Dataset Information

VarAmpliCNV: analyzing variance of amplicons to detect CNVs in targeted NGS data.

ABSTRACT:

Motivation

Computational identification of copy number variants (CNVs) in sequencing data is a challenging task. Existing CNV-detection methods account for various sources of variation and perform different normalization strategies. However, their applicability and predictions are restricted to specific enrichment protocols. Here, we introduce a novel tool named varAmpliCNV, specifically designed for CNV-detection in amplicon-based targeted resequencing data (Haloplex™ enrichment protocol) in the absence of matched controls. VarAmpliCNV utilizes principal component analysis (PCA) and/or metric dimensional scaling (MDS) to control variances of amplicon associated read counts enabling effective detection of CNV signals.

Results

Performance of VarAmpliCNV was compared against three existing methods (ConVaDING, ONCOCNV and DECoN) on data of 167 samples run with an aortic aneurysm gene panel (n = 30), including 9 positive control samples. Additionally, we validated the performance on a large deafness gene panel (n = 145) run on 138 samples, containing 4 positive controls. VarAmpliCNV achieved higher sensitivity (100%) and specificity (99.78%) in comparison to competing methods. In addition, unsupervised clustering of CNV segments and visualization plots of amplicons spanning these regions are included as a downstream strategy to filter out false positives.

Availability and implementation

The tool is freely available through galaxy toolshed and at: https://hub.docker.com/r/cmgantwerpen/varamplicnv. Supplementary Data File S1: https://tinyurl.com/2yzswyhh; Supplementary Data File S2: https://tinyurl.com/ycyf2fb4.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Kumar AA

PROVIDER: S-EPMC9805572 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

varAmpliCNV: analyzing variance of amplicons to detect CNVs in targeted NGS data.

Kumar Ajay Anand AA Loeys Bart B Van De Beek Gerarda G Peeters Nils N Wuyts Wim W Van Laer Lut L Vandeweyer Geert G Alaerts Maaike M

Bioinformatics (Oxford, England) 20230101 1

<h4>Motivation</h4>Computational identification of copy number variants (CNVs) in sequencing data is a challenging task. Existing CNV-detection methods account for various sources of variation and perform different normalization strategies. However, their applicability and predictions are restricted to specific enrichment protocols. Here, we introduce a novel tool named varAmpliCNV, specifically designed for CNV-detection in amplicon-based targeted resequencing data (Haloplex™ enrichment protoco ...[more]

PMID: 36440912

Similar Datasets

Project description:BackgroundDespite the new next-generation sequencing (NGS) molecular approaches implemented the genetic testing in clinical diagnosis, copy number variation (CNV) detection from NGS data remains difficult mainly in the absence of bioinformatics personnel (not always available among laboratory resources) and when using very small gene panels that do not meet commercial software criteria. Furthermore, not all large deletions/duplications can be detected with the Multiplex Ligation-dependent Probe Amplification (MLPA) technique due to both the limitations of the methodology and no kits available for the most of genes.AimWe propose our experience regarding the identification of a novel large deletion in the context of a rare skeletal disease, multiple osteochondromas (MO), using and validating a user-friendly approach based on NGS coverage data, which does not require any dedicated software or specialized personnel.MethodsThe pipeline uses a simple algorithm comparing the normalized coverage of each amplicon with the mean normalized coverage of the same amplicon in a group of "wild-type" samples representing the baseline. It has been validated on 11 samples, previously analyzed by MLPA, and then applied on 20 patients with MO but negative for the presence of pathogenic variants in EXT1 or EXT2 genes. Sensitivity, specificity, and accuracy were evaluated.ResultsAll the 11 known CNVs (exon and multi-exon deletions) have been detected with a sensitivity of 97.5%. A novel EXT2 partial exonic deletion c. (744-122)-?_804+?del -out of the MLPA target regions- has been identified. The variant was confirmed by real-time quantitative Polymerase Chain Reaction (qPCR).ConclusionIn addition to enhancing the variant detection rate in MO molecular diagnosis, this easy-to-use approach for CNV detection can be easily extended to many other diagnostic fields-especially in resource-limited settings or very small gene panels. Notably, it also allows partial-exon deletion detection.

Project description:Highly specific amplification of complex DNA pools without bias or template-independent products (TIPs) remains a challenge. We have developed a procedure using phi29 DNA polymerase and trehalose and optimized control of amplification to create micrograms of specific amplicons without TIPs from down to sub-femtograms of DNA. The amplicons from 5 ng and 0.5 ng DNA, which were from originally good quality of gDNA (05-050), or partially degraded gDNA (04-018), faithfully demonstrated all previously known heterozygous segmental duplications and deletions (3 Mb to 18 kb) located on chromosome 22 and even a homozygous deletion smaller than 1 kb with high resolution chromosome-wide CGH. Specifically, HR-CGH with 5 ng-input gDNA-derived amplicon detected all previously known chromosomal segmental aberrations in chromosome 22 in samples from two different probands, and was indistinguishable from the HR-CGH result with native gDNA from the same probands (Fig. 4, Fig. S3 and S4). The break points were also precisely demonstrated. These include a heterozygous genomic segmental duplication (3 copies, 3 Mb in size, sample 05-050, Fig. 4) and 2 different heterozygous deletions (1 copy, 1.4 Mb and 18 kb respectively, sample 04-018, Fig. S4), all of which are located in or bounded by regions of low copy repeats (LCRs). In addition, a previous known homozygous deletion of 975 bp (in 04-018 and 05-050) was again accurately demonstrated (05-050 data showed in Fig. 4c), although sometimes (04-018) the data was a little noisier than with unamplified DNA (Fig. S4d). In contrast, the Wpa-40oC resulted in abundant signal noise and failed in detection of these copy number aberrations (Fig. 4, Fig. S3, S4). Impressively, HR-CGH with 0.5 ng gDNA-derived amplicons via Wpa also clearly detected the known CNVs, although noisier (Fig. S4). The 0.1ng gDNA derived amplicons via Wpa could not unambiguously show CNVs because of higher variability of signals, but the CNVs’ patterns were mostly well maintained (Fig. S4 for 04-018). We did also notice some locus-imbalance in the amplicon, however this was minimized, and was reproducible when the input was above a certain threshold amount, and it could be well compensated if the same amplified reference sample was applied in parallel as showed above. Keywords: Whole-pool amplification, high resolution comparative genome hybridization (HR-CGH)