scholarly journals MCKAT: a multi-dimensional copy number variant kernel association test

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Nastaran Maus Esfahani ◽  
Daniel Catchpoole ◽  
Javed Khan ◽  
Paul J. Kennedy
Keyword(s):  
Copy Number ◽  
Kernel Method ◽  
Random Effect ◽  
Random Effect Model ◽  
Score Test ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
Association Test ◽  
Single Pair ◽  
Related Trait

Abstract Background Copy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia. Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods. Results We address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets. Conclusion A multi-dimensional copy number variant kernel association test can detect statistically significant associated CNV regions with any disease-related trait. MCKAT can provide biologists with CNV hot spots at the cytogenetic band level that CNVs on them may have a significant association with disease-related traits. Using MCKAT, biologists can narrow their investigation from the whole genome, including many genes and CNVs, to more specific cytogenetic bands that MCKAT identifies. Furthermore, MCKAT can help biologists detect significantly associated CNVs with disease-related traits across a patient group instead of examining each subject’s CNVs case by case.

scholarly journals MCKAT, a multi-dimensional copy number variant kernel association test

2021 ◽  
Author(s):  
Nastaran Maus Esfahani ◽  
Daniel Catchpoole ◽  
Javed Khan ◽  
Paul J. Kennedy
Keyword(s):  
Copy Number ◽  
Kernel Method ◽  
Random Effect ◽  
Random Effect Model ◽  
Score Test ◽  
Copy Number Variant ◽  
Association Test ◽  
P Value ◽  
Single Pair ◽  
Related Trait

AbstractBackgroundCopy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia.Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods.ResultsWe address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets.ConclusionA multi-dimensional copy number variant kernel association test can detect significantly associated CNVs with any disease-related trait. MCKAT can help biologists detect significantly associated CNVs with any disease-related trait across a patient group instead of examining the CNVs case by case in each subject.

scholarly journals SMCKAT, a Sequential Multi-Dimensional CNV Kernel-Based Association Test

Life ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1302
Author(s):  
Nastaran Maus Esfahani ◽  
Daniel Catchpoole ◽  
Paul J. Kennedy
Keyword(s):  
Random Effect ◽  
Random Effect Model ◽  
Copy Number Variants ◽  
Association Test ◽  
Biomedical Literature ◽  
Data Sets ◽  
Whole Genome ◽  
Sequential Order ◽  
Single Chromosome ◽  
Biologically Relevant

Copy number variants (CNVs) are the most common form of structural genetic variation, reflecting the gain or loss of DNA segments compared with a reference genome. Studies have identified CNV association with different diseases. However, the association between the sequential order of CNVs and disease-related traits has not been studied, to our knowledge, and it is still unclear that CNVs function individually or whether they work in coordination with other CNVs to manifest a disease or trait. Consequently, we propose the first such method to test the association between the sequential order of CNVs and diseases. Our sequential multi-dimensional CNV kernel-based association test (SMCKAT) consists of three parts: (1) a single CNV group kernel measuring the similarity between two groups of CNVs; (2) a whole genome group kernel that aggregates several single group kernels to summarize the similarity between CNV groups in a single chromosome or the whole genome; and (3) an association test between the CNV sequential order and disease-related traits using a random effect model. We evaluate SMCKAT on CNV data sets exhibiting rare or common CNVs, demonstrating that it can detect specific biologically relevant chromosomal regions supported by the biomedical literature. We compare the performance of SMCKAT with MCKAT, a multi-dimensional kernel association test. Based on the results, SMCKAT can detect more specific chromosomal regions compared with MCKAT that not only have CNV characteristics, but the CNV order on them are significantly associated with the disease-related trait.

scholarly journals Exome sequencing in patients with antiepileptic drug exposure and complex phenotypes

2019 ◽  
Vol 105 (4) ◽  
pp. 384-389 ◽  
Author(s):  
Adam Jackson ◽  
Heather Ward ◽  
Rebecca Louise Bromley ◽  
Charulata Deshpande ◽  
Pradeep Vasudevan ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Copy Number ◽  
Developmental Disorders ◽  
Drug Exposure ◽  
Genetic Disorders ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
In Utero ◽  
Developmental Problems ◽  
Number Of Children

