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DNA Copy Number Variations

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Cancer type prediction based on copy number aberration and chromatin 3D structure with convolutional neural networks.

BMC genomics
BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have been produced that provides unprecedented opportunities for advanced association studies between somatic mutations and cancer types/subtypes which f...

ClinTAD: a tool for copy number variant interpretation in the context of topologically associated domains.

Journal of human genetics
Standard clinical interpretation of DNA copy number variants (CNVs) identified by cytogenomic microarray involves examining protein-coding genes within the region and comparison to other CNVs. Emerging basic research suggests that CNVs can also exert...

Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data.

Genes
It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrinsic differences are closely related to clinical diagnosis and designation of treatment plans. With the accumulation of biological and medicine datasets...

Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.

IEEE/ACM transactions on computational biology and bioinformatics
Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since thera...

EnsembleCNV: an ensemble machine learning algorithm to identify and genotype copy number variation using SNP array data.

Nucleic acids research
The associations between diseases/traits and copy number variants (CNVs) have not been systematically investigated in genome-wide association studies (GWASs), primarily due to a lack of robust and accurate tools for CNV genotyping. Herein, we propose...

A machine-learning approach for accurate detection of copy number variants from exome sequencing.

Genome research
Copy number variants (CNVs) are a major cause of several genetic disorders, making their detection an essential component of genetic analysis pipelines. Current methods for detecting CNVs from exome-sequencing data are limited by high false-positive ...

Risk stratification of cervical lesions using capture sequencing and machine learning method based on HPV and human integrated genomic profiles.

Carcinogenesis
From initial human papillomavirus (HPV) infection and precursor stages, the development of cervical cancer takes decades. High-sensitivity HPV DNA testing is currently recommended as primary screening method for cervical cancer, whereas better triage...

A Deep Learning Approach for Detecting Copy Number Variation in Next-Generation Sequencing Data.

G3 (Bethesda, Md.)
Copy number variants (CNV) are associated with phenotypic variation in several species. However, properly detecting changes in copy numbers of sequences remains a difficult problem, especially in lower quality or lower coverage next-generation sequen...

CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression.

IEEE/ACM transactions on computational biology and bioinformatics
Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiation and progression. Widely used methods, such as DNA arrays and genomic DNA sequencing, are relatively expensive and require DNA samples at a microgra...