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• DATA FILES FOR SJEWS-WGS

  DATA FILES FOR SJEWS-WGS

  Dataset EGAD00001001020

• DATA FILES FOR Histone Capture bams

  DATA FILES FOR Histone Capture bams

  Dataset EGAD00001000657

• SNP data for Ovarian cancer PRS

  SNP data for Ovarian cancer PRS (cases)

  Dataset EGAD00001008143

• Mutational Landscape and Tumor Burden Assessed by Cell-Free DNA in Diffuse Large B-Cell Lymphoma: a Population-based Study

  Purpose: We analyzed the utility of cfDNA in a prospective population-based cohort to determine the mutational profile, assess tumor burden, and estimate its impact in response rate and outcome in patients with DLBCL. Experimental Design: One-hundred patients were diagnosed with DLBCL during the study period. Mutational status of 112 genes was studied in cfDNA by targeted next-generation sequencing. Paired formalin-fixed paraffin-embedded samples and volumetric PET/CT were assessed when available. Results: Appropriate cfDNA to perform the analyses was obtained in 79/100 cases. At least one mutation could be detected in 69/79 cases (87%). The sensitivity of cfDNA to detect the mutations was 68% (95% CI: 56.2-78.7). The mutational landscape found in cfDNA samples was highly consistent with that shown in the tissue and allowed genetic classification in 43% of the cases. A higher amount of ctDNA significantly correlated with clinical parameters related to tumor burden (elevated LDH and β2-microglobulin serum levels, advanced stage, and high-risk IPI) and total metabolic tumor volume assessed by PET/CT. In patients treated with curative intent, high ctDNA levels (>2.5 log hGE/mL) were associated with lower complete response (65% vs. 96%, P<0.004), shorter progression-free survival (65% vs. 85%, P=0.038) and overall survival (73% vs. 100%, P=0.007) at 2 years, although it did not maintain prognostic value in multivariate analyses. Conclusions: In a population-based prospective DLBCL series, cfDNA resulted an alternative source to estimate tumor burden and to determine the tumor mutational profile and genetic classification, which have prognostic implications and may contribute to a future tailored

  Study EGAS00001004733

• WTCCC case-control study for Hypertension

  WTCCC genome-wide case-control association study for Hypertension (HT) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000009

• DAC for "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  This DAC will be created for sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas." The dataset includes Illumina-based exome sequencing of tumor specimens, paired blood specimens, bulk RNA-seq, and Visium FFPE.

  Dac EGAC50000000579

• BLUEPRINT September 2016, ATAC-seq for osteoclast from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for osteoclast from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002907

• BLUEPRINT September 2016, ATAC-seq for naive B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from tonsil, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002903

• BLUEPRINT September 2016, ATAC-seq Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002920

• BLUEPRINT September 2016, ATAC-seq for plasma cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for plasma cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002912

• A Phase I Study with a Personalized Neoantigen Cancer Vaccine in Melanoma

  Effective anti-tumor immunity in humans has been associated with presence of T cells targeting neoantigens that arise from non-silent tumor-specific mutations. Here we conducted whole-exome sequencing of tumor and normal cells from individual patients to identify mutations. We assessed the expression of mutated alleles by RNA-sequencing of tumor. We demonstrated the feasibility, safety and immunogenicity of a vaccine that targets up to 20 personal neoantigens predicted to be presented by the autologous patient tumor.Antigen-specific CD8+ T cells that can recognize and eliminate cancer cells play a crucial role in anti-tumor immune responses. Here we conducted single-cell sequencing of cells infiltrating melanoma specimens originating from 4 patients and determine the TCR clonality of the CD8+ tumor infiltrating cells. We investigated the relationship between T cell clonality and phenotypic cell states coupling single-cell transcriptome to single-cell TCR seq. The surface expression of a panel of protein was detected in parallel using CITE-Seq antibodies. Sorted tumor and peripheral blood specimens were processed in parallel.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out matched ribosome profiling (Ribo-seq), RNA-sequencing, and whole genome sequencing on one of the patients, as well as Ribo-seq on an additional patient. We used it to discover novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001451

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• Broad utility of ultrasensitive analysis of ctDNA dynamics across solid tumors treated with immunotherapy

