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• The Ovarian Cancer Association Consortium OncoArray genome-wide association study

  A custom Illumina genotyping array, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis as described in PMID:27697780.The array was used to genotype ovarian cancer cases and controls from multiple studies participating in the Ovarian Cancer Association Consortium, of which 54,747 passes QC.An initial principal components analysis was carried out using a method described in PMID:27697780 to assign subject to intercontinental ancestry groups: “European”, “African”, “Asian” and "Other". Within ancestry principal components analysis was carried using a set of ~33k unlinked markers. Subsequent analyses were adjusted for the ancestry specific PCs: 9 Eur, 10 Asian, 1 African and 6 Mixed. These PCs are included in the imputed dataset phenotypes file

  Study EGAS00001002305

• MARS-seq dataset of five obese human subjects and a lean human subject

  Biopsies from visceral adipose tissue from the omental depot (OAT) were obtained from five obese individuals and one lean donor with participant informed consent obtained after the nature and possible consequences of the studies were explained under protocols approved by the Institutional Review Boards of the Perelman School of Medicine at the University of Pennsylvania, the Children’s Hospital of Philadelphia, or the Tel Aviv Sourasky Medical Center. The obese donors underwent bariatric surgery, the lean donor underwent cholecystectomy. OAT samples were placed in 1 mL of DMEM, and finely minced under sterile conditions before digestion in 50 mL of DMEM with 3 mg/1 mL collagenase IV (Gibco). Samples were incubated at 37°C in a rotating oven for 20-60 min. Adipocyte and stromal vascular fractions (SVF) were separated by centrifugation, and red blood cells (RBCs) were removed from the SVF by histopaque gradient (Sigma). Single-cell RNA-sequencing libraries were prepared using the MARS-seq pipeline, and sequenced on the MiSeq 500 or HiSeq 2500 Sequencing System (Illumina).

  Dataset EGAD00001005100

• Myeloid cell programming in patients with non-medullary thyroid carcinoma

  This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

  Dataset EGAD00001008108

• DNA methylation and transposable element landscapes define human regulatory T cells in tissues and identify their blood recirculating counterpart

  Regulatory T cells (Treg cells) in tissues can perform immunoregulatory and tissue-regenerative functions. Despite these important tasks, human-tissue Treg cells lack understanding, specifically, the epigenetic basis of their differentiation as well as re-circulating tissue-Treg cells are incompletely understood. Here, we performed genome-wide DNA methylation analysis of human Treg cells from skin and blood and embedded this in a multi-omic epigenetic framework including chromatin accessibility and gene-expression. We thereby revealed novel epigenetic programs defining human skin Treg cell differentiation and delineated how these are present on the different epigenetic levels. We discovered that transposable elements are an integral constituent of the demethylation landscape in skin Treg cells. Based on TCR-sequencing and DNA demethylation homologies, our data unveil that blood CCR8+ Treg cells are recirculatory human tissue-Treg cells. Our data provide novel insights in human tissue-Treg biology, required to harness these cells for therapeutic avenues.

  Study EGAS50000000738

• Next Generation Sequencing in an IBD Pedigree Whole Genome Data

  In 2009 we identified a four-generation family with over 700 members and 41 affected with Crohn's disease (CD). At the time we sequenced the exome of 6 affected individuals but did not identify any coding variants which appear to explain the high prevalence of disease. Since then we have collected DNA from a large number of additional family members, genotyped linkage arrays on the entire family to refine genomic regions shared by identity by descent and genotyped affected and unaffected members at known CD risk loci identified by Genome Wide Association Studies (GWAS). These analyses have confirmed that a significant unexplained excess of disease remains after accounting for all known genetic factors, and that several regions of the genome are shared by a large fraction of affected individuals. We therefore perform whole genomes sequencing from 8 individuals which will allow us to impute the complete sequence of nearly all the members of the two largest and most severely affected branches of the family.

  Dataset EGAD00001000399

• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  In many areas of oncology, we lack sensitive tools to track low burden disease. While cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low disease burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and post-operative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance, and empowering treatment optimization in low-disease burden oncology care

  Study EGAS00001004406

• Oxford Nanopore long-read sequencing data of high-grade serous ovarian cancer

  This dataset comprises whole-genome Oxford Nanopore long-read sequencing data from six high-grade serous ovarian cancer (HGSOC) patients, including cryopreserved, pre-treatment tumor tissues and matched peripheral blood samples (12 samples in total). High-molecular-weight DNA was prepared using the SQK-LSK114 Ligation Sequencing Kit and sequenced on FLO-PRO114M flow cells (R10.4.1). Basecalling was conducted using the super-accurate (SUP) model, enabling simultaneous detection of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). The dataset includes BAM files containing base modification information for downstream genomic and epigenomic analyses.

  Dataset EGAD50000001509

• RIP-SeqRaw data

  This dataset contains the raw count matrix generated in the PTBP1 project. Sequencing data were obtained from bulk directional RNA-seq and RIP-seq experiments performed on a NovaSeq 6000 platform (2×100 bp paired-end reads). Read counts were computed using HTSeq-count, without normalization. The dataset comprises two groups of samples: controls and patients. For each group, both input and immunoprecipitated samples are available. Patient samples correspond to skin biopsies from individuals affected by a neurodevelopmental disorder associated with variable skeletal dysplasia and disproportionate short-limbed short stature.

