Accuracy and efficiency of germline variant calling pipelines for human genome data

Zhao, Sen; Agafonov, Oleg; Azab, Abdulrahman; Stokowy, Tomasz; Hovig, Eivind

doi:10.1038/s41598-020-77218-4

Cited by 75 publications

(66 citation statements)

References 41 publications

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“…As a demonstration we chose Agilent hybrid capture panel + Illumina DRAGEN somatic small variant caller. For our ultra-large dataset (> 1000 × WES) without matched normal samples, Illumina DRAGEN bioinformatics pipeline was chosen based on high accuracy, high efficiency, and for not needing matched normal samples 29 , 30 . A recent benchmark study showed that across 5 datasets, DRAGEN produces 14–67% and 22–91% fewer false SNV calls, 35–86% and 48–89% fewer false indel calls, at 75% and 830% faster speed than Strelka2 and Mutect2 respectively 24 .…”

Section: Discussionmentioning

confidence: 99%

Confirming putative variants at ≤ 5% allele frequency using allele enrichment and Sanger sequencing

Yan¹,

Chen

Cheng

et al. 2021

Sci Rep

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Whole exome sequencing (WES) is used to identify mutations in a patient’s tumor DNA that are predictive of tumor behavior, including the likelihood of response or resistance to cancer therapy. WES has a mutation limit of detection (LoD) at variant allele frequencies (VAF) of 5%. Putative mutations called at ≤ 5% VAF are frequently due to sequencing errors, therefore reporting these subclonal mutations incurs risk of significant false positives. Here we performed ~ 1000 × WES on fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissue biopsy samples from a non-small cell lung cancer patient, and identified 226 putative mutations at between 0.5 and 5% VAF. Each variant was then tested using NuProbe NGSure, to confirm the original WES calls. NGSure utilizes Blocker Displacement Amplification to first enrich the allelic fraction of the mutation and then uses Sanger sequencing to determine mutation identity. Results showed that 52% of the 226 (117) putative variants were disconfirmed, among which 2% (5) putative variants were found to be misidentified in WES. In the 66 cancer-related variants, the disconfirmed rate was 82% (54/66). This data demonstrates Blocker Displacement Amplification allelic enrichment coupled with Sanger sequencing can be used to confirm putative mutations ≤ 5% VAF. By implementing this method, next-generation sequencing can reliably report low-level variants at a high sensitivity, without the cost of high sequencing depth.

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Section: Discussionmentioning

confidence: 99%

Confirming putative variants at ≤ 5% allele frequency using allele enrichment and Sanger sequencing

Yan¹,

Chen

Cheng

et al. 2021

Sci Rep

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show abstract

“…For example, sequencing pipelines, typically using algorithms running on high-end computer clusters on general CPUs, are being integrated in processors themselves (i.e., ‘hard-coded’). The reconfigurable DRAGEN Bio-IT Processor, produced by Illumina [ 56 ], has hard-coded highly optimized algorithms for the full next generation sequencing (NGS) secondary analysis pipeline, which set world speed records for genomic data analysis [ 57 ].…”

Section: Progress Of Genomic Technologies Enabling Personalized Medicinementioning

confidence: 99%

Advances in Genomic Discovery and Implications for Personalized Prevention and Medicine: Estonia as Example

Prins

Leitsalu

Pärna

et al. 2021

JPM

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The current paradigm of personalized medicine envisages the use of genomic data to provide predictive information on the health course of an individual with the aim of prevention and individualized care. However, substantial efforts are required to realize the concept: enhanced genetic discoveries, translation into intervention strategies, and a systematic implementation in healthcare. Here we review how further genetic discoveries are improving personalized prediction and advance functional insights into the link between genetics and disease. In the second part we give our perspective on the way these advances in genomic research will transform the future of personalized prevention and medicine using Estonia as a primer.

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“…This file contains biological sequences aligned to a reference sequence in a machine readable format. Methods like Samtools [3] and The Genome Analysis Toolkit (GATK) are recognized as being the most accurate for more advanced Bioinformatics analysis [4][5] such as variant calling (BAM to VCF), to look for a singlenucleotide polymorphism (SNP) "genetic mutations". The FreeBayes variant detector gives by far the best compromise in speed and sensitivity [6][7].…”

Section: Introductionmentioning

confidence: 99%

Towards Protect a Specific Information in Genomic Data

Achour¹,

Belmadani²

2021

IJIES

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Research on the privacy of human genomic data has significantly increased these last years to find out effective solutions to protect the most critical information resulting from an alignment operation such as the genomic position, cigar and Read content. In this paper, the authors propose an encoding technique based on homomorphic encryption to protect genomic positions of DNA sequences for a secure storage of BAM file. This technique uses two Discrete Gaussian Sampling algorithms for comparison purposes which is Gauss and Knuth-Yao algorithm. The framework was implemented on Java from scratch using container data structure with standard java HashMap for the representation of duplicates positions elements exiting in BAM file. The proposed method was assessed on the NA12878 dataset with initially 2 million positions to encrypt. Obtained results show that the FV-Knuth-Yao technique with HashMap architecture storing 165667 positions and a polynomial degree equal to 64 ensures a fast encryption time estimated to 6,5 minutes. The decryption operation needs 1 hour with zero loss of information. The acceptable security level reached 2 64 operations to break the cryptosystem. To demonstrate the efficiency, security and reliability of our approach, the FV-Knuth-Yao was compared with the OPE Method as implemented in SECRAM tool which is based on a deterministic encryption scheme. Our work mainly focuses on the security of genomic data without compression of BAM file.

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Accuracy and efficiency of germline variant calling pipelines for human genome data

Cited by 75 publications

References 41 publications

Confirming putative variants at ≤ 5% allele frequency using allele enrichment and Sanger sequencing

Confirming putative variants at ≤ 5% allele frequency using allele enrichment and Sanger sequencing

Advances in Genomic Discovery and Implications for Personalized Prevention and Medicine: Estonia as Example

Towards Protect a Specific Information in Genomic Data

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