IntroductionFetal anticonvulsant syndrome (FACS) describes the pattern of physical and developmental problems seen in those children exposed to certain antiepileptic drugs (AEDs) in utero. The diagnosis of FACS is a clinical one and so excluding alternative diagnoses such as genetic disorders is essential.MethodsWe reviewed the pathogenicity of reported variants identified on exome sequencing in the Deciphering Developmental Disorders (DDD) Study in 42 children exposed to AEDs in utero, but where a diagnosis other than FACS was suspected. In addition, we analysed chromosome microarray data from 10 patients with FACS seen in a Regional Genetics Service.ResultsSeven children (17%) from the DDD Study had a copy number variant or pathogenic variant in a developmental disorder gene which was considered to explain or partially explain their phenotype. Across the AED exposure types, variants were found in 2/15 (13%) valproate exposed cases and 3/14 (21%) carbamazepine exposed cases. No pathogenic copy number variants were identified in our local sample (n=10).ConclusionsThis study is the first of its kind to analyse the exomes of children with developmental disorders who were exposed to AEDs in utero. Though we acknowledge that the results are subject to bias, a significant number of children were identified with alternate diagnoses which had an impact on counselling and management. We suggest that consideration is given to performing whole exome sequencing as part of the diagnostic work-up for children exposed to AEDs in utero.

scholarly journals Detection and characterization of copy number variants based on whole-genome sequencing by DNBSEQ platforms

2019 ◽  
Author(s):  
Junhua Rao ◽  
Lihua Peng ◽  
Fang Chen ◽  
Hui Jiang ◽  
Chunyu Geng ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
Whole Genome ◽  
Genome Wide ◽  
Wide Range ◽  
Distribution Sensitivity ◽  
Cnv Detection

AbstractBackgroundNext-generation sequence (NGS) has rapidly developed in past years which makes whole-genome sequencing (WGS) becoming a more cost- and time-efficient choice in wide range of biological researches. We usually focus on some variant detection via WGS data, such as detection of single nucleotide polymorphism (SNP), insertion and deletion (Indel) and copy number variant (CNV), which playing an important role in many human diseases. However, the feasibility of CNV detection based on WGS by DNBSEQ™ platforms was unclear. We systematically analysed the genome-wide CNV detection power of DNBSEQ™ platforms and Illumina platforms on NA12878 with five commonly used tools, respectively.ResultsDNBSEQ™ platforms showed stable ability to detect slighter more CNVs on genome-wide (average 1.24-fold than Illumina platforms). Then, CNVs based on DNBSEQ™ platforms and Illumina platforms were evaluated with two public benchmarks of NA12878, respectively. DNBSEQ™ and Illumina platforms showed similar sensitivities and precisions on both two benchmarks. Further, the difference between tools for CNV detection was analyzed, and indicated the selection of tool for CNV detection could affected the CNV performance, such as count, distribution, sensitivity and precision.ConclusionThe major contribution of this paper is providing a comprehensive guide for CNV detection based on WGS by DNBSEQ™ platforms for the first time.

scholarly journals HandyCNV: Standardized Summary, Annotation, Comparison, and Visualization of Copy Number Variant, Copy Number Variation Region, and Runs of Homozygosity

2021 ◽  
Vol 12 ◽  
Author(s):  
Jinghang Zhou ◽  
Liyuan Liu ◽  
Thomas J. Lopdell ◽  
Dorian J. Garrick ◽  
Yuangang Shi
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
R Package ◽  
Copy Number Variation Region ◽  
Runs Of Homozygosity ◽  
Number Variation ◽  
Genomic Studies ◽  
Computing Platforms ◽  
Analysis System

Detection of CNVs (copy number variants) and ROH (runs of homozygosity) from SNP (single nucleotide polymorphism) genotyping data is often required in genomic studies. The post-analysis of CNV and ROH generally involves many steps, potentially across multiple computing platforms, which requires the researchers to be familiar with many different tools. In order to get around this problem and improve research efficiency, we present an R package that integrates the summarization, annotation, map conversion, comparison and visualization functions involved in studies of CNV and ROH. This one-stop post-analysis system is standardized, comprehensive, reproducible, timesaving, and user-friendly for researchers in humans and most diploid livestock species.

scholarly journals The prenatal diagnosis and clinical outcomes of fetuses with 15q11.2 copy number variants: a case series of 36 patients

