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• Reference epigenome KNIH009 WGBS data generated from KEP study

  A KNIH009 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for preadipocytes

  Dataset EGAD00001002757

• RNASeq_EGAS00001001306

  RNASeq sequencing. Each library was sequenced using TruSeq SBS Kit v3-HS, in paired-end mode with a read length of 2 × 76 bp. We generated more than 20 million paired-end reads for each sample in a fraction of a sequencing lane on HiSeq2000 (Illumina Inc.) following the manufacturer’s protocol. Image analysis, base calling and quality scoring of the run were processed using the manufacturer’s software Real Time Analysis (RTA 1.13.48) and followed by generation of FASTQ sequence files.

  Dataset EGAD00001001443

• UK10K NEURO ABERDEEN

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This sample set comprises cases of schizophrenia with additional cognitive measurements, collected in Aberdeen, Scotland.For further information on the Aberdeen cohort please contact David St Clair (d.stclair@abdn.ac.uk).

  Study EGAS00001000109

• UK10K RARE CHD

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The CHD (congenital heart disease) samples will be part of the “rare disease” group, and will undergo exome sequencing.For further information with regard to this cohort please contact Shoumo Bhattacharya (shoumo@me.com).

  Study EGAS00001000125

• Single-Cell Mitochondrial Mutation Lineage Tracing of Non-Dysplastic and Dysplastic Barrett's Esophagus

  This study addresses a critical knowledge gap in understanding Barrett's esophagus (BE), a common metaplastic condition and precursor to esophageal adenocarcinoma, by identifying lineage connections and cell states underlying its development and malignant transformation. We collected biopsies from 13 Barrett's esophagus patients undergoing routine surveillance endoscopy, sampling metaplastic tissue alongside normal squamous esophagus and gastric cardia tissues when clinically appropriate. Our novel approach integrated single-cell RNA sequencing of nearly 180,000 cells with mitochondrial DNA mutation analysis for lineage tracing, coupled with spatial transcriptomics and comprehensive whole-exome sequencing. For one patient with high-grade dysplasia, we performed detailed whole-exome sequencing analysis at 100x coverage on dissociated Barrett's esophagus cells alongside matched normal esophagus and gastric cardia tissues. This genomic profiling revealed critical genetic drivers of malignant transformation, including a truncating mutation in the mutation cluster region of APC (a negative WNT regulator), mutations in the tumor suppressor genes CDKN2A and TP53, and significant copy number alterations including loss of CDKN2A on chromosome 9. These genetic alterations corresponded with the transcriptional changes observed in our single-cell data, particularly WNT pathway dysregulation and the expansion of LGR5-expressing stem cells, providing molecular evidence for how single clones can initiate the dysplastic transformation. Data deposited in dbGaP consist specifically of the whole-exome sequencing raw files, processed variant calls, and copy number analyses from the single patient with high-grade dysplasia and matched normal esophagus and stomach control tissue. Whole exome sequencing was performed on an Illumina NovaSeq 6000. Sequencing data was preprocessed following the Genome Analysis Toolkit's (GATK) Best Practices. Sequencing data was analyzed with Mutect2 (GATK, v4.2.5.0) to identify short somatic mutations including single-nucleotide polymorphisms and insertions and deletions. The Barrett's esophagus sample was run with the two matched normals, as well as the publicly available germline resource somatic-hg38_af-only-gnomad.hg38.vcf.gz (GATK). Somatic variant calls were filtered using FilterMutectCalls (GATK) and loaded into the Integrative Genomics Viewer (v2.12.3) for identification of high-quality variants in known esophageal adenocarcinoma regulators. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9). CNV, Mutect2, and SVC analyses will be made available through dbGAP. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9) with the default run settings; a pooled reference was generated from the normal esophagus and stomach samples. Copy number results were plotted directly within CNVkit using the function scatter.

  Study phs003949

• The dataset of Southeast Borneo individuals (Banjar and Ngaju ethnic groups) was used as comparative data to determine the Asian parental population of the Malagasy. Our study found strong support for an origin of the Asian ancestry of Malagasy among the Banjar.

  Malagasy genetic diversity results from an exceptional proto-globalisation process that took place over a thousand years ago across the Indian Ocean. Previous efforts to locate the Asian origin of Malagasy have highlighted Borneo broadly as a potential source, but so far no firm source populations have been identified. Here, we have generated genome-wide data from two Southeast Borneo populations, the Banjar and the Ngaju, together with published data compiled from populations across the Indian Ocean region. We find strong support for an origin of the Asian ancestry of Malagasy among the Banjar. This group emerged from the long-standing presence of a Malay Empire trading post in Southeast Borneo, which favoured admixture between the Malay and an autochthonous Borneo group, the Ma’anyan. Reconciling genetic, historical and linguistic data, we show that the Banjar, in Malay-led voyages, were the most probable Asian source among the analysed groups in the founding of the Malagasy gene pool.