  Prior studies have suggested the biomarker potential of plasma circulating tumor DNA (ctDNA) in cancer patients treated with immune checkpoint inhibitors (ICIs). In order to characterize the potential role of ultrasensitive ctDNA detection in the management of these patients we have performed tumor whole-genome-informed, ultrasensitive ctDNA analysis—tracking approximately 1,800 tumor-specific mutations per patient—in a retrospective cohort (n=136) and a prospective validation cohort (n=66) across 24 cancer types treated with ICIs alone or in combination with bispecific antibodies or immune cell engagers. Analyzing 1,455 longitudinal samples, we found that ctDNA molecular response measured as early as 3 weeks after treatment initiation correlated with improved progression-free and overall survival, while ctDNA clearance at any time strongly correlated with radiological response and prolonged survival. Additionally, ctDNA dynamics distinguished true progression from pseudoprogression and predicted outcomes in patients receiving continued immunotherapy beyond initial progression. This study highlights the broader applicability of ultrasensitive ctDNA as a biomarker across cancer types and immunotherapy modalities.

  Study EGAS50000001333

• Djerroudi et al., E-cadherin inactivation shapes tumor microenvironment specificities in invasive lobular carcinoma

  Invasive lobular breast carcinoma (ILC) shows specific stromal features, T lymphocyte infiltration (TIL) being associated with poor prognosis. Here, we reveal the involved mechanism by performing single cell RNA sequencing, combined immunohistochemistry, deconvolution of bulk RNA sequencing from large retrospective ILC series, and functional assays using primary cells. We show that ILC accumulate FAP+ inflammatory cancer-associated fibroblasts (iCAF) through a previously undescribed mechanism mediated by E-cadherin/CDH1 on CAF plasticity. Indeed, CDH1 inactivation in ILC cancer cells prevents differentiation of iCAF into myofibroblastic CAF (myCAF), leading to iCAF accumulation. In turn, iCAF increase TIL infiltration and shape their spatial organization in ILC. Subsequently, CDH1-inactivated ILC cancer cells promote immune escape by lack of retention and activation of ITGAE-expressing resident memory CD8+ T lymphocytes (TRM). Hence, our study uncovers reciprocal interactions between CDH1-inactivated cancer cells, iCAF and CD8+ TRM, revealing why and how TILs have a poor prognosis in ILC patients, a mechanism extrapolated to other CDH1-mutated cancer types.

  Study EGAS50000000761

• Mitochondrial-Nuclear Mutational Cross-Talk Drives Recurrence of Localized Prostate Cancer

  Prostate cancer remains the most prevalent non-skin cancer in men, but has a remarkably quiet mutational profile. Exome sequencing studies have revealed few recurrent somatic single nucleotide variants (SNVs). Whole-genome sequencing studies have not yet identified highly recurrent driver non-coding SNVs (ncSNVs) or genomic rearrangements (Grs). As a result, the underlying events that drive this frequent disease remain unknown. While mitochondrial mutations have been linked to several tumour types, including prostate cancer, their global frequency and impact has remained unknown. To determine if mitochondrial mutations might drive some prostate cancers, we analyzed the mitochondrial genomes of 216 tumours from patients with the most commonly diagnosed form of prostate cancer. We developed a pipeline that conservatively identified only mitochondrial SNVs (mitoSNVs) that differed in the heteroplasmy fraction as compared to their paired-normal by at least 20%. We identified several features of the mitochondrial genome that were correlated with nuclear genomic mutations, as well as features that were significantly associated with biochemical recurrence.

  Study EGAS00001001782

• Integrated single cell analysis in transformed follicular lymphoma

  Histological transformation of follicular lymphoma to aggressive form occurs 2-3% per year with poor outcome. Divergent evolution and an altered tumour-microenvironment (TME) have been implicated during transformation. However, phenotypic consequences of this evolution and its implication in TME remain unknown. To address this, we performed single cell whole genome and whole transcriptome sequencing of paired pre/post transformation patient samples. We further performed scWTS of additional samples from patients without transformation. Our analysis revealed evolutionary dynamics of transformation at unprecedented resolution. Integration of scWGS and scWTS identified pathways upregulated during evolution. scWTS analysis revealed a shifting TME landscape, with an exhausted signature emerging during transformation. Using multi-color immunofluorescence we transferred these findings to a TME-based transformation biomarker, subsequently validated in independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation, and shifting cross-talk between malignant cells and TME.

