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17 de ago. de 2020 · Abstract. Autism spectrum disorder (ASD) has phenotypically and genetically heterogeneous characteristics. A simulation study demonstrated that attempts to categorize patients with a complex ...
17 de ago. de 2020 · We conducted cluster analyses using the k-means algorithm with a cluster number of 15 based on phenotypic variables from the Simons Simplex Collection (SSC). As a preliminary study, we conducted a conventional genome-wide association study (GWAS) with a data set of 597 ASD cases and 370 controls. In the second step, we divided cases based on ...
17 de ago. de 2020 · As a preliminary study, we conducted a conventional genome-wide association study (GWAS) with a data set of 597 ASD cases and 370 controls. In the second step, we divided cases based on the clustering results and conducted GWAS in each of the subgroups vs controls (cluster-based GWAS).
22 de abr. de 2019 · Herein, we performed a genome-wide association study (GWAS) to detect potential genetic variation and candidate genes underlying the phenotypic records at different parities for PU and FI in a ...
30 de nov. de 2019 · Autism spectrum disorder (ASD) has phenotypically and genetically heterogeneous characteristics. Here, we show a two-step genome-wide association study (GWAS). We used two datasets: one genotyped with the Illumina Human Omni2.5 (Omni2.5) in the discovery stage, and the other genotyped with the Illumina BeadChip 1Mv3 (1Mv3) in the replication stage. In the first step in the discovery stage, we ...
22 de abr. de 2019 · Autism spectrum disorder (ASD) has clinically and genetically heterogeneous characteristics. Here, we show a two-step genome-wide association study (GWAS). In the first step, we observed no significant associations in a GWAS including 597 cases and 370 controls. In the second step, we conducted a cluster analysis using k-means with 15 clusters based on Autism Diagnostic Interview-Revised (ADI ...
22 de abr. de 2019 · Clustering by phenotype and genome-wide association study in autism. The findings suggest that clustering may successfully identify subgroups with relatively homogeneous disease etiologies and that attempts to categorize patients with a complex disease into more homogeneous subgroups could have more power to elucidate hidden heritability. Expand.
