| 1. |
- de Leeuw, Nicole, et al.
(författare)
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Diagnostic Interpretation of Array Data Using Public Databases and Internet Sources
- 2012
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Ingår i: Human Mutation. - : Hindawi Limited. - 1059-7794 .- 1098-1004. ; 33:6, s. 930-940
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Tidskriftsartikel (refereegranskat)abstract
- The range of commercially available array platforms and analysis software packages is expanding and their utility is improving, making reliable detection of copy-number variants (CNVs) relatively straightforward. Reliable interpretation of CNV data, however, is often difficult and requires expertise. With our knowledge of the human genome growing rapidly, applications for array testing continuously broadening, and the resolution of CNV detection increasing, this leads to great complexity in interpreting what can be daunting data. Correct CNV interpretation and optimal use of the genotype information provided by single-nucleotide polymorphism probes on an array depends largely on knowledge present in various resources. In addition to the availability of host laboratories' own datasets and national registries, there are several public databases and Internet resources with genotype and phenotype information that can be used for array data interpretation. With so many resources now available, it is important to know which are fit-for-purpose in a diagnostic setting. We summarize the characteristics of the most commonly used Internet databases and resources, and propose a general data interpretation strategy that can be used for comparative hybridization, comparative intensity, and genotype-based array data.
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| 2. |
- Miller, David T., et al.
(författare)
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Consensus Statement : Chromosomal Microarray Is a First-Tier Clinical Diagnostic Test for Individuals with Developmental Disabilities or Congenital Anomalies
- 2010
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 86:5, s. 749-764
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Tidskriftsartikel (refereegranskat)abstract
- Chromosomal microarray (CMA) is increasingly utilized for genetic testing of individuals with unexplained developmental delay/intellectual disability (DD/ID), autism spectrum disorders (ASD), or multiple congenital anomalies (MCA). Performing CMA and G-banded karyotyping on every patient substantially increases the total cost of genetic testing. The International Standard Cytogenomic Array (ISCA) Consortium held two international workshops and conducted a literature review of 33 studies, including 21,698 patients tested by CMA. We provide an evidence-based summary of clinical cytogenetic testing comparing CMA to G-banded karyotyping with respect to technical advantages and limitations, diagnostic yield for various types of chromosomal aberrations, and issues that affect test interpretation. CMA offers a much higher diagnostic yield (15%-20%) for genetic testing of individuals with unexplained DD/ID, ASD, or MCA than a G-banded karyotype (similar to 3%, excluding Down syndrome and other recognizable chromosomal syndromes), primarily because of its higher sensitivity for submicroscopic deletions and duplications. Truly balanced rearrangements and low-level mosaicism are generally not detectable by arrays, but these are relatively infrequent causes of abnormal phenotypes in this population (<1%). Available evidence strongly supports the use of CMA in place of G-banded karyotyping as the first-tier cytogenetic diagnostic test for patients with DD/ID, ASD, or MCA. G-banded karyotype analysis should be reserved for patients with obvious chromosomal syndromes (e.g., Down syndrome), a family history of chromosomal rearrangement, or a history of multiple miscarriages.
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| 3. |
- Szatmari, Peter, et al.
(författare)
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Mapping autism risk loci using genetic linkage and chromosomal rearrangements.
- 2007
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 39:3, s. 319-328
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Tidskriftsartikel (refereegranskat)abstract
- Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,168 families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.
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