  Study EGAS00001007023

• Identifying causative mutations for Thrombocytopenia with Absent Radii

  Identifying causative mutations for Thrombocytopenia with Absent Radii

  Dataset EGAD00001000018

• DAC for hepatoblastoma sequencing data

  Data Access Committee for sequencing data of hepatoblastoma PDX cell models sequenced under University of Helsinki.

  Dac EGAC50000000548

• TTN gene targeted sequencing for AMC cohort

  TTN gene targeted sequencing for AMC cohort (n=24)

  Dataset EGAD00001005497

• DATA FILES FOR SJEPD

  DATA FILES FOR SJEPD

  Dataset EGAD00001000854

• DATA FILES FOR GRUBER SJAMLM7 EXOME

  DATA FILES FOR GRUBER SJAMLM7 EXOME

  Dataset EGAD00001003134

• RNA-seq data for NRF2 study

  RNA-seq data for clinical samples

  Dataset EGAD00001002243

• Long-term organoid culture of a small intestinal neuroendocrine tumor

  Dac EGAC00001003157

• Molecular characterization of a renal cell carcinoma PDX cohort

  Study EGAS00001006249

• Role of Genetic Factors in the Pathogenesis of Lung Disease

  Three individuals with lymphangioleiomyomatosis (LAM) underwent evaluation for Tuberous Sclerosis Complex (TSC)-associated mucocutaneous and internal findings. Next-generation sequencing (NGS) of cutaneous findings was used to confirm clinical suspicion for mosaic TSC in individuals with LAM. Mosaic mutations in TSC2 were found in these three individuals.

  Study phs003108

• RNAseq of 12q-amplified osteosarcomas

  RNA-seq of 12q-amplified osteosarcomas for detection of gene fusions and gene expression analysis. RNA-seq was used to look for novel gene fusions and promoter swapping events, and study the expression levels of identified 3' partners. Additionally, global gene expression patterns were used to separate cases into clusters.

  Study EGAS50000000494

• Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution

  Raw sequencing data for the manuscript "Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution". It includes PacBio long-read scRNA-seq, illumina short-read scRNA-seq and Twist-based targeted scRNA-seq datasets for two adrenal samples.

  Study EGAS50000001537

• The role of MALT1 in driving IBN resistance in MCL

  The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment.

  Study EGAS00001006832

• RNA-Seq on OCIAML-22 Fractions

  The donor AML patient (unsorted) that was used to generate OCI-AML22 was expanded for the indicated number of days (Donor: 0 day, 12d: 12 days, 2m: 2 months, 3m: 3 months), then sorted for the indicated fraction (CD34p: CD34+; CD34m: CD34-, CD38m: CD38-, CD38m: CD38-).

  Study EGAS00001006512

• February 2020 data update (fastq) 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.

  February 2020 data update (fastq) 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 EGAD00001006220

• ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001231

• ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001233

• ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K4me1) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001232

• DNA methylation (RRBS) data for the validation the glioblastoma progression study (GBMatch).

  Genome-wide profiling of DNA methylation levels by RRBS in 150 glioblastoma tumor samples. Patients were selected to represent the general population of glioblastoma patients based on Austrian Brain Tumor Registry. These DNA methylation profiles were created for the validation of the glioblastoma progression study (GBMatch) and consist of 106 profiles from FFPE samples and 44 profiles from fresh-frozen samples. For the 44 fresh-frozen samples also WGS data (43 genomes) and RNA-seq data (37 transcriptomes) have been produced for validation purposes.

  Dataset EGAD00001004074

• ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K9me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001234

• ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K27ac) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001229

• FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

  28 patients. Cell-free DNA and leukocyte DNA, both from before any neoadjuvant treatment. Tumor FFPE tissue (plus metastasic tissue for some patients) from after any neoadjuvant treatment. Some cfDNA from follow-up time points (e.g. after neodj. treatment or in the clinical course). IDT xgen Pan-Cancer panel for hybridisation capture. Illumina TruSeq library prep for cfDNA and leukocyte DNA, Illumina DNA Prep for FFPE DNA. n=150 libraries in total.

