A Systematic Assessment of Accuracy in Detecting Somatic Mosaic Variants by Deep Amplicon Sequencing: Application to NF2 Gene
Author(s) -
Elisa Contini,
Irene Paganini,
Roberta Sestini,
Luisa Candita,
Gabriele Lorenzo Capone,
Lorenzo Barbetti,
Serena Falconi,
Sabrina Frusconi,
Irene Giotti,
Costanza Giuliani,
Francesca Torricelli,
Matteo Benelli,
Laura Papi
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0129099
Subject(s) - amplicon , deep sequencing , false positive paradox , dna sequencing , biology , genetics , computational biology , genotype , amplicon sequencing , polymerase chain reaction , gene , genome , computer science , artificial intelligence , 16s ribosomal rna
The accurate detection of low-allelic variants is still challenging, particularly for the identification of somatic mosaicism, where matched control sample is not available. High throughput sequencing, by the simultaneous and independent analysis of thousands of different DNA fragments, might overcome many of the limits of traditional methods, greatly increasing the sensitivity. However, it is necessary to take into account the high number of false positives that may arise due to the lack of matched control samples. Here, we applied deep amplicon sequencing to the analysis of samples with known genotype and variant allele fraction (VAF) followed by a tailored statistical analysis. This method allowed to define a minimum value of VAF for detecting mosaic variants with high accuracy. Then, we exploited the estimated VAF to select candidate alterations in NF2 gene in 34 samples with unknown genotype (30 blood and 4 tumor DNAs), demonstrating the suitability of our method. The strategy we propose optimizes the use of deep amplicon sequencing for the identification of low abundance variants. Moreover, our method can be applied to different high throughput sequencing approaches to estimate the background noise and define the accuracy of the experimental design.
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