14976 results for "cancer studies using rna-seq"

in 40.26 milliseconds.

• RNA sequencing analysis of lymphoblastoid cell lines with wildtype or defective Epstein-Barr virus

  Lymphoblastoid cell lines established using either wildtype or BALF5-deficient Epstein-Barr virus were analyzed by RNA sequencing.

  Dataset EGAD00001004297

• Transcriptome - MBD4-deficient AML

  Transcriptome sequencing for WEHI-AML-1 and WEHI-AML-2. RNA libraries were generated using the Illumina TruSeq RNA Sample Preparation Kit v2 and sequenced on an Illumina HiSeq2500.

  Dataset EGAD00001003569

• Single cell RNA sequencing of colorectal cancer

  To understand intrinsic cancer cell signatures and the surrounding microenvironemt and their interactions, we performed single-cell RNA sequencing on 63,689 cells from 23 patients with 23 primary colorectal cancer and 10 matched normal mucosa samples. Analyzing of primary colorectal cancer and normal mucosa samples show a comprehensive cellular landscape of colon cancer, which is a valuable resource for the development of therapeutic strategies.

  Dataset EGAD00001005198

• Single-cell profiling of co-cultures of GSCCs and macrophages

  This dataset contains scRNA-seq data from 8 co-cultures of GSCCs and macrophages, and 1 monoculture of macrophages. Samples were individually labeled and pooled using MULTI-seq technology and processed with 10x Genomics Technology.

  Dataset EGAD00001011275

• Impact of cryopreservation on transcriptome analysis of peripheral blood mononuclear cells

  To investigate the effect of cryopreservation on PBMCs, we conducted an experiment using samples from three healthy donors under four conditions: fresh PBMCs, PBMCs subjected to a single freeze–thaw cycle, PBMCs refrozen in freezing mix, and PBMCs refrozen in TRIzol. This resulted in a total of 12 samples (three replicates per condition). RNA was extracted from all PBMC samples using the Qiagen miRNeasy Mini Kit, followed by polyA RNA sequencing on the Illumina NovaSeq 6000 platform. Blood was collected from one male and two female adult donors. Sequencing yielded high-quality data, with an average of 27.8 million reads per sample and over 94% of bases exceeding a Q30 quality score.

  Study EGAS50000001196

• hereditary BrEAst Case CONtrol study (BEACCON)

  The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC.

  Dataset EGAD00001007025

• scRNA-seq of human follicular lymphoma and lymph node

  Cryopreserved cells from human nodal follicular lymphoma and lymph node samples were thawed and processed for scRNA-seq analysis. CD3+ CD19− 7-AAD− live T cells (six FL samples from the Original cohort) or 7-AAD− whole live hematopoietic cells (five lymph node and nine FL samples from Validation cohort 1) were sorted using a FACS Aria II or III instrument (BD Biosciences). To generate single-cell emulsions, 6,000–10,000 live cells were loaded into the 10X Genomics Chromium Controller for single-cell partitioning, along with the reverse transcriptase reagent mixture and 3' or 5' gel beads. Sorted T or whole hematopoietic cells were converted to barcoded scRNA-seq libraries using 10X Genomics Chromium single cell 3' reagent kits (v3) for the Validation cohort 1, 5' reagent kits (v1) for the Original cohort, according to the manufacturer’s instructions. The libraries were sequenced on an Illumina HiSeq X Ten or NovaSeq X Plus system, mapped to the human genome (build GRCh38), and demultiplexed using CellRanger pipelines (v3.1.0, 10x Genomics).

  Dataset EGAD50000001143

• Drug development for pediatric cancers: the importance of patient' s genomic data re-use

