A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Hintzsche, Jennifer D.; Robinson, William A.; Tan, Aik Choon

doi:10.1155/2016/7983236

Cited by 39 publications

(22 citation statements)

References 83 publications

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“…The use of different variant callers, with exactly the same filtering parameters, was intentional. VarScan, a high performance variant caller [ 17 ], is commonly used in analytical pipelines for the analysis of the cancer genome [ 18 ] and therefore, was considered our gold standard. VarScan results were directly compared with Ion Reporter, the analytical pipeline specifically designed for variant calling of data generated by Ion sequencing platforms to allow for a streamlined workflow.…”

Section: Resultsmentioning

confidence: 99%

Development and validation of a targeted next generation DNA sequencing panel outperforming whole exome sequencing for the identification of clinically relevant genetic variants

et al. 2017

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Next generation sequencing (NGS) technologies have revolutionized our approach to genomic research. The use of whole genome sequencing (WGS), whole exome sequencing (WES), transcriptome profiling, and targeted DNA sequencing has exponentially improved our understanding of the human genome and the genetic complexities underlying malignancy. Yet, WGS and WES clinical applications remain limited due to high costs and the large volume of data generated. When utilized to address biological questions in basic science studies, targeted sequencing panels have proven extremely valuable due to reduced costs and higher sequencing depth. However, the routine application of targeted sequencing to the clinical setting is limited to a few cancer subtypes. Some highly aggressive tumor types, like type 2 endometrial cancer (EC), could greatly benefit from routine genomic analysis using targeted sequencing. To explore the potential utility of a mid size panel (~150 genes) in the clinical setting, we developed and validated a custom panel against WGS, WES, and another commercially available targeted panel. Our results indicate that a mid size custom designed panel is as efficient as WGS and WES in mapping variants of biological and clinical relevance, rendering higher coverage, at a lower cost, with fewer variants of uncertain significance. Because of the much higher sequencing depth that could be achieved, our results demonstrate that targeted sequencing outperformed WGS and WES in the mapping of pathogenic variants in a breast cancer case, as well as a case of mixed serous and high-grade endometrioid EC, the most aggressive EC subtype.

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Section: Resultsmentioning

confidence: 99%

Development and validation of a targeted next generation DNA sequencing panel outperforming whole exome sequencing for the identification of clinically relevant genetic variants

et al. 2017

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“…Despite the broad range of potential sources of neoantigens in cancer cells, the process of selection of genomically encoded antigens that are of immunological significance remains to be well-established. Many computational pipelines have been developed to predict neoantigens from cancer genomes (91,92). A joint effort referred to as the Tumor Neoantigen Selection Alliance (TESLA; supported by the Parker Institute for Cancer Immunotherapy and the Cancer Research Institute) to find the right predictive algorithms for targeting neoantigens (based upon NSVs) through large scale validation is ongoing.…”

Section: On a Computational Hunt For Neoantigens Somatic Mutation Calmentioning

confidence: 99%

Computational Prediction and Validation of Tumor-Associated Neoantigens

2020

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“…Also pathogen typing or population assignment objectives primarily require information on polymorphic sites. It is nevertheless quite common to see such studies to undertake expensive WGS procedures only for final analyses to take place ‘post-VCF’ 24 , i.e., using a list of diagnostic markers compiled from a small fraction of polymorphic reads.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide locus sequence typing (GLST) of eukaryotic pathogens

Schwabl¹,

et al. 2020

Preprint

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20Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful 21 inference from pathogen genetic variation, however, is often restrained by limited access to representative 22 target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive 23 or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly 24 from vector/host material but are often too complex and expensive for resource-poor settings where infectious 25 diseases prevail. This study proposes a simple, cost-effective 'genome-wide locus sequence typing' (GLST) 26 tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. 27 The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a 28 single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation 29 at under 4 USD per sample. Approximately 100 libraries can be sequenced together in one Illumina MiSeq 30 run. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic 31 agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free 32 metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/µl T. cruzi DNA and further 33 elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing 34 discrete typing units (DTUs) TcI, TcIII, TcIV, and TcVI. The 780 SNP sites we identify in the sample set 35 repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and 36 geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate 37 DTUs. We discuss the advantages, limitations and prospects of our method across a spectrum of 38 epidemiological research. 40Genome-wide single nucleotide polymorphism (SNP) analysis is a powerful and increasingly common 41 approach in the study and surveillance of infectious disease. Understanding patterns of SNP diversity within 42 pathogen genomes and across pathogen populations can resolve fundamental biological questions (e.g., 43 reproductive mechanisms in T. cruzi 1 , reconstruct past 2 and present transmission networks (e.g., 44 Staphylococcus infections within hospitals) 3 or identify the genetic bases of virulence 4,5 and resistance to drugs 45 (see examples from Plasmodium spp. 6,7 ). A number of obstacles, however, complicate access to 46 representative, genome-wide SNP information using modern sequencing tools. Micro-pathogens are often 47 sampled in low quantities and together with large amounts of host/vector tissue, microbiota, or environmental 48 DNA. Sequencing is rarely viable directly from the infection source and studies have often found it necessary 49 to isolate and culture the target organism to higher densities before extracting D...

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A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Cited by 39 publications

References 83 publications

Development and validation of a targeted next generation DNA sequencing panel outperforming whole exome sequencing for the identification of clinically relevant genetic variants

Development and validation of a targeted next generation DNA sequencing panel outperforming whole exome sequencing for the identification of clinically relevant genetic variants

Computational Prediction and Validation of Tumor-Associated Neoantigens

Genome-wide locus sequence typing (GLST) of eukaryotic pathogens

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