inCNV: An Integrated Analysis Tool for Copy Number Variation on Whole Exome Sequencing

Chanwigoon, Saowwapark; Piwluang, Sakkayaphab; Wichadakul, Duangdao

doi:10.1177/1176934320956577

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…This indicates that high-throughput sequencing is an important part of the genetic characterization of ASD. Reliable methods for calling genic CNV from sequencing data have been established [ 49 – 52 ]; hence, there is good reason to use sequencing as a first-tier clinical approach, especially when one considers the co-occurrence of pdSNV and pdCNV in some subjects. The high rates of genetic findings in this epidemiological cohort provide a very strong rationale for developing precision medicine approaches in ASD, with treatment tailored to differences in underlying etiology and biology.…”

Section: Discussionmentioning

confidence: 99%

Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder

et al. 2021

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Background The Autism Sequencing Consortium identified 102 high-confidence autism spectrum disorder (ASD) genes, showing that individuals with ASD and with potentially damaging single nucleotide variation (pdSNV) in these genes had lower cognitive levels and delayed age at walking, when compared to ASD participants without pdSNV. Here, we made use of a Swedish sample of individuals with ASD (called PAGES, for Population-Based Autism Genetics & Environment Study) to evaluate the frequency of pdSNV and their impact on medical and psychiatric phenotypes, using an epidemiological frame and universal health reporting. We then combine findings with those for potentially damaging copy number variation (pdCNV). Methods SNV and CNV calls were generated from whole-exome sequencing and chromosome microarray data, respectively. Birth and medical register data were used to collect phenotypes. Results Of 808 individuals assessed by sequencing, 69 (9%) had pdSNV in the 102 ASC genes, and 144 (18%) had pdSNV in the 102 ASC genes or in a larger set of curated neurodevelopmental genes (from the Deciphering Developmental Disorders study, the gene2phenotype database, and the Radboud University gene lists). Three or more individuals had pdSNV in GRIN2B, POGZ, SATB1, DYNC1H1, SCN8A, or CREBBP. In comparison, out of the 996 individuals from whom CNV were called, 105 (11%) carried one or more pdCNV, including four or more individuals with CNV in the recurrent 15q11q13, 22q11.2, and 16p11.2 loci. Carriers of pdSNV were more likely to have intellectual disability (ID) and epilepsy, while carriers of pdCNV showed increased rates of congenital anomalies and scholastic skill disorders. Carriers of either pdSNV or pdCNV were more likely to have ID, scholastic skill disorders, and epilepsy. Limitations The cohort only included individuals with autistic disorder, the more severe form of ASD, and phenotypes are defined from medical registers. Not all genes studied are definitively ASD genes, and we did not have de novo information to aid in classification. Conclusions In this epidemiological sample, rare pdSNV were more common than pdCNV and the combined yield of potentially damaging variation was substantial at 27%. The results provide compelling rationale for the use of high-throughout sequencing as part of routine clinical workup for ASD and support the development of precision medicine in ASD.

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Section: Discussionmentioning

confidence: 99%

Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder

et al. 2021

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“…While often not explicitly labeled as visualization research contributions, bioinformatics tool developments often include such components. For this paper, the host of CNV visualization tools is the most relevant (e.g., [23]- [31]). NGS data related to CNVs are commonly displayed in a scatterplot where the coverage depth or copy ratio is presented along the genomic position [23], [26], [28], [32].…”

Section: Related Workmentioning

confidence: 99%

Visualization for Diagnostic Review of Copy Number Variants in Complex DNA Sequencing Data

Ståhlbom,

Molin,

Lundström

et al. 2024

IEEE Trans. Visual. Comput. Graphics

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Genomics is at the core of precision medicine, and there are high expectations on genomics-enabled improvement of patient outcomes in the years to come. Around the world, initiatives to increase the use of DNA sequencing in clinical routine are being deployed, such as the use of broad panels in the standard care for oncology patients. Such a development comes at the cost of increased demands on throughput in genomic data analysis. In this paper, we use the task of copy number variant (CNV) analysis as a context for exploring visualization concepts for clinical genomics. CNV calls are generated algorithmically, but time-consuming manual intervention is needed to separate relevant findings from irrelevant ones in the resulting large call candidate lists. We present a visualization environment, named Copycat, to support this review task in a clinical scenario. Key components are a scatter-glyph plot replacing the traditional list visualization, and a glyph representation designed for at-aglance relevance assessments. Moreover, we present results from a formative evaluation of the prototype by domain specialists, from which we elicit insights to guide both prototype improvements and visualization for clinical genomics in general.

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“…Efforts mainly residing in the bioinformatics research community often include tools to visualize genomics data as well. As our case study centers on CNV analysis, CNV visualization tools are the most relevant here ( Tebel et al, 2017 ; Sante et al, 2014 ; Macnee et al, 2022 ; Chandramohan et al, 2021 ; Markham et al, 2019 ; Ramesh et al, 2022 ; Ma et al, 2015 ; Zhou et al, 2021 ; Chanwigoon et al, 2020 ). Many tools target cohort analysis and other types of research-only use.…”

Section: Introductionmentioning

confidence: 99%

The thorny complexities of visualization research for clinical settings: A case study from genomics

et al. 2023

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In this perspective article we discuss a certain type of research on visualization for bioinformatics data, namely, methods targeting clinical use. We argue that in this subarea additional complex challenges come into play, particularly so in genomics. We here describe four such challenge areas, elicited from a domain characterization effort in clinical genomics. We also list opportunities for visualization research to address clinical challenges in genomics that were uncovered in the case study. The findings are shown to have parallels with experiences from the diagnostic imaging domain.

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inCNV: An Integrated Analysis Tool for Copy Number Variation on Whole Exome Sequencing

Cited by 4 publications

References 35 publications

Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder

Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder

Visualization for Diagnostic Review of Copy Number Variants in Complex DNA Sequencing Data

The thorny complexities of visualization research for clinical settings: A case study from genomics

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