  Cancer in children is uncommon and the overall prognosis for most pediatric cancers is good. However, while the combined survival rates have improved over the last decades, certain childhood malignancies, such as high-grade gliomas or metastatic sarcomas, still remain incurable in most patients. New strategies for targeting those devastating diseases are imperative, and patient genomic data can become a key asset in the process [1]. The Pediatric Cancer Genome Project’s datasets At EGA, we store over 500 datasets with sequencing data from pediatric cancer patients. A remarkable case is the datasets belonging to the Pediatric Cancer Genome Project (PCGP) from St. Jude Children’s Research Hospital–Washington University (Table 1 - EGAS list). PCGP is an ambitious effort to identify the mutations that drive childhood cancer and find new cures. Those datasets include 600 patients with complete tumor and normal genomes from 15 different tumor types. PCGP datasets have been an important resource for various studies that pooled genomic data from different public and in-house datasets to perform extensive genomic characterizations and publish comprehensive pan-cancer pediatric studies [2],[3]. Other interesting pediatric cancer datasets are from the Pediatric Brain Tumor Consortium, Sickkids or ICGC PedBrain project. How data reuse impacts drug development for pediatric cancers Recently, in October 2024, Nature Communications published a work led by the University of Michigan where authors used data from EGA (PCGP) check the table below as part of their strategy to pursue the identification of new tumor vulnerabilities susceptible to becoming novel therapeutic targets in diffuse midline glioma. Diffuse midline gliomas (DMG) are treatment-resistant and uniformly fatal pediatric brain tumors. The prognosis of this brainstem tumor is dismal with a median overall survival of 9–12 months from diagnosis. In this study, the authors first developed a lab model of the disease and reanalyzed data from the EGA to identify genes potentially linked to tumor severity. This approach revealed involvement of specific metabolic pathways, suggesting new possibilities for therapeutic intervention. In mice, the study shows that the use of statins can improve survival. For a brief overview of the underlying science, diffuse midline gliomas present intratumor heterogeneity with subpopulations of less-differentiated oligodendrocyte precursors and more differentiated astrocytes. Authors established in vitro models to recapitulate both phenotypes and identify metabolic programs in both subpopulations. To determine the clinical relevance, the authors re-used gene expression data from 76 DMG patients identifying a gene signature predicting decreased overall survival. After extensive metabolic characterization of subpopulations, authors defined strategies to target specific metabolic vulnerabilities. Pre-clinical experiments in mice using OXPHOS inhibitors and statins showed a reduction in tumor burden and increased overall survival [4]. In this scenario, the re-use of high-quality patient’s sequencing data appeared as an advantageous strategy to support the clinical relevance of in-vitro and pre-clinical findings. On the other hand, in rare conditions such as childhood cancer, the availability of public datasets and the possibility of pooling data from different sources can be the only way to obtain impactful results that lead to improvements for patients. References Davidoff, A. M. Pediatric Oncology. Seminars in pediatric surgery 19, 225–233 (2010). Gröbner, S. N. et al. The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). Venu Thatikonda et al. Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers. Nature Cancer 4, 276–289 (2023). Mbah, N. E. et al. Therapeutic targeting of differentiation-state dependent metabolic vulnerabilities in diffuse midline glioma. Nature Communications 15, (2024). Datasets and Studies ID Title Access Policy Year EGAD00001000134 Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAS0000100192 Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas St. Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project 2017 EGAS00001000575 Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue The hospital for sick children ("SickKids") 2016 EGAD00001000792 Exome sequencing reads of paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAD00001002006 Whole genome sequencing of paediatric glioblastoma in the ICGC PedBrain project ICGC PedBrain project 2016

  Blog drug-development-for-pediatric-cancers

• COLONOMICS small RNA sequencing

  This dataset consists of SOLiD small RNA-seq of 250 colorectal samples: 100 tumor tissue samples, 100 normal tissue samples (adjacent to tumor sites) and 50 matched control samples of healthy individuals. CSfasta and qual files converted to single fastq files prior to uploading.

  Dataset EGAD00001004827

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076

• Molecular characterization of invasive lobular carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Dataset EGAD00001000288

• scRNA-seq of HSPC treated with gemcitabine and carbplatin

  The study used cryopreserved hematopoietic stem and progenitor cells (HSPCs) harvested from one patient with chronic myelogenous leukemia (CML). The cells were thawed and acclimatized for 48 hours in StemMACS HSC Expansion Media XF (Miltenyi Biotec) supplemented with StemMACS HSC Expansion Cocktail (Miltenyi Biotec) at 37°C in a humidified atmosphere containing 5% CO2. 4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. FASTQ-files were then processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression for each cell.

