ArticleMethods in molecular biology (Clifton, N.J.)2012
Online resources for genomic structural variation.
Article in Methods in molecular biology (Clifton, N.J.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Overview of the genetic basis toward early detection of breast cancer.Breast cancer (Dove Medical Press) · 2019Review
- Deletion of REXO1L1 locus in a patient with malabsorption syndrome, growth retardation, and dysmorphic features: a novel recognizable microdeletion syndrome?BMC medical genetics · 2015Article
- Next-generation sequencing reveals novel rare fusion events with functional implication in prostate cancer.Oncogene · 2015Article
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Abstract
Genomic structural variation (SV) can be thought of on a continuum from a single base pair insertion/deletion (INDEL) to large megabase-scale rearrangements involving insertions, deletions, duplications, inversions, or translocations of whole chromosomes or chromosome arms. These variants can occur in coding or noncoding DNA, they can be inherited or arise sporadically in the germline or somatic cells. Many of these events are segregating in the population and can be considered common alleles while others are new alleles and thus rare events. All species studied to date harbor structural variants and these may be benign, contributing to phenotypes such as sensory perception and immunity, or pathogenic resulting in genomic disorders including DiGeorge/velocardiofacial, Smith-Margenis, Williams-Beuren, and Prader-Willi syndromes. As structural variants are identified, validated, and their significance, origin, and prevalence are elucidated, it is of critical importance that these data be collected and collated in a way that can be easily accessed and analyzed. This chapter describes current structural variation online resources (see Fig. 1 and Table 1), highlights the challenges in capturing, storing, and displaying SV data, and discusses how dbVar and DGVa, the genomic structural variation databases developed at NCBI and EBI, respectively, were designed to address these issues.
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