calling method using TMAP and GATK (OTG-snpcaller). This method combined our own optimized processes, Remove Duplicates According to AS Tag (RDAST) and Alignment Optimize Structure (AOS), together with TMAP and GATK, to call SNPs from Proton data. We sequenced four se ...[more]

PMID: 24824529

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Project description:BackgroundThe advent of next generation sequencing has opened new avenues for basic and applied research. One application is the discovery of sequence variants causative of a phenotypic trait or a disease pathology. The computational task of detecting and annotating sequence differences of a target dataset between a reference genome is known as "variant calling". Typically, this task is computationally involved, often combining a complex chain of linked software tools. A major player in this field is the Genome Analysis Toolkit (GATK). The "GATK Best Practices" is a commonly referred recipe for variant calling. However, current computational recommendations on variant calling predominantly focus on human sequencing data and ignore ever-changing demands of high-throughput sequencing developments. Furthermore, frequent updates to such recommendations are counterintuitive to the goal of offering a standard workflow and hamper reproducibility over time.ResultsA workflow for automated detection of single nucleotide polymorphisms and insertion-deletions offers a wide range of applications in sequence annotation of model and non-model organisms. The introduced workflow builds on the GATK Best Practices, while enabling reproducibility over time and offering an open, generalized computational architecture. The workflow achieves parallelized data evaluation and maximizes performance of individual computational tasks. Optimized Java garbage collection and heap size settings for the GATK applications SortSam, MarkDuplicates, HaplotypeCaller, and GatherVcfs effectively cut the overall analysis time in half.ConclusionsThe demand for variant calling, efficient computational processing, and standardized workflows is growing. The Open source Variant calling workFlow (OVarFlow) offers automation and reproducibility for a computationally optimized variant calling task. By reducing usage of computational resources, the workflow removes prior existing entry barriers to the variant calling field and enables standardized variant calling.

Dataset Information

OTG-snpcaller: an optimized pipeline based on TMAP and GATK for SNP calling from ion torrent data.

Publications

OTG-snpcaller: an optimized pipeline based on TMAP and GATK for SNP calling from ion torrent data.

Similar Datasets

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