  Study EGAS00001004381

• A Phase II Neoadjuvant Study of Palbociclib in Combination with Letrozole and Trastuzumab as Neoadjuvant Treatment of Stage II-III ER+ HER2+ Breast Cancer (PALTAN)

  Women with early stage ER+/HER2+ breast cancer (BC) are less likely to achieve pathological complete response (pCR) after chemotherapy with standard of care dual HER2 blockade than patients with ER-/HER2+ BC. Additionally, the toxicity burden of standard systemic therapy is high. Thus, this single arm phase 2 clinical trial investigated a novel de-escalation regimen with trastuzumab, letrozole, and palbociclib in those with early stage ER+/HER2+ BC. The aim was to determine if this treatment regimen will achieve similar pCR rates as conventional treatment and spare women the toxicity burden of regular treatments. The primary endpoint was pCR after 16 weeks of treatment with trastuzumab, letrozole, and palbociclib. Patients with newly diagnosed ER+ HER2+ invasive BC with clinical stages II and III were eligible for this protocol. Research biopsies were performed during the treatment course for whole exome and RNA sequencing, PAM50 molecular subtyping, and Ki67 assessment using immunohistochemistry for complete cell cycle arrest (CCCA: Ki67 ≤2.7%). Results showed a pCR of 7.7% and a rate of residual cancer burden at 0 or I of 38.5%. CCCA was observed in 85% at Cycle 1 day 15 post palbociclib, trastuzumab, and letrozole treatment (C1D15), compared to 27% at surgery after palbociclib was discontinued. PAM50 subtyping identified 31.2% HER2-E, 43.8% Luminal B, 25% Luminal A. 161 genes were differentially expressed comparing C1D15 to baseline. Whole exome and RNA sequencing data will be available through dbGaP.

  Study phs003147

• Medulloblastoma dataset

  This dataset contains a tumor + normal DNA sequence data and tumor RNA seq data for a medulloblastoma patient.

  Dataset EGAD50000000384

• DAC Ghent University - Department of Movement and Sports Sciences

  DAC of Ghent University for RNA-seq data of human skeletal muscle biopsies collected at the Department of Movement and Sports Sciences

  Dac EGAC50000000263

• RNAseq counts

  RNA-seq data from ILC samples. This dataset includes raw, unnormalized counts per gene, per sample.

  Dataset EGAD50000000826

• DAC - Department of Periodontology, University of Gothenburg, Sweden

  Data Access Committee to manage external requests. Project: RNA-seq data from soft tissue biopsies harvested from dental implant sites with peri-implantitis

  Dac EGAC50000000241

• Single cell RNA-Seq of Clear Cell Sarcoma of the Kidney

  Dataset EGAD00001007498

• TenK10K project

  This DAC handles access to data from the TenK10K project, which is comprised of matched whole-genome sequencing (WGS) and single-cell RNA-sequencing (scRNA-seq) datasets.

  Dac EGAC50000000931

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

  organoid and tissue bam files from rna-seq experiment

  Dataset EGAD00001010175

• Characterization of chromatin accessibility in metastatic prostate cancer

  The development of resistance to second-generation AR-signaling inhibitors (ARSIs) and progression to metastatic castrate-resistant prostate cancer (mCRPC) represents a huge obstacle to the improvement of patients’ clinical outcomes. Lineage plasticity is a common mechanism that drives the development of mCRPC by changing chromatin conformation at regulatory elements affecting downstream gene activity. ATAC-seq is a popular technique that measures accessible chromatin regions. To better understand of potential epigenomic mechanisms of ARSI resistance in prostate cancer, in this study, we performed ATAC-seq on 70 mCRPC tissue biopsies from the SU2C/PCF West Coast Dream Team (WCDT) cohort.

  Study EGAS00001006698

• CLL_targeted_exome_sequencing

  Aim to characterise cancer gene landscape in CLL, particularly in cases with mutated POT1 gene. Treatment-naïve CLL cases will be interrogated by targeted exome sequencing using a cancer gene panel.

  Study EGAS00001001963

• Genomic and epigenomic study of Japanese renal cell carcinoma including WGS, RNA-seq, ATAC-seq, and methyl-seq

  We performed whole-genomic and transcriptomic sequencing of more than 100 Japanese renal cell carcinoma (RCC) cases, including clear cell RCC, papillary RCC, chromophobe RCC, and TFE3-translocated RCC. In addition, we conducted epigenome sequencing analyses: the assay for transposase-accessible chromatin sequencing (ATAC-seq) and enzymatic methyl sequencing.