  Dataset EGAD00001010081

• March 2016 update of Whole genome bisulfite sequencing assay data (fastq) 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.

  March 2016 update of Whole genome bisulfite sequencing assay data (fastq) 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 EGAD00001001957

• ChIP-Seq (H3K27me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K27me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001230

• March 2016 update of whole genome shotgun sequencing data (bam/fastq) 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.

  March 2016 update of whole genome shotgun sequencing data (bam/fastq) 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 EGAD00001001958

• March 2016 update of Whole genome bisulfite sequencing assay data (bams) 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.

  March 2016 update of Whole genome bisulfite sequencing assay data (bams) 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 EGAD00001001987

• March 2016 update of smRNA-Seq assays data (bam/fastq) 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.

  March 2016 update of smRNA-Seq assays data (bam/fastq) 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 EGAD00001001959

• IFN-γ and TNF-α drive a CXCL10+ CCL2+ Macrophage Phenotype Expanded in Severe COVID-19 Lungs and Inflammatory Diseases with Tissue Inflammation

  We explored how the human macrophages response to different inflammatory factors, focusing particularly on the effects of antiviral interferons (IFN-β and IFN-γ), pro-inflammatory cytokines such as TNF-α, and other mediators like IL-4. Co-cultured fibroblasts were a component in some conditions to generate factors produced by resident stroma. We used a single-cell antibody-based hashing strategy to multiplex samples from different stimulatory conditions in one sequencing run. This macrophage transcriptomic data reveals distinct macrophage activation states and polarizations shaped by different tissue-related inflammatory conditions at single-cell resolution. We further performed an unbiased integration between tissue-level macrophages and this stimulated human blood-derived macrophages, which pinpoint an IFN-γ and TNF-α synergistically driven inflammatory macrophage phenotype expanded in severe COVID-19 lungs and other inflamed disease tissues.

  Study phs002780

• Translational analyses from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  Epigenetic modulators may sensitize platinum-resistant ovarian cancer (PROC) to immune checkpoint inhibition by reprogramming the tumor microenvironment. We report clinical and translational findings from a phase II non-randomized study of pembrolizumab and oral azacytidine in 34 women with PROC (NCT02900560). The effect of combined epigenetic and immunotherapy was evaluated by transcriptomic analyses of serially biopsied tumors. Differential gene expression analyses revealed an upregulation of inflammatory and cytolytic genes and co-inhibitory checkpoints 6 weeks on-therapy. Upregulation of interferon signaling, antigen presentation and immune cell adhesion and migration gene sets was prominent on-therapy, together with an increased density of CD8+ T -cells. Patients with a CA-125 and/or clinical response showed an enrichment of adaptive and conserved immune response gene sets on-therapy.

  Study EGAS50000001165

• DATA FILES FOR SJOS

  DATA FILES FOR SJOS

  Dataset EGAD00001000159

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000161

• Screening for abnormal CGI methylation in primary colorectal tumours

  Screening for abnormal CGI methylation in primary colorectal tumours

  Dataset EGAD00001000213

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000352

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000353

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• WGS and WXS files for Dyer ATRX study

  WGS and WXS files for Dyer ATRX study

  Dataset EGAD00001003389

• RNA-Seq data for Juvenile Pilocytic Astrocytomas

  RNA-Seq data for 9 JPA samples.

  Dataset EGAD00001009043

• Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols [time-course bulkRNAseq]

  Time-course bulk-RNA sequencing of brain organoids grown in four distinct growth protocols designed to generate dorsal (D) and ventral (V) forebrain, midbrain (M) and striatum (S) tissue at days 13 (for dorsal and ventral)/16 (for midbrain and striatum), 25, 40, 80 and 120. Per per cell line-protocol-timepoint combination three organoids (biological replicates) were grown. For reference, also three samples of the pluripotent stem cells across cell lines, not yet exposed to any protocol, were sequenced (day 0, pluripotent).