  Dataset EGAD50000001722

• Visium CytAssist Spatial Gene Expression analysis for glioblastoma

  The glioblastoma spatial transcriptomics dataset was generated from 4 FFPE fixed adult glioblastoma samples, using the 10x Genomics Visium platform, producing raw FASTQ files, spatial feature matrices (.h5, .mtx, .tsv), and paired histology images (.tif). Spot-level transcript counts were aligned to tissue architecture and processed in Seurat, with results stored as .rds objects. Data visualization was performed using SpatialFeaturePlot, and quantitative analyses were supported by custom Matlab scripts. The dataset provides both raw and processed files, offering reproducible spatially resolved transcriptomic profiles of glioblastoma tissue sections

  Dataset EGAD50000001767

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from diagnostic tumor samples of four B-other ALL patients (ALLT-314, ALLT-319, ALLT-327, ALLT-334), and from relapse sample of one B-other ALL patient (ALLT-316) . NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic and relapse tumor samples were sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb per sample.

  Dataset EGAD50000002598

• Peripheral immunoprofiling of stratifies COVID-19 patients based on disease-specific neutrophil signatures

  The SARS-CoV-2 pandemic has led to increasing numbers of COVID-19 patients all over the world. Aetiopathologies range from no symptoms, mild flu-like to severe cases succumbing to respiratory failure. Reports on a dysregulated immune system in the severe cases, showing similarities to cytokine release syndrome, calls for better characterization and understanding of the changes in the immune system as well as their variance across COVID-19 patients in order to be able to design according to host-directed therapies. Here, we profiled blood transcriptomes of 39 COVID-19 patients and 10 control donors. Enriched granulocyte signatures in whole blood samples were verified in granulocyte samples from 49 COVID-19 patients in a second cohort.

  Study EGAS00001004503

• Copy-number signatures and mutational processes in ovarian carcinoma

  This study contains the data underlying our approach for copy-number signature identification in high-grade serous ovarian cancer. The samples studied are part of the BriTROC-1 consortium, a national study into relapsed high-grade serous ovarian cancer. The dataset consists of shallow-whole genome sequencing of 300 samples from 143 patients with match tagged-amplicon sequencing of TP53. The study also contains deeper whole-genome sequencing of 48 cases.

  Study EGAS00001002557

• Distinct genomic profile and specific targeted drug responses in adult cerebellar glioblastoma

  Only a few studies have reported the molecular characteristics of adult cerebellar glioblastoma (C-GBM), a subtype comprising 1% of glioblastoma cases located within the infratentorial brain region due to the rarity. By identifying genomic profiles from 19 adult C-GBM samples, we revealed the genetic intertumoral heterogeneity in C-GBM as well as distinct genomic characteristics from those of supratentorial glioblastomas (S-GBMs), emphasizing the need of individualized therapies for C-GBM patients.

  Study EGAS00001002517

• Sorted WGS for three samples

  This dataset contains Whole Genome Sequencing (WGS) data from two cell populations (myeloid and lymphoid) and the germline population sorted from a primary sample of the novel FOXF1/FENDRR ALL subtype. All the three samples are in bam file type.

  Dataset EGAD50000001792

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-335). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002577

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-376). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002578

• RNA sequencing data of pediatric BCR::ABL1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one BCR::ABL1 ALL patient (ALLT-343). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002579

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one KMT2A-r ALL patient (ALLT-375). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002581

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a relapse sample of one ETV6::RUNX1 ALL patient (ALLT-341). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The relapse sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002588

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 5)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one ETV6::RUNX1 ALL patient (ALLT-380). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002591

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from diagnostic tumor samples of two B-other ALL patients (ALLT-369, ALLT-378). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor samples were sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002600

• Clonally heritable gene expression imparts a layer of diversity within cell types

  Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high coverage single cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying clonal human lymphocytes and mouse brain cells, we uncovered a vast diversity of heritable gene expression patterns among different clones of cells of the same type in vivo. We combined chromatin accessibility and RNA profiling on different lymphocyte clones to reveal thousands of regulatory regions exhibiting interclonal variation which could be directly linked to interclonal variation in gene expression. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging and disease.

  Study EGAS50000000161

• RNA-sequencing on thyroid samples from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality

  The current data pertains RNA-sequencing reads obtained from thyroid samples acquired from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality. Total RNA was isolated from left lobe from thyroid samples using a hand-held homogenizer and the Promega ReliaPrep RNA Miniprep System (Thermo Fisher Scientific). RNA yield was determined with the NanoDrop Microvolume Spectrophotometer (Thermo Fisher Scientific). Fragmentation and mRNA library preparation was performed using the Kapa mRNA Hyperprep Kit (Roche, Basel, Switzerland). Libraries were equimolar pooled and quality was checked on a TapeStation system using the DNA1000 ScreenTape (Agilent Technologies, Santa Clara, CA, USA). Libraries were sequenced with poly(A) selection to sequence all messenger RNA for gene expression analysis on the NovaSeq6000 PE150 (Illumina, San Diego, CA, USA), producing at least 40M 150-bp paired-end reads per library.

  Dataset EGAD50000000387

• The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

  Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

  Dataset EGAD00001015503

• The Natural History of Human Prostate Cancer

  Whole genome DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of 3 men. For each of three different prostates, multiple tumour samples (4, 5, and 3 depending on the case) and one normal tissue sample were whole genome sequenced with a matched blood sample using the Illumiuna HiSeq platform. Tumour samples were sequenced to a target depth of 50X and normals and blood to a target depth of 30X. As of September 2020, some of the studies using these data include: Cooper et al, Nature Genetics 2015 (PMID: 25730763) Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000689