  Study EGAS00001006919

• Oesophageal adenocarcinoma scRNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains single-cell RNA-seq generated from the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19) and additional donors with Barrett's oesophagus using the 5' Single Cell Gene Expression assay from 10x Genomics. Samples were generated from oesophageal tumours, Barrett's oesophagus, and normal oesophagus and gastric tissues, with the aim of generating a reference atlas for cell types found in normal and disease-associated tissue states in the upper GI tract. This reference atlas was used as the basis for a deconvolution workflow to estimate the cell composition of bulk transcriptomes from these tissues, and to assess cell type-specific expression patterns of potential predictive biomarkers for immunochemotherapy regimens in this setting.

  Dataset EGAD00001009401

• Dataset for study Genome-wide gene expression analysis following CRISPRi of transposable elements

  Transposable elements (TEs), once regarded as parasitic genomic remnants, are now recognized as key regulators of gene expression and genome evolution, yet the functional specificity of individual TE subfamilies remains largely unexplored. This dataset investigates the transcriptional consequences of targeted repression of MER57E3 and LTR10B2 elements using CRISPR interference (CRISPRi) in human induced pluripotent stem cells (hiPSCs). hiPSCs expressing CRISPRi machinery (n = 2 biological replicates) were transduced with guide RNAs targeting individual or grouped copies of MER57E3 and LTR10B2, as well as the ZNF678 promoter or a lacZ non-targeting control. Transduced cells were subsequently differentiated into neural progenitor cells (NPCs), and total RNA was extracted for mRNA library preparation and sequencing. The dataset comprises 24 single-end mRNA-seq FASTQ files generated from these NPCs and wild-type controls.

  Dataset EGAD00001015689

• Ipilimumab and Decitabine in Treating Patients With Relapsed or Refractory Myelodysplastic Syndrome or Acute Myeloid Leukemia

  The NCI Experimental Therapeutics Clinical Trials Network (ETCTN)/Cancer Therapy Evaluation Program (CTEP) 10026 study (NCT02890329) tested combined ipilimumab and decitabine treatment in two cohorts: Arm A consisted of patients with relapsed acute myeloid leukemia (AML) after allogeneic hematopoietic stem cell transplantation. Arm B consisted of patients with advanced myelodysplastic syndrome (MDS) or AML that did not previously undergo stem cell transplantation. During the study, peripheral blood and bone marrow samples were obtained from study participants at study entry (screening), following the first lead-in cycle of decitabine monotherapy, during combined treatment with decitabine and ipilimumab, and at the end of treatment.This study tested the combination of the CTLA-4 blocking antibody ipilimumab and the DNA methyltransferase inhibitor decitabine in advanced myeloid disease in the transplant-naive and post-transplant context. The samples were used for bulk and single cell RNA sequencing (scRNA-seq) as well as whole exome sequencing (WES).

  Study phs003015

• Systematic kinase inhibitor profiling identifies CDK9 as a synthetic lethal target in NUT midline carcinoma

  Kinase inhibitors represent the backbone of targeted cancer therapy, yet only a limited number of oncogenic drivers are directly druggable. By interrogating the activity of 1,505 kinase inhibitors we found that BRD4-NUT-rearranged NUT midline carcinoma (NMC) cells are specifically killed by CDK9 inhibition (CDK9i) and exhibit a unique dependency on CDK9 and Cyclin-T1 expression. We show that CDK9i leads to robust induction of apoptosis and of markers of DNA damage response in NMC cells. While both CDK9i and bromodomain inhibition over time result in reduced Myc protein expression, only bromodomain inhibition induces cell differentiation and a p21-induced cell cycle arrest in these cells. Finally, RNA-Seq and ChIP-based analyses reveal a BRD4-NUT specific CDK9i-induced perturbation of transcriptional elongation. Thus, our data provide a mechanistic basis for the genotype-dependent vulnerability of NUT midline carcinoma cells to CDK9i that may be of relevance for the development of targeted therapies for NMC patients.

  Study EGAS00001002588

• Whole-transcriptome characterization of cell-free RNA (cfRNA) in cancer and non-cancer patients

  Whole-transcriptome characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Dataset includes collapsed BAM files for plasma cfRNA from each patient, as well as collapsed BAM files for RNA from matched tumor tissue (when available).