  Study EGAS50000000663

• Osteosarcoma mate-pair and RNA-sequencing

  DNA mate pair and RNA sequencing data of conventional osteosarcomas. Mate pair libraries, with average insert sizes of 2-4 kb, were prepared for sequencing using the Nextera Mate Pair Library Preparation Kit. Paired-end 76 base pair reads were generated using an Illumina NextSeq 500 sequencing instrument. Total RNA was enriched for polyadenylated RNA using magnetic oligo(dT) beads. Enriched RNA was prepared for sequencing using the TruSeq RNA Sample Preparation Kit v2 and paired-end 151 base pair reads were generated from the cDNA libraries using an Illumina NextSeq 500 instrument.

  Study EGAS00001003842

• Genetic Diseases of Immune Homeostasis and Autoimmunity Caused by GIMAP Deficiency

  We investigated 17 affected individuals in 9 kindreds with lymphopenia, splenomegaly, liver disease, thrombocytopenia, lymphadenopathy, severe recurrent lung infections, skin diseases, and lymphoma. Whole-exome sequencing of the cohort revealed mutations in GIMAP5. We also found another patient from one kindred with a unique mutation in the gene GIMAP6, discovered by whole-exome sequencing. A comprehensive investigation of this gene mutation through in vivo and in vitro experiments revealed that GIMAP6 deficiency results in defects in autophagy in patient T cells and interruption of GIMAP7 and GABARAPL2 interactions. GIMAP6 deficiency leads to affected patients to present with clinical phenotypes such as recurrent infections, lymphoproliferation, autoimmunity, and inflammation.

  Study phs002816

• Ribosomal Depleted Total RNA-Seq of PBMCs and Skin from Controls and Systemic Sclerosis Patients

  This study involved prospective collection of skin biopsies and peripheral blood mononuclear cell (PBMC) samples from controls with no self-reported history of autoimmune or inflammatory disease and cases with Rheumatologist-confirmed systemic sclerosis: limited cutaneous systemic sclerosis (lcSSc), diffuse cutaneous systemic sclerosis (dcSSc), very early diagnosis of systemic sclerosis (VEDOSS), and systemic sclerosis sine scleroderma (SSS). Some SSc cases were sampled at a 6 month routine follow-up visit. PBMCs were collected and lysed immediately. Skin punches were stabilized in RNAlater until extraction. All RNA-Seq libraries were created using Takara/Clontech ribosomal depletion kits, and sequenced on either a HiSeq2500 or HiSeq3000.

  Study phs002902

• The Genetics of Food Cue Reactivity in Children

  This study aimed to investigate genetic factors related to appetite, eating in the absence of hunger and brain reward response to food cues in a convenience sample of pre-adolescent children taken through two studies (A and B). The study involved genome-wide genotyping using the Illumina Global Screening Array. The study found an obesity polygenic risk score related to parent-reported appetitive traits in children, The study also found that FTO was related to eating in the absence of hunger and brain reward response to food cues. Available data include genotypes, measured height and weight, appetitive traits, consumption, brain reward response to food cues, and sociodemographic variables.

  Study phs003550

• Genetic Analysis of Epidermal Inclusion Cysts

  The goal of this study was to identify a potential driver of epidermal inclusion cysts, or epidermoid cysts, (EICs) in human skin. Individuals were recruited at EIC excision appointments made a priori, with no exclusion criteria. Fresh biopsies and saliva were taken from consented patients, and DNA harvested immediately. Whole exome sequencing was performed (150-bp paired end reads) to 200X in tissue and 80X in saliva via Illumina NovaSeq 6000 sequencer. Identification of somatic mutations was performed using GATK best practices. Somatic variants in the NEK9 gene were found in 12/14 cases sequenced, with clustering of variants within the RCC1 and kinase domains of the protein.

  Study phs003776

• Transcriptomic analysis of membranes from proliferative vitreoretinal diseases and isolated human retinal pigment epithelium

  This study investigates the transcriptomic profiles of proliferative vitreoretinal diseases (PVD) membranes, including proliferative vitreoretinopathy and epiretinal membranes collected from patients undergoing surgery, as well as human retinal pigment epithelial cells isolated from post-mortem donor eyes. Total RNA was extracted using AllPrep DNA/RNA Micro Kit (Qiagen) and cDNA libraries were prepared using the Ovation Solo RNA-seq Kit (Tecan). Multiplexed libraries were loaded onto a NovaSeq 6000 platform (Illumina), and sequences were generated using a 200-cycle kit. This study includes over 80 pathological and healthy samples to allow comparison of gene expression profiles and gain insights into the molecular mechanisms of PVD.

  Study EGAS50000001253

• WTCCC case-control study for Rheumatoid Arthritis

  WTCCC genome-wide case-control association study for Rheumatoid Arthritis (RA) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000011

• WTCCC case-control study for Type 1 Diabetes

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000014

• WTCCC case-control study for Type 2 Diabetes

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000016

• WTCCC case-control study for Coronary Artery Disease

  WTCCC genome-wide case-control association study for Bipolar disorder (CAD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000003

• Genome-wide analysis for non alcoholic fatty liver disease

  Genome-wide association study for the 902 patients of non alcoholic fatty liver disease (NAFLD) including non alcoholic steato hepatitis (NASH) and hepatocellurar carcinoma and 7672 controls.

  Study JGAS000126

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002901

• ChIP-seq fastq and alignment files

  ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

  Dataset EGAD00001006279

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002905

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002921

• Dataset for H3K27me3 ChIP-seq data for neuroblastoma cell lines (Neuroblastoma_CL)

  Dataset for H3K27me3 ChIP-seq data of 31 neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 2500

  Dataset EGAD00001015809

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002919

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002900

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002917

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002914

• BLUEPRINT September 2016, ATAC-seq for naive B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002902

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002913

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002909

• Molecular discrimination for multicentric occurrence and intrahepatic metastasis by whole genome sequencing of multiple liver cancers

  RIKEN collection of WGS reads for 13 multicentric liver cancers or intrahepatic metastasis and matched blood samples for 12 donors.

  Dataset EGAD00001001996

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002922

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002899

• FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

  This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

  Dataset EGAD00001015356

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A - Data Access Committee

  Dac EGAC00001003049

• The APL DAC comprises a clinician and biologist who conducted the study.

  Dac EGAC00001000865

• Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

  Dac EGAC00001001625

• PIK3CA mutation in a case of CTNNB1 mutant sinonasal glomangiopericytoma

  Study EGAS00001005653

• A critical spotlight on the paradigms of FFPE-DNA sequencing

  Study EGAS00001005757

• SNP Array Data for EGAS00001004666

  SNP Array Data for EGAS00001004666

  Dataset EGAD00010002257

• Heart

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000655

• Asian Genome Project(BioBank Japan genotype data)

  Biobank Japan registrants sequenced for Asian Genome Project

  Study JGAS000647

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• Oxford Nanopore sequencing for APL

  Raw fast5 file of Oxford Nanopore sequencing for an APL patient sample

  Dataset EGAD00001008151

• snv calls for subclonal reconstruction

  single nucleotide variant calls from somatic sniper, vcf format. input for subclonal reconstruction

  Dataset EGAD00001003753

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000695

• Swedish Bipolar Disorder exome sequencing (SWEBIC)

  This research project was a collaboration between the Karolinska Institute and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 5340 SWEBIC Bipolar case samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000001123

• Exome Recapture and Sequencing of Prospectively Characterized Clinical Specimens From Cancer Patients

  The study cohort comprises samples from patients whose tumors have been prospectively characterized as part of their care at Memorial Sloan Kettering Cancer Center. This includes a variety of distinct tumor type and molecular subtypes.

  Study phs001783

• TB-DAR Genotyping Study

  Active TB patients (sputum smear-positive and GeneXpert-positive) recruited at the Temeke District Hospital in Dar es Salaam, Tanzania, as part of a prospective study that ran between November 2013 and June 2022 (TB-DAR cohort).

  Study EGAS00001007216

• Balanced_Ependymoma

  We propose to definitively characterise the somatic genetics of a number of pediatric malignant tumours including ependymoma, high grade glioma and central nervous system primitive neurectodermal tumours through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000174