3311 results for "*geneti*"

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• June 2016 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2016 data update (bam/fastq for CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087 ChIP-Seq and RNA-Seq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002239

• RNA-seq and Hi-C data of a chromothripsis patient's iPS cells

  This dataset contains RNA-seq and Hi-C data files of induced pluripotent stem (iPS) cells and iPS cell-derived neural progenitors (NPCs) derived from a germline chromothripsis patient and both parents. iPS cells of the patient (cell lines 14 and 15), the father (lines 23 (with two replicates) and 32) and mother (line 30) were differentiated to NPCs and RNA was collected on day 0, day 7 and day 10 of differentiation. In addition, Hi-C data for two iPS cell-derived NPC lines from the patient (14 and 15) and two lines from the father (23 and 32) was generated.

  Dataset EGAD00001002242

• Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES)

  The T2D-GENES/GoT2D 13K exome sequencing study includes ~13,000 samples, half T2D cases and half T2D controls, from five ancestries (~5K Europeans, ~2K each of African-American, East-Asian, South-Asian, and Hispanic). Samples underwent deep exome sequencing, with SNVs and INDEls called according to GATK best practices; variant sites were then filtered according to the GATK best practices, and then samples and variants underwent further filtering based on aggregate genotype quality as described in Fuchsberger et al. (e.g. low call rate, excess heterozygosity for samples, low call rate or coverage for variants). Please note that one of the samples in the T2D-GENES vcf does not have phenotype data.

  Dataset EGAD00001002246

• GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes

  The GoT2D study includes ~2800 samples, half T2D cases and half T2D controls, of Northern European ancestry sequenced over 3 three technologies: deep whole exome sequencing, low-pass (4x) whole genome sequencing, and OMNI 2.5M genotyping. Samples were ascertained to be phenotypically "extreme" (e.g. leaner, younger cases and older, more obese controls). Genotypes (SNVs, INDELs, and SVs) were called separately for each technology and then integrated via genotype refinement into a single phased reference panel; samples and variants were then excluded based on QC procedures described in Fuchsberger et al. Please note that 2 of the samples in the GoT2D vcf do not have phenotype data.

  Dataset EGAD00001002247

• Genetics and Networks of Congenital Heart Defects

  Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation.

  Dataset EGAD00001002251

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq EAC expression data - Publication Secrier & Li et al., 2016, Nature Genetics

  Dataset EGAD00001002260

• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues.

  Dataset EGAD00001002266

• Chad genetic diversity reveals an African history marked by multiple Holocene Eurasian migrations

  Whole-genome sequencing data from Chad and Lebanon.

  Dataset EGAD00001002742

• BLUEPRINT: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cells (WGS)

  BLUEPRINT: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cells (WGS)

  Dataset EGAD00001002663

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for mature neutrophil, on genome GRCh37)

  ChIP-Seq data for 182 mature neutrophil sample(s). 2847 run(s), 366 experiment(s), 355 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002670

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  RNA-Seq data for 212 CD4-positive, alpha-beta T cell sample(s). 212 run(s), 212 experiment(s), 212 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002671

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  ChIP-Seq data for 154 CD4-positive, alpha-beta T cell sample(s). 355 run(s), 265 experiment(s), 250 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002673

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for mature neutrophil, on genome GRCh37)

  RNA-Seq data for 205 mature neutrophil sample(s). 205 run(s), 205 experiment(s), 205 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002675

• Data files for PCGP SJACT WES

  This dataset contains WES files for the SJACT cohort associated with the paper "Genetic landscape of pediatric Adrenocortical Tumor". In this paper, we analyse 37 adrenocortical tumours (ACTs) by whole-genome, whole-exome and/or transcriptome sequencing.

  Dataset EGAD00001002679

• Data files for PCGP SJACT RNASEQ

  This dataset contains RNA-Seq files for the SJACT cohort associated with the paper "Genetic landscape of pediatric Adrenocortical Tumor". In this paper, we analyse 37 adrenocortical tumours (ACTs) by whole-genome, whole-exome and/or transcriptome sequencing.