  Dataset EGAD00001006484

• Gene expression by RNAseq in bronchial biopsies of asthmatics, asthma in remission and healthy subjects

  The study focus was differential expression in bronchial biopsies between persistent asthma, asthma in remission and healthy controls using RNAseq. There were 184 samples that passed QC. RNA samples were processed using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina, San Diego, CA), using an automated procedure in a Caliper Sciclone NGS Workstation (PerkinElmer, Waltham, MA). In this procedure, all cytoplasmic and mitochondria rRNA was removed (RiboZero Gold kit). The obtained cDNA fragment libraries were loaded in pools of multiple samples unto an Illumina HiSeq2500 sequencer using default parameters for paired-end sequencing (2 × 100 bp). Data are available as 221 pairs of FASTQ-files. Note that several samples are associated with multiple sequence runs.

  Dataset EGAD00001005112

• Molecular Classification of Hormone Sensitive and Castration Resistant prostate cancer, using non-negative matrix factorization molecular subtyping

  We aim to identify molecular subtypes of prostate cancer using consensus non-negative matrix factorization and correlate these with existing biomarkers to inform future immunotherapeutic strategies.

  Study EGAS00001006204

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

  Study phs001442

• MPRA-SCZ

  RNA-Seq and ATAC-Seq of iPSC derived neurons under baseline and KCl stimulation conditions from 10 distinct donors, including 5 healthy controls and 5 schizophrenic individuals. scATAC of human post mortem prefrontal cortex from 4 adult individuals including 2 neurotypical individuals and 2 schizophrenic individuals.

  Dataset EGAD00001011335

• The transcriptome and DNA methylome profiling of the early human post-implantation embryos

  whole genome sequencing data of parent blood samples. Single cell full-length RNA-seq and PBAT-Seq data of in vitro culture D6 to D14 human embryo.

  Dataset EGAD00001005137

• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• 28 RNA-Seq from CAF-S1, CAF-S4 and EPCAM cells coming from Primary tumors and Lymph nodes of 5 patients)

  Dataset EGAD00001005744

• RNAseq RPKM

  RNA-seq data from ILC samples. This dataset includes counts normalized for sequencing depth and gene length.

  Dataset EGAD50000000828

• scRNA primaries

  Single cell RNA-seq for primary samples

  Dataset EGAD00001006135

• PACA-CA RNASeq fastq files

  Fastq files for PACA-CA RNA Seq analysis, for DCC release 27

  Dataset EGAD00001003972

• Covacta RNAseq merged EGA metadata

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

  Dataset EGAD00001011162

• Expression profiling of pediatric brain tumors Embryonal Tumor with Multilayered Rosettes (ETMR)

  RNA was prepared using the IlluminaTruSeq RNA sample preparation kit for poly-adenylated mRNA with an average of 97.64 million reads per sample respectively

  Dataset EGAD00001004803

• RNA-sequencing (Illumina HiSeq 4000) of tumor-stage mycosis fungoides

  This dataset contains RNA-sequencing data of tumors from 8 patients with mycosis fungoides. The data was generated using the Illumina HiSeq 4000 platform.

  Dataset EGAD00001003983

• Ancestry and somatic profile predict acral melanoma origin and prognosis – WXS

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015755

• Revealing active mutational processes in tumours using DigiPico/MutLX at unprecedented accuracy

  Active mutational processes in a tumor result in genetic micro-heterogeneity that can determine the tumor’s evolutionary trajectory. Identification of these processes by studying micro-heterogeneity can unveil novel aspects of tumor evolution with potential therapeutic implications. Such studies, however, are inherently problematic because of the discovery of excessive false positive mutations. Here we report the optimization and validation of a robust whole genome sequencing and analysis pipeline (DigiPico/MutLX) that virtually eliminates false positive results. Using our method, we identified, for the first time, a sub-clonal local hyper-mutation (kataegis) event in a recurrent ovarian carcinoma, which was unidentifiable from the bulk WGS data of the same tumor. Overall, we propose DigiPico/MutLX method as a powerful framework for the reliable study of genetic micro-heterogeneity in tumor and normal tissues.

  Study EGAS00001003555

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__alkylating_agents

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003637

• Genomic evolution of pancreatic cancer at single-cell resolution

  This project assesses genomic evolution of pancreatic cancer using the Mission Bio Tapestri platform and Whole Exome Sequencing. The Mission Bio Tapestri platform is a single-cell DNA sequencing platform using a targeted gene panel to assess SNV/CNV. Several samples, including primary and metastatic tissue, were used to investigate changes at single-cell resolution.

  Study EGAS50000001351

• