A Comparison of Variant Calling Pipelines Using Genome in a Bottle as a Reference

Cornish, Adam; Guda, Chittibabu

doi:10.1155/2015/456479

Cited by 145 publications

(133 citation statements)

References 33 publications

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“…Within this context, the standard solution is to perform steps 1-3 using Illumina's own proprietary, opensource tool: bcl2fastq2. On the other hand, there is variety of read aligners in widespread use [3], though BWA-MEM [2] is quite popular among these and has been found to produce some of the best alignments [1]. These tools only provide parallelism within a single computing node (shared-memory parallelism).…”

Section: Methodsmentioning

confidence: 99%

Distributed stream processing for genomics pipelines

Versaci¹,

Pireddu²,

Zanetti³

2017

Preprint

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Personalized medicine is in great part enabled by the progress in data acquisition technologies for modern biology, such as next-generation sequencing (NGS). Conventional NGS processing workflows are composed by independent tools implementing shared-memory parallelism which communicate by means of intermediate files. With increasing data sizes this approach is showing its limited scalability and robustness characteristics – problems that make it unsuitable for large-scale, population-wide personalized medicine applications. In this work we propose the adoption of the stream computing architecture to make the genomics pipeline more scalable, and fault-tolerant. We implemented the first processing phases for Illumina sequencing data – from raw data to alignment – using the Apache Flink distributed stream processing framework and Apache Kafka. The new pipeline has been tested processing the raw output of an Illumina HiSeq3000 sequencer and producing aligned reads in CRAM format. The results show near optimal scalability characteristics on experiments from 1 to 12 computing nodes, with a speed-up of 9.5x over the conventional solution (which cannot automatically run on multiple nodes). This result is particularly positive considering that the very short runtime of the experiment – less than 15 minutes – makes significant the constant time costs imposed by the overheads of the frameworks.

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Section: Methodsmentioning

confidence: 99%

Distributed stream processing for genomics pipelines

Versaci¹,

Pireddu²,

Zanetti³

2017

Preprint

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“…It allowed more systematic comparison of SNP and genotype callers aiming to provide clinical NGS usage guidance [218]. There is growing evidence of improving sensitivity and specificity of variant call by utilizing multiple call consensus approach together with this reliable SNP set [219,220].…”

Section: Problems and Best Practices To Solve Them: Variant Calling Amentioning

confidence: 99%

Computational Errors and Biases in Short Read Next Generation Sequencing

Abnizova¹,

Boekhorst²,

Orlov³

2017

J Proteomics Bioinform

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“…NIST RM 8398, the genomic DNA derived from the well-characterized cell line GM12878, is the world's first RM used for whole-genome variant assessment [45]. In addition, the reference data collected for the physical genomic DNA can be used to assess the performance of bioinformatics pipelines [46]. Cell lines, DNA, and the data from the GIAB project (http://jimb.stanford.edu/) are publicly available.…”

Section: Commercial Sources Of Qc Materials For Ngs Assaymentioning

confidence: 99%

Quality control materials for pharmacogenomic testing in the clinic

Lin

Zhang

Han

et al. 2017

Clinical Chemistry and Laboratory Medicine (CCLM)

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Pharmacogenomics has significantly added to our understanding of drug responses in clinical pharmacology, changing the paradigm of treatment decisions. Interrogations of both inherited and somatic variations for therapeutic purposes are increasingly being adopted in clinics, where quality control (QC) materials are required. However, for many pharmacogenomic tests, the acquisition of well-characterized QC materials is often difficult or impossible. In this review, several sources of appropriate QC materials for therapy-associated genetic testing are discussed. Among them, the novel methods for producing renewable controls that resemble patient samples are highlighted. Owing to technological complexity, more efforts are needed to develop proper controls for next-generation sequencing-based assay.

show abstract

A Comparison of Variant Calling Pipelines Using Genome in a Bottle as a Reference

Cited by 145 publications

References 33 publications

Distributed stream processing for genomics pipelines

Distributed stream processing for genomics pipelines

Computational Errors and Biases in Short Read Next Generation Sequencing

Quality control materials for pharmacogenomic testing in the clinic

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