17 research outputs found

    <i>De novo</i> CMA detected events are more enriched in GU patients than in individuals without urogenital abnormalities.

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    <p><i>Footnotes</i>: Two-tailed Fisher's exact test was used to evaluate the association of CMA detected <i>de novo</i> events with urogenital defects. *: GU cases (n = 90 out of the total of 116 analyzed GU children) and non GU controls (n = 8951) run only on CMA V.6.1 and CMA Oligo V6, since <i>de novo</i> events were specifically observed in GU patients screened with these two qualitatively comparable platforms (n = 10; see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0015392#pone-0015392-t006" target="_blank">Table 6</a>); <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0015392#pone.0015392-Ou1" target="_blank">[21]</a>. See Statistical Analysis in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0015392#s2" target="_blank">Methods</a> for details.</p

    Overlapping Chromosomal Rearrangements in DSD patients.

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    <p><b>A</b>. <b>Delineation of a minimal human 9p sex reversal deletion.</b> Schematic representation of the overlapping CMA detected 9p deletions in three unrelated 46,XY patients presenting with gonadal dysgenesis. A minimal common 260 Kb region was defined. Map showing the BAC clones covering the critical sex determination region and the normal flanking clones (RP11-459D20 and GS-43N6). A UCSC genome browser view (<i>May 2006</i> Human Assembly) of the <i>RefSeq</i> genes encompassing the minimal 9p24.3 sex-reversing region was presented. <b>B</b>. <b>Structural variation shared by unrelated patients presenting with distinct urogenital defects, may affect master regulator(s) of human genital development.</b> A common genomic interval of 65 Kb in the cytoband 5p15.31 was deleted in patient 6 with genital ambiguity and duplicated in patient 5 with hypospadias. CMA detection of the 65 Kb duplication in patient 5 and a UCSC genome browser view (<i>May 2006</i> Human Assembly) of the encompassed <i>ADCY2</i> gene were presented.</p

    <i>De novo</i> clinically relevant copy number changes detected in patients presenting with disorders of sex development (DSD).

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    <p> <i>Footnotes:</i></p><p>Minimal size of the spontaneous aberrations (Mb) and the number of the encompassing HGNC (Hugo Gene Nomenclature Committee) genes (G) (NCBI Build v35.1) were indicated.</p><p><i>P</i> values were based on two-tailed Fisher's exact test comparing the frequency of each spontaneous event in cases versus controls. Significance threshold was set at <i>P</i> = 5.0×10<sup>−2</sup>.</p><p>Abbreviations: Inh: Inheritance, <i>dn</i>: de novo.</p

    Comprehensive map of non-polymorphic copy number changes detected by CMA in patients with disorders of sex development.

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    <p>On the right, CMA detected imbalances were shown for each clinical condition (asterisks). To gain insight into the genomic distribution of the identified imbalances, all published single gene mutations associated with cryptorchidism (blue), hypospadias (green) and ambiguous genitalia (red) were reviewed and indicated on the left side of the chromosomes. References are available upon request.</p

    Fusion of Large-Scale Genomic Knowledge and Frequency Data Computationally Prioritizes Variants in Epilepsy

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    <div><p>Curation and interpretation of copy number variants identified by genome-wide testing is challenged by the large number of events harbored in each personal genome. Conventional determination of phenotypic relevance relies on patterns of higher frequency in affected individuals versus controls; however, an increasing amount of ascertained variation is rare or private to clans. Consequently, frequency data have less utility to resolve pathogenic from benign. One solution is disease-specific algorithms that leverage gene knowledge together with variant frequency to aid prioritization. We used large-scale resources including Gene Ontology, protein-protein interactions and other annotation systems together with a broad set of 83 genes with known associations to epilepsy to construct a pathogenicity score for the phenotype. We evaluated the score for all annotated human genes and applied Bayesian methods to combine the derived pathogenicity score with frequency information from our diagnostic laboratory. Analysis determined Bayes factors and posterior distributions for each gene. We applied our method to subjects with abnormal chromosomal microarray results and confirmed epilepsy diagnoses gathered by electronic medical record review. Genes deleted in our subjects with epilepsy had significantly higher pathogenicity scores and Bayes factors compared to subjects referred for non-neurologic indications. We also applied our scores to identify a recently validated epilepsy gene in a complex genomic region and to reveal candidate genes for epilepsy. We propose a potential use in clinical decision support for our results in the context of genome-wide screening. Our approach demonstrates the utility of integrative data in medical genomics.</p></div
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