16833 results for "sec+and+unspecified+malignant+neoplasm"

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• CPC-GENE H3K27ac ChIP-seq

  CPC-GENE H3K27ac ChIP-seq data comprises 48 tumour samples and 6 benign samples sequenced with single end Illumina HiSeq 2000.

  Dataset EGAD00001010296

• H3Africa SIREN Phenotype

  Phenotype data for 3421 Samples from Nigeria and Ghana, genotyped with the Illumina NestSeq 500.

  Dataset EGAD00001011075

• Covacta RNAseq merged EGA metadata

  Sample metadata for the RNA-seq dataset. This dataset includes subject-level data and longitudinal visit day information for the corresponding samples.

  Dataset EGAD00001011162

• Single molecule molecular inversion probe capture developed using the CIViC database

  This study evaluated the use of the Clinical Interpretations of Variants in Cancer database (CIViC) to develop an Open-sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP is a resource that allows users to develop a clinical capture panel that can be linked back to clinical summaries within the CIViC database. This method for capture panel development and variant annotation was tested using 27 cancer samples from 5 tumor subtypes with original exome or genome sequencing. Specifically, using OpenCAP, 111 variants were identified as relevant for the capture panel and 2,027 smMIPs were designed to target these variants. The smMIPs panel design was employed on all samples to validate the capture panel design. When compared to original sequencing, the CIViC smMIPs capture panel demonstrated a 95% sensitivity for variant detection (n = 61 variants). Additionally, the CIViC smMIPs capture panel identified 182 additional clinically relevant variants that had been missed on original sequencing.

  Study phs001890

• The Etiological Bases of Giftedness: Epidemiological Study of Cognitive Ability in Children in Saudi Arabia

  Recent studies of genetic foundations of cognitive ability rely on large samples (hundreds of thousands) of individuals from relatively outbred populations of mostly European ancestry. Hypothesizing that the genetic foundation of cognitive ability depends on the broader population-specific genetic context, we performed a genome-wide association study and homozygosity mapping of cognitive ability estimates obtained through latent variable modeling in a sample of 354 children from the consanguineous population of Saudi Arabia. Approximately half of the sample demonstrated significantly elevated homozygosity levels indicative of inbreeding, and among those with elevated homozygosity, it was negatively associated with cognitive ability. Further homozygosity mapping identified a specific run, inclusive of the GRIA4 gene, that survived corrections for multiple testing for association with cognitive ability. The results suggest that in a consanguineous population, a notable proportion of the variance in cognitive ability in the normal range in children might be regulated by population-specific mechanisms such as patterns of elevated autozygosity.

  Study phs001884

• Predictive impact of rare genomic copy number variations in siblings of individuals with autism spectrum disorders

  Identification of genetic biomarkers associated with autism spectrum disorders (ASDs) could improve recurrence prediction for families with a child with ASD. Here, we describe clinical microarray findings for 253 longitudinally phenotyped ASD families from the Baby Siblings Research Consortium (BSRC), encompassing 288 infant siblings. By age 3, 103 siblings (35.8%) were diagnosed with ASD and 54 (18.8%) were developing atypically. Thirteen siblings have copy number variants (CNVs) involving ASD-relevant genes: 6 with ASD, 5 atypically developing, and 2 typically developing. Within these families, an ASD-related CNV in a sibling has a positive predictive value (PPV) for ASD or atypical development of 0.83; the Simons Simplex Collection of ASD families shows similar PPVs. Polygenic risk analyses suggest that common genetic variants may also contribute to ASD. CNV findings would have been pre-symptomatically predictive of ASD or atypical development in 11 (7%) of the 157 BSRC siblings who were eventually diagnosed clinically.

  Study phs001876

• High-Throughput LINE-1 Retrotransposon Discovery in Humans

  The aim of this study is to discover LINE-1 (L1) insertion sites present in humans that are absent from the reference genome sequence. We use the distinguishing nucleotide characteristics of human-specific L1 elements to resequence the L1 3' flanking regions thus locating the L1 insertion sites whether or not they are present in the reference genome assembly. In doing so, we have uncovered a higher than expected number of non-reference L1 insertions, an average of 152 insertions per individual. In addition, we find that any two individuals differ at an average of 285 sites with respect to presence or absence of L1 insertions in those sites, and use this to estimate the rate of retrotransposition in humans at 1 event per 140 live births (95% c.i. 1/95 to 1/270). We show that individual 'L1 profiles' recapitulate genetic ancestry as expected, and find that dimorphic insertions are more frequent in introns relative to fixed insertions.

  Study phs000273

• Regulatory Genomics of Human Embryonic Development

  We used epigenetic profiling to map active enhancers in the developing human limb and cortex as described in two published studies: Cotney J, Leng J, Yin J, Reilly SK et al. The evolution of lineage-specific regulatory activities in the human embryonic limb. Cell 2013;154(1):185-96. Reilly SK, Yin J, Ayoub AE, Emera D et al. Evolutionary changes in promoter and enhancer activity during human corticogenesis. Science 2015;347(6226):1155-9. We also used ChIP-seq to map binding sites for the chromatin modifier CHD8 in the developing human brain, as described in one published study: Cotney J, Muhle RA, Sanders SJ, Liu L et al. The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment. Nat Commun 2015;6:6404. We are also depositing primary human sequence reads related to processed datasets in the Gene Expression Omnibus under the following accession numbers: GSE42413 (Cotney et al. 2013); GSE63649 (Reilly et al. 2015); GSE57369 (Cotney et al. 2015).

  Study phs001226

• Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

  While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE [Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics] project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis.

  Study phs001703

• Genome sequencing identifies splice-disrupting variants in childhood heart disease

  We used genome sequencing (GS) to identify cardiac specific splice disrupting variants that were subsequently validated in a subset of participants. In turn, we developed a heart-specific model for canonical and non-canonical splice variants, which was applied to patients with congenital heart disease (CHD). These included patients with two of the most common forms of cyanotic CHD i.e. tetralogy of Fallot (TOF) and dextro-transposition of the great arteries (TGA). In addition to identifying canonical splice-disrupting variants in known CHD-related genes in 1% cases, this approach identified putatively damaging non-canonical splice-disrupting variants in 11% of isolated CHD, with deeply intronic variants representing 53% of non-canonical splice-disrupting variants in CHD genes. GS was critical for the identification of variants that would not be captured by routine clinical genetic tests including exome sequencing, while cardiac RNA-Seq allowed for high specificity in the interpretation of splice-disrupting effects in the heart.

  Study EGAS50000000586