  Study EGAS00001001841

• Somatic Mutations in Epilepsy: Whole Genome Sequence Analysis of Single Neurons

  Low-coverage whole-genome sequencing was performed on single-cells from resected brain tissues obtained from an individual with hemimegalencephaly (HMG) along with a somatic copy number variant (sCNV) of chromosome 1q in order to characterize the sCNV at the single cell level. Single neuronal nuclei and non-neuronal nuclei were isolated by fluorescence-activated cell sorting (FACS) using NeuN immunoreactivity to identify neurons. 46 neurons and 30 non-neuronal cells, as well as a batch of 10 and a batch of 100 cells from each group, were genome amplified using multiple displacement amplification (MDA) and sequenced on an Illumina HiSeq 2000 sequencer. Thirty-two samples were multiplexed into each HiSeq lane for single-end 50 bp runs, obtaining ~5 million pass-filter reads per sample.

  Study phs002615

• Single-Cell Atlas of Human Liver and Blood Immune Cells Across Fatty Liver Disease Stages

  The goal of the study was to investigate immunological correlates of human fatty liver disease progression. We generated a single-cell RNA-seq (scRNA-seq) atlas of immune cells from liver fine needle aspirates (FNAs) and paired peripheral blood mononuclear cells (PBMCs) from a full-spectrum Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)/Metabolic Dysfunction-Associated Steatohepatitis (MASH) human cohort, using the 3' 10X Genomics platform. Using computational analyses to assess changes in cellular frequencies and function, we found heightened immunoregulatory programs with profibrotic potential alongside a shift from antigen-specific to natural killer cytotoxic functions in the liver with MASH progression. Available data include raw single-cell transcriptomic data (FASTQ files) for each sample type (PBMC, FNA) per patient alongside clinical and histological measurements of fatty liver disease.

  Study phs004044

• Baseline epigenetic clock measures in the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA)

  Epigenetic clock measures for a subset of 1,870 participants within the NICOLA cohort. The following epigenetic clocks were generated: (±PC)PhenoAge, (±PC)GrimAge, (±PC)Horvath1, (±PC)Hannum, PCDNAmTL and DunedinPACE. +PC represents the use of the principal component adjusted version of the clock.

  Dataset EGAD50000002063

• scRNA/TCR-seq of CD8+ T cells from a melanoma patient

  Specific in vitro stimulation of patient-derived PBMC with the neoantigens SYTL4-S363F and KIF2C-P13L was followed by enriching for CD137+ activated T cells. Restimulated T cells as well as an unstimulated patient PBMC sample from the same time point were used for scRNA-Seq/scTCR-Seq.

  Dataset EGAD50000000854

• Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

  Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

  Dataset EGAD00001005519

• RNA-sequencing

  RNA-sequencing for a cohort of B-ALL samples : 5 Down Syndrome (DS), 16 Hyperdiploid (HeH), 6 iAMP21, 9 other. RNA-sequencing for B-cell progenitors from 3 healthy. It also contains RNA-sequencing datasets of Patient-Derived Xenografts (X) developed from the B-ALL samples : 4 Down Syndrome (DS), 4 Hyperdiploid (HeH), 1 iAMP21, 3 other.

  Dataset EGAD00001005426

• Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections

  Advamced Visium Spatial Gene Expression assay for FFPE tissues with human and SARS-CoV-2 whole transcriptome (WT) information at a 55 µm resolution. The dataset consists of 13 tissue sections from 5 patient lung tissue samples, 3 from COVID-19 patients and 2 from control patients.

  Dataset EGAD00001008701

• CHROMATIN ACTIVATION PROFILING OF STEREOTYPED CHRONIC LYMPHOCYTIC LEUKEMIAS

  We used chromatin-immunoprecipitation followed by sequencing (ChIP-Seq) with an antibody for the H3K27ac (a bona fide histone mark for regulatory element activation) in sorted CLL cells from 15 CLL, including cases from stereotyped subsets #1, #2, #4, and #8. The samples were sequenced by Illumina HiSeq 2500.

  Dataset EGAD00001009082

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_C

  Dataset EGAD00001001706

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_F

  Dataset EGAD00001001707

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB21_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB21_M

  Dataset EGAD00001001705

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB21_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB21_F

  Dataset EGAD00001001704

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB21_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB21_C

  Dataset EGAD00001001703

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB1_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB1_M

  Dataset EGAD00001001702

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB1_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB1_F

  Dataset EGAD00001001701

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB1_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB1_C

  Dataset EGAD00001001700

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB15_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB15_M

  Dataset EGAD00001001699

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB15_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB15_F

  Dataset EGAD00001001698

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB15_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB15_C

  Dataset EGAD00001001697