PEcnv: accurate and efficient detection of copy number variations of various lengths

Wang, Xuwen; Xu, Ying; Liu, Ruo-Yu; Lai, Xin; Liu, Yuqian; Wang, Shenjie; Zhang, Xuanping; Wang, Jiayin

doi:10.1093/bib/bbac375

Cited by 6 publications

(3 citation statements)

References 36 publications

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“…Taking CNV detection as an example, the size of sliding window is the crucial factor impacting the detection precision. Xuwen et al (56) have presented a CNV caller with a dynamic sliding window that automatically adjust the window size based on the length of CNV to achieve the optimal setting. The adaptive window with self-adopted size makes it capable of handling CNVs with various lengths ranging from kb-scale to chromosomearm level.…”

Section: Developing Novel Bioinformatics Tools With Error Controlmentioning

confidence: 99%

What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort

Liu

Wang

et al. 2023

Front. Immunol.

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Tumor mutation burden (TMB) is a widely recognized biomarker for predicting the efficacy of immunotherapy. However, its use still remains highly controversial. In this study, we examine the underlying causes of this controversy based on clinical needs. By tracing the source of the TMB errors and analyzing the design philosophy behind variant callers, we identify the conflict between the incompleteness of biostatistics rules and the variety of clinical samples as the critical issue that renders TMB an ambivalent biomarker. A series of experiments were conducted to illustrate the challenges of mutation detection in clinical practice. Additionally, we also discuss potential strategies for overcoming these conflict issues to enable the application of TMB in guiding decision-making in real clinical settings.

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Section: Developing Novel Bioinformatics Tools With Error Controlmentioning

confidence: 99%

What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort

Liu

Wang

et al. 2023

Front. Immunol.

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“…It can also find several other forms of gene structural variants. PEcnv [ 18 ] fills the gap in the recognition of small CNVs by detecting CNVs of varying sizes using a base coverage corrected model and a dynamic sliding window. IhybCNV [ 19 ] improves detection performance by integrating results from different detectors.…”

Section: Introductionmentioning

confidence: 99%

OTSUCNV: an adaptive segmentation and OTSU-based anomaly classification method for CNV detection using NGS data

Xie,

Ge,

Alvi

et al. 2024

BMC Genomics

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Copy-number variations (CNVs), which refer to deletions and duplications of chromosomal segments, represent a significant source of variation among individuals, contributing to human evolution and being implicated in various diseases ranging from mental illness and developmental disorders to cancer. Despite the development of several methods for detecting copy number variations based on next-generation sequencing (NGS) data, achieving robust detection performance for CNVs with arbitrary coverage and amplitude remains challenging due to the inherent complexity of sequencing samples. In this paper, we propose an alternative method called OTSUCNV for CNV detection on whole genome sequencing (WGS) data. This method utilizes a newly designed adaptive sequence segmentation algorithm and an OTSU-based CNV prediction algorithm, which does not rely on any distribution assumptions or involve complex outlier factor calculations. As a result, the effective detection of CNVs is achieved with lower computational complexity. The experimental results indicate that the proposed method demonstrates outstanding performance, and hence it may be used as an effective tool for CNV detection.

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“…Though this method has been widely used for signal processing, no study has reported its application in CNV peak detection and analysis. Currently, some of popular methods for detecting and analyzing CNVs include, but is not limited to, CNVkit [22], Control-FREEC [23], iCopyDAV [24], PEcnv [25] and CNV_IFTV [26]. Each of these methods has its own characteristics and advantages.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Savitzky–Golay Filters for Analysis of Copy Number Variation Peaks from Whole-Exome Sequencing Data

et al. 2023

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Copy number variation (CNV) is a form of structural variation in the human genome that provides medical insight into complex human diseases; while whole-genome sequencing is becoming more affordable, whole-exome sequencing (WES) remains an important tool in clinical diagnostics. Because of its discontinuous nature and unique characteristics of sparse target-enrichment-based WES data, the analysis and detection of CNV peaks remain difficult tasks. The Savitzky–Golay (SG) smoothing is well known as a fast and efficient smoothing method. However, no study has documented the use of this technique for CNV peak detection. It is well known that the effectiveness of the classical SG filter depends on the proper selection of the window length and polynomial degree, which should correspond with the scale of the peak because, in the case of peaks with a high rate of change, the effectiveness of the filter could be restricted. Based on the Savitzky–Golay algorithm, this paper introduces a novel adaptive method to smooth irregular peak distributions. The proposed method ensures high-precision noise reduction by dynamically modifying the results of the prior smoothing to automatically adjust parameters. Our method offers an additional feature extraction technique based on density and Euclidean distance. In comparison to classical Savitzky–Golay filtering and other peer filtering methods, the performance evaluation demonstrates that adaptive Savitzky–Golay filtering performs better. According to experimental results, our method effectively detects CNV peaks across all genomic segments for both short and long tags, with minimal peak height fidelity values (i.e., low estimation bias). As a result, we clearly demonstrate how well the adaptive Savitzky–Golay filtering method works and how its use in the detection of CNV peaks can complement the existing techniques used in CNV peak analysis.

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PEcnv: accurate and efficient detection of copy number variations of various lengths

Cited by 6 publications

References 36 publications

What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort

What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort

OTSUCNV: an adaptive segmentation and OTSU-based anomaly classification method for CNV detection using NGS data

Adaptive Savitzky–Golay Filters for Analysis of Copy Number Variation Peaks from Whole-Exome Sequencing Data

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