scholarly journals Allele-specific copy-number discovery from whole-genome and whole-exome sequencing

2015 ◽  
Vol 43 (14) ◽  
pp. e90-e90 ◽  
Author(s):  
WeiBo Wang ◽  
Wei Wang ◽  
Wei Sun ◽  
James J. Crowley ◽  
Jin P. Szatkiewicz
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Whole Genome ◽  
Whole Exome ◽  
Allele Specific

scholarly journals Reliable analysis of clinical tumor-only whole exome sequencing data

2019 ◽  
Author(s):  
Sehyun Oh ◽  
Ludwig Geistlinger ◽  
Marcel Ramos ◽  
Martin Morgan ◽  
Levi Waldron ◽  
...  
Keyword(s):  
Open Source ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
High Accuracy ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Mutational Signatures ◽  
Whole Exome ◽  
Allele Specific

AbstractBackgroundAllele-specific copy number alteration (CNA) analysis is essential to study the functional impact of single nucleotide variants (SNV) and the process of tumorigenesis. Most commonly used tools in the field rely on high quality genome-wide data with matched normal profiles, limiting their applicability in clinical settings.MethodsWe propose a workflow, based on the open-source PureCN R/Bioconductor package in conjunction with widely used variant-calling and copy number segmentation algorithms, for allele-specific CNA analysis from whole exome sequencing (WES) without matched normals. We use The Cancer Genome Atlas (TCGA) ovarian carcinoma (OV) and lung adenocarcinoma (LUAD) datasets to benchmark its performance against gold standard SNP6 microarray and WES datasets with matched normal samples. Our workflow further classifies SNVs by somatic status and then uses this information to infer somatic mutational signatures and tumor mutational burden (TMB).ResultsApplication of our workflow to tumor-only WES data produces tumor purity and ploidy estimates that are highly concordant with estimates from SNP6 microarray data and matched-normal WES data. The presence of cancer type-specific somatic mutational signatures was inferred with high accuracy. We also demonstrate high concordance of TMB between our tumor-only workflow and matched normal pipelines.ConclusionThe proposed workflow provides, to our knowledge, the only open-source option for comprehensive allele-specific CNA analysis and SNV classification of tumor-only WES with demonstrated high accuracy.

scholarly journals Reliable Analysis of Clinical Tumor-Only Whole-Exome Sequencing Data

2020 ◽  
pp. 321-335 ◽  
Author(s):  
Sehyun Oh ◽  
Ludwig Geistlinger ◽  
Marcel Ramos ◽  
Martin Morgan ◽  
Levi Waldron ◽  
...  
Keyword(s):  
Open Source ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Microarray Data ◽  
Copy Number ◽  
High Accuracy ◽  
Cancer Type ◽  
Mutational Signatures ◽  
Whole Exome ◽  
Allele Specific

PURPOSE Allele-specific copy number alteration (CNA) analysis is essential to study the functional impact of single-nucleotide variants (SNVs) and the process of tumorigenesis. However, controversy over whether it can be performed with sufficient accuracy in data without matched normal profiles and a lack of open-source implementations have limited its application in clinical research and diagnosis. METHODS We benchmark allele-specific CNA analysis performance of whole-exome sequencing (WES) data against gold standard whole-genome SNP6 microarray data and against WES data sets with matched normal samples. We provide a workflow based on the open-source PureCN R/Bioconductor package in conjunction with widely used variant-calling and copy number segmentation algorithms for allele-specific CNA analysis from WES without matched normals. This workflow further classifies SNVs by somatic status and then uses this information to infer somatic mutational signatures and tumor mutational burden (TMB). RESULTS Application of our workflow to tumor-only WES data produces tumor purity and ploidy estimates that are highly concordant with estimates from SNP6 microarray data and matched normal WES data. The presence of cancer type–specific somatic mutational signatures was inferred with high accuracy. We also demonstrate high concordance of TMB between our tumor-only workflow and matched normal pipelines. CONCLUSION The proposed workflow provides, to our knowledge, the only open-source option with demonstrated high accuracy for comprehensive allele-specific CNA analysis and SNV classification of tumor-only WES. An implementation of the workflow is available on the Terra Cloud platform of the Broad Institute (Cambridge, MA).

scholarly journals Allele-specific copy number estimation by whole exome sequencing

