scholarly journals Feature-based classifiers for somatic mutation detection in tumour–normal paired sequencing data

2011 ◽  
Vol 28 (2) ◽  
pp. 167-175 ◽  
Author(s):  
Jiarui Ding ◽  
Ali Bashashati ◽  
Andrew Roth ◽  
Arusha Oloumi ◽  
Kane Tse ◽  
...  
Keyword(s):  
Somatic Mutation ◽  
Mutation Detection ◽  
Sequencing Data ◽  
Feature Based ◽  
Somatic Mutation Detection

VHVT: An ultra-sensitive somatic mutation detection and performance assessment program.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1588-1588 ◽  
Author(s):  
Jilong Liu ◽  
Zu Liu ◽  
Shaomin Cheng ◽  
Fengming Guo ◽  
Meihua Tan ◽  
...  
Keyword(s):  
Somatic Mutation ◽  
Mutation Detection ◽  
Low Frequency ◽  
Allelic Frequency ◽  
Driver Mutations ◽  
Clinical Samples ◽  
Sequencing Error ◽  
Sequencing Data ◽  
Standard Data ◽  
Somatic Mutation Detection

1588 Background: NGS as a high throughput technique is particular valuable for cancer given its ability to detect multiple driver mutations. While reads contain SNVs and short InDels can be mapped to the right position using gatk-like programs, a program designed for germline mutation detection, reads contain long InDels such as EGFR EX19 deletions often wrongly mapped especially when deletions near the ends of the reads. Thus, gatk would not recognize these reads, consequently underestimate the mutation allelic frequency, and even missed out InDels when supporting reads were rare. Methods: Here we present a variation hotspot validation toolkit (VHVT), a validation based method to precisely detect the ultra-low frequency somatic mutations. As far as we know, it is the first specialized somatic mutation detection software. First, reference sequences aimed at the hotspot mutations were assembled, then reads were be mapped to the new assembled reference to precisely distinguish the supporting reads. Moreover, log odds (LOD) and Poisson mathematical model were integrated to control sequencing error, as a result, VHVT can achieve a limitation of detection at 0.01% with sensitivity and specificity above 95% and 99% respectively. In addition, we developed a method to quantitatively assess the performance of variation detection program using standard reference data. By mapping to the reconstructed reference, all supporting reads will be detected in sequencing data, and comparing theses with the number of supporting reads delivered by a program we can define recognition ratio of supporting reads. Results: Our reference standard data showed that VHVT can recognize average 30% more support reads than gatk for EGFR EX19 deletions. In a total 498 NSCLC clinical samples test, VHVT detected actionable mutations in 289 samples. 243 positive mutations were verified (168 by SANGER sequencing, 75 by ddPCR) with concordance rate at 100%. Conclusions: Taken all together, our results demonstrated the robust performance of VHVT for somatic mutation detection and program assessment and thus facilitate the development of personalized cancer therapy.

scholarly journals An empirical Bayesian framework for somatic mutation detection from cancer genome sequencing data

2013 ◽  
Vol 41 (7) ◽  
pp. e89-e89 ◽  
Author(s):  
Yuichi Shiraishi ◽  
Yusuke Sato ◽  
Kenichi Chiba ◽  
Yusuke Okuno ◽  
Yasunobu Nagata ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Somatic Mutation ◽  
Mutation Detection ◽  
Bayesian Framework ◽  
Cancer Genome ◽  
Sequencing Data ◽  
Empirical Bayesian ◽  
Cancer Genome Sequencing ◽  
Somatic Mutation Detection

scholarly journals Restriction endonuclease-mediated real-time digestion-PCR for somatic mutation detection

2012 ◽  
Vol 132 (12) ◽  
pp. 2858-2866 ◽  
Author(s):  
Jinyin Zhao ◽  
Feifei Xie ◽  
Wei Zhong ◽  
Weili Wu ◽  
Shoufang Qu ◽  
...  
Keyword(s):  
Restriction Endonuclease ◽  
Real Time ◽  
Somatic Mutation ◽  
Mutation Detection ◽  
Somatic Mutation Detection

scholarly journals Somatic mutation detection efficiency in EGFR: a comparison between High Resolution Melting Analysis and Sanger Sequencing

2020 ◽  
Author(s):  
Reenu Anne Joy ◽  
Sukrishna Kamalasanan Thelakkattusserry ◽  
Narendranath Vikkath ◽  
Renjitha Bhaskaran ◽  
Damodaran Vasudevan ◽  
...  
Keyword(s):  
High Resolution ◽  
Somatic Mutation ◽  
Sanger Sequencing ◽  
Mutation Detection ◽  
Detection Efficiency ◽  
Limit Of Detection ◽  
Tumor Tissues ◽  
Allele Specific ◽  
Somatic Mutation Detection ◽  
Allele Fraction