  Dataset EGAD00001002680

• Epigenome maps of time-resolved monocyte to macrophage differentiation and innate immune memory

  Innate immune memory is the phenomenon whereby innate immune cells such as monocytes or macrophages undergo functional reprogramming after exposure to microbial components such as LPS. We apply an integrated epigenomic approach to characterize the molecular events involved in LPS-induced tolerance in a time dependent manner. ChIP-seq, RNA-seq, WGBS and ATAC-seq data were generated. This analysis identified epigenetic programs in tolerance and trained macrophages, and the potential transcription factors involved. Experimental set-up Time-course in vitro culture of human monocytes. Two innate immune memory states can be induced in culture through an initial exposure of primary human monocytes to either LPS or BG for 24 hours, followed by removal of stimulus and differentiation to macrophages for an additional 5 days. Cells were collected at baseline (day 0), 1 hour, 4 hour, 24 hour and 6 days.

  Dataset EGAD00001002693

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cells, (ChIP-Seq_H3K4me3 for mature neutrophil, on genome GRCh37)

  ChIP-Seq_H3K4me3 data for 133 mature neutrophil sample(s). 208 run(s), 136 experiment(s), 136 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002711

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cells, (ChIP-Seq_H3K27me3 for mature neutrophil, on genome GRCh37)

  ChIP-Seq_H3K27me3 data for 131 mature neutrophil sample(s). 321 run(s), 134 experiment(s), 134 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002712

• September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002724

• Epigenetic dysregulation in autism spectrum disorder

  Autism spectrum disorder (ASD) is a collection of neuro-developmental disorders characterized by deficits in social interaction and social communication, along with restricted and repetitive behaviour patterns. we globally interrogated the histone acetylomes of enhancers in a large cohort of ASD and control samples by analyzing tissue from three brain regions postmortem: prefrontal cortex (PFC), temporal cortex (TC) and cerebellum (CB). H3K27ac was selected as the representative acetylation mark and 288 ChIP-seq were performed on these postmortem samples.

  Dataset EGAD00001002725

• Prognostic relevance of microenvironmental factors CD163 and CD8 combined with EZH2 and chromosome 18 gain in a validation cohort of follicular lymphoma patients of the Lunenburg Lymphoma Biomarker Consortium

  Background: In follicular lymphoma (FL), studies addressing the prognostic value of microenvironment-related immunohistochemical (IHC) markers and tumor cell-related genetic markers have yielded conflicting results, precluding implementation in practice. Therefore, the Lunenburg Lymphoma Biomarker Consortium (LLBC) performed a validation study for published markers. Methods: To maximize sensitivity, an end-of-spectrum design was applied for 122 uniformly immunochemotherapy-treated FL patients retrieved from international trials and registries; early failure (EF): progression or lymphoma-related death <2 years versus long remission: response duration of >5 years. IHC staining for T-cells and macrophages was performed on tissue microarrays from initial biopsy and scored with a validated computer-assisted protocol. Shallow whole-genome and deep targeted sequencing was performed on the same samples. Results: 96/122 cases with complete molecular and immunohistochemical data were included in the analysis. EZH2 wild-type (p=0.006), gain of chromosome 18 (p=0.002), low percentages of CD8+ cells (p=0.011) and CD163+ areas (p=0.038) were associated with EF. No significant differences in other markers were observed, thereby refuting previous claims on their prognostic significance. Conclusion: Using an optimized study design, this LLBC study validates wild-type EZH2 status, gain of chromosome 18, low percentages of CD8+ cells and CD163+ area as predictors of EF to immunochemotherapy in FL.

  Dataset EGAD00001002738

• A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing.

  Dataset EGAD00001002740

• Somatic genetic basis of Wilms’ tumour

  We investigated the somatic genetic basis of Wilms’ tumour and found complex phylogenetic relations between tumours.

  Dataset EGAD00001004774