2017 ◽  
Vol 11 (2) ◽  
pp. 1169-1192 ◽  
Author(s):  
Hao Chen ◽  
Yuchao Jiang ◽  
Kara N. Maxwell ◽  
Katherine L. Nathanson ◽  
Nancy Zhang
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Estimation ◽  
Whole Exome ◽  
Allele Specific

Whole-exome sequencing reveals potential germline and somatic mutations in 60 malignant ovarian germ cell tumors

2021 ◽  
Author(s):  
Juan Chen ◽  
Yan Li ◽  
Jianlei Wu ◽  
Yakun Liu ◽  
Shan Kang
Keyword(s):  
Germ Cell ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Peripheral Blood ◽  
Copy Number ◽  
Somatic Mutations ◽  
Germ Cell Tumors ◽  
Germline Mutations ◽  
Deletion Region ◽  
Whole Exome

Abstract Background Malignant ovarian germ cell tumors (MOGCTs) are rare and heterogeneous ovary tumors. We aimed to identify potential germline mutations and somatic mutations in MOGCTs by whole-exome sequencing. Methods The peripheral blood and tumor samples from these patients were used to identify germline mutations and somatic mutations, respectively. For those genes corresponding to copy number alterations (CNA) deletion and duplication region, functional annotation of was performed. Immunohistochemistry was performed to evaluate the expression of mutated genes corresponding to CNA deletion region. Results In peripheral blood, copy number loss and gain were mostly found in yolk sac tumors (YST). Moreover, POU5F1 was the most significant mutated gene with mutation frequency > 10% in both CNA deletion and duplication region. In addition, strong cytoplasm staining of POU5F1 (corresponding to CNA deletion region) was found in 2 YST and nuclear staining in 2 dysgerminomas (DG) tumor samples. Genes corresponding to CNA deletion region were significantly enriched in the signaling pathway of regulating pluripotency of stem cells. In addition, genes corresponding to CNA duplication region were significantly enriched in the signaling pathways of RIG-I-like receptor, Toll-like receptor, NF-kappa B and Jak–STAT. KRT4, RPL14, PCSK6, PABPC3 and SARM1 mutations were detected in both peripheral blood and tumor samples. Conclusions Identification of potential germline mutations and somatic mutations in MOGCTs may provide a new field in understanding the genetic feature of the rare biological tumor type in the ovary.

scholarly journals Challenges of using next generation sequencing in newborn screening

2015 ◽  
Vol 97 ◽  
Author(s):  
EYAL REINSTEIN
Keyword(s):  
Newborn Screening ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Ethical Issues ◽  
Whole Genome ◽  
Short Article ◽  
Public Health Programs ◽  
Whole Exome ◽  
Metabolic Conditions ◽  
Widespread Dissemination

SummaryWhole-genome and whole-exome sequencing for clinical applications is now an integral part of medical genetics practice. The term newborn screening refers to public health programs designed to screen newborns for various treatable metabolic conditions, by measuring levels of circulating blood metabolites. The availability and significant decrease in sequencing costs has raised the question of whether metabolic newborn screening should be replaced by whole-genome or whole-exome sequencing. While newborn genome sequencing can potentially increase the number of disorders identified by newborn screening, the generalization of its practice raises a number of important ethical issues. This short article argues that there are medical, psychological, ethical and economic reasons why widespread dissemination of newborn screening is still premature.

scholarly journals Whole-genome sequencing offers additional but limited clinical utility compared with reanalysis of whole-exome sequencing

2018 ◽  
Vol 20 (11) ◽  
pp. 1328-1333 ◽  
Author(s):  
Ahmed Alfares ◽  
Taghrid Aloraini ◽  
Lamia Al subaie ◽  
Abdulelah Alissa ◽  
Ahmed Al Qudsi ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Genome Sequencing ◽  
Clinical Utility ◽  
Whole Genome ◽  
Whole Exome

scholarly journals RefCNV: Identification of Gene-Based Copy Number Variants Using Whole Exome Sequencing

2016 ◽  
Vol 15 ◽  
pp. CIN.S36612 ◽  
Author(s):  
Lun-Ching Chang ◽  
Biswajit Das ◽  
Chih-Jian Lih ◽  
Han Si ◽  
Corinne E. Camalier ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Estimation Methods ◽  
Single Nucleotide Variants ◽  
False Positive Error ◽  
Reference Set ◽  
Genome Wide ◽  
Whole Exome

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly ( r = 0.96–0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman's coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.

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