Abstract Background: High resolution melting curve analysis is a cost-effective rapid screening method for detection of somatic gene mutation. The performance characteristics of this technique has been explored previously, however, analytical parameters such as limit of detection of mutant allele fraction and total concentration of DNA, have not been addressed. The current study focuses on comparing the mutation detection efficiency of High-Resolution Melt Analysis (HRM) with Sanger Sequencing in somatic mutations of the EGFR gene in non-small cell lung cancer .Methods: The minor allele fraction of somatic mutations was titrated against total DNA concentration using Sanger sequencing and HRM to determine the limit of detection. The mutant and wildtype allele fractions were validated by multiplex allele-specific real-time PCR. Somatic mutation detection efficiency, for exons 19 & 21 of the EGFR gene, was compared in 116 formalin fixed paraffin embedded tumor tissues, after screening 275 tumor tissues by Sanger sequencing.Results: The limit of detection of minor allele fraction of exon 19 mutation was 1% with Sequencing, and 0.25% with HRM, whereas for exon 21 mutation, 0.25% MAF was detected using both methods. Multiplex allele-specific real-time PCR revealed that the wildtype DNA did not impede the amplification of mutant allele in mixed DNA assays. All mutation positive samples detected by Sanger sequencing, were also detected by HRM. About 28% cases in exon 19 and 40% in exon 21, detected as mutated in HRM, were not detected by sequencing. Overall, sensitivity and specificity of HRM were found to be 100% and 67% respectively, and the negative predictive value was 100%, while positive predictive value was 80%. Conclusion: The comparative series study suggests that HRM is a modest initial screening test for somatic mutation detection of EGFR, which must further be confirmed by Sanger sequencing. With the modification of annealing temperature of initial PCR, the limit of detection of Sanger sequencing can be improved.

Targeted Hybrid-Capture for Somatic Mutation Detection in the Clinic

2015 ◽  
pp. 321-341
Author(s):  
Catherine E. Cottrell ◽  
Andrew J. Bredemeyer ◽  
Hussam Al-Kateb
Keyword(s):  
Somatic Mutation ◽  
Mutation Detection ◽  
Hybrid Capture ◽  
Somatic Mutation Detection

scholarly journals Somatic mutation detection efficiency in EGFR: a comparison between high resolution melting analysis and Sanger sequencing

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Reenu Anne Joy ◽  
Sukrishna Kamalasanan Thelakkattusserry ◽  
Narendranath Vikkath ◽  
Renjitha Bhaskaran ◽  
Sajitha Krishnan ◽  
...  
Keyword(s):  
High Resolution ◽  
Somatic Mutation ◽  
Sanger Sequencing ◽  
Mutation Detection ◽  
Detection Efficiency ◽  
Limit Of Detection ◽  
Tumor Tissues ◽  
Allele Specific ◽  
Somatic Mutation Detection ◽  
Allele Fraction

Abstract Background High resolution melting curve analysis is a cost-effective rapid screening method for detection of somatic gene mutation. The performance characteristics of this technique has been explored previously, however, analytical parameters such as limit of detection of mutant allele fraction and total concentration of DNA, have not been addressed. The current study focuses on comparing the mutation detection efficiency of High-Resolution Melt Analysis (HRM) with Sanger Sequencing in somatic mutations of the EGFR gene in non-small cell lung cancer. Methods The minor allele fraction of somatic mutations was titrated against total DNA concentration using Sanger sequencing and HRM to determine the limit of detection. The mutant and wildtype allele fractions were validated by multiplex allele-specific real-time PCR. Somatic mutation detection efficiency, for exons 19 & 21 of the EGFR gene, was compared in 116 formalin fixed paraffin embedded tumor tissues, after screening 275 tumor tissues by Sanger sequencing. Results The limit of detection of minor allele fraction of exon 19 mutation was 1% with sequencing, and 0.25% with HRM, whereas for exon 21 mutation, 0.25% MAF was detected using both methods. Multiplex allele-specific real-time PCR revealed that the wildtype DNA did not impede the amplification of mutant allele in mixed DNA assays. All mutation positive samples detected by Sanger sequencing, were also detected by HRM. About 28% cases in exon 19 and 40% in exon 21, detected as mutated in HRM, were not detected by sequencing. Overall, sensitivity and specificity of HRM were found to be 100 and 67% respectively, and the negative predictive value was 100%, while positive predictive value was 80%. Conclusion The comparative series study suggests that HRM is a modest initial screening test for somatic mutation detection of EGFR, which must further be confirmed by Sanger sequencing. With the modification of annealing temperature of initial PCR, the limit of detection of Sanger sequencing can be improved.

scholarly journals Clinical Validation of Somatic Mutation Detection by the OncoScan CNV Plus Assay

2021 ◽  
Vol 23 (1) ◽  
pp. 29-37
Author(s):  
Scott C. Smith ◽  
Midhat S. Farooqi ◽  
Melissa A. Gener ◽  
Kevin Ginn ◽  
Julie M. Joyce ◽  
...  
Keyword(s):  
Somatic Mutation ◽  
Mutation Detection ◽  
Clinical Validation ◽  
Somatic Mutation Detection
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