2021 ◽  
Author(s):  
Jessica Kang ◽  
Chien Nan Lee ◽  
Yi-Ning Su ◽  
Ming-Wei Lin ◽  
Yi-Yun Tai ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Developmental Delay ◽  
Copy Number ◽  
De Novo ◽  
Copy Number Variants ◽  
Case Series ◽  
Copy Number Variant ◽  
University Hospital ◽  
Limited Information ◽  
Ultrasound Findings

Objective: The prenatal genetic counseling of fetus diagnosed with the 15q11.2 copy number variant (CNV) involving the BP1-BP2 region has been difficult due to limited information and controversial opinion on prognosis. Design: Case series. Setting: This study uses data from National Taiwan University Hospital. Sample: Data of 36 pregnant women who underwent prenatal microarray analysis from 2012 to 2017 and were assessed at National Taiwan University Hospital. Methods: Data were collected by reviewing patients’ medical record. Comparison of patient characteristics, prenatal ultrasound findings and postnatal outcomes between different cases involving the 15q11.2 BP1-BP2 region were presented. Main outcome measured: Postnatal prognosis. Results: Out of the 36 patients diagnosed with CNVs involving the BP1-BP2 region, 5 were diagnosed with microduplication and 31 with microdeletion. Abnormal ultrasound findings were recorded in 12 cases prenatally. De novo microduplications were observed in 25% of the cases and microdeletions were found in 14%. Amongst the cases, 10 pregnant women received termination of pregnancy and 26 gave birth to healthy individuals (27 babies in total). Conclusion: The prognoses of 15q11.2 CNVs were controversial and recent studies have revealed its connection with developmental delay and autism. In our study, no obvious developmental delay or neurological disorders were detected postnatally in the 1 case of 15q11.2 microduplication and 25 cases of microdeletion.

scholarly journals Validity of the Family‐Based Association Test for Copy Number Variant Data in the Case of Non‐Linear Intensity‐Genotype Relationship

2012 ◽  
Vol 36 (8) ◽  
pp. 895-898 ◽  
Author(s):  
Manuela Zanda ◽  
Suna Onengut ◽  
Neil Walker ◽  
John A. Todd ◽  
David G. Clayton ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Variant ◽  
Association Test ◽  
The Family ◽  
Non Linear ◽  
Family Based ◽  
Linear Intensity

scholarly journals Association test using Copy Number Profile Curves (CONCUR) enhances power in rare copy number variant analysis

2020 ◽  
Vol 16 (5) ◽  
pp. e1007797
Author(s):  
Amanda Brucker ◽  
Wenbin Lu ◽  
Rachel Marceau West ◽  
Qi-You Yu ◽  
Chuhsing Kate Hsiao ◽  
...  
Keyword(s):  
Copy Number ◽  
Copy Number Variant ◽  
Association Test ◽  
Copy Number Profile ◽  
Variant Analysis

scholarly journals Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease

2018 ◽  
Author(s):  
Andrew M Gross ◽  
Subramanian S. Ajay ◽  
Vani Rajan ◽  
Carolyn Brown ◽  
Krista Bluske ◽  
...  
Keyword(s):  
Copy Number ◽  
De Novo ◽  
Genetic Disorders ◽  
Diagnostic Testing ◽  
Copy Number Variants ◽  
Uniparental Disomy ◽  
Copy Number Variant ◽  
Break Point ◽  
Clinically Significant ◽  
Family Based

AbstractPurposeCurrent diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, whole genome sequencing (WGS) has the potential to detect all genomic mutation types on a single platform and workflow. Here we sought to evaluate copy number variant (CNV) calling as part of a clinically accredited WGS test.MethodsUsing a depth-based copy number caller we performed analytical validation of CNV calling on a reference panel of 17 samples, compared the sensitivity of WGS-based variants to those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis, annotation, filtering, visualization of WGS based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.ResultsWe found that CNV calls from WGS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed. This pipeline also enabled identification of cases of uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of some CNVs enabled break-point level resolution of genomic rearrangements and phasing of de-novo CNVs.ConclusionRobust identification of CNVs by WGS is possible within a clinical testing environment, and further developments will bring improvements in resolution of smaller and more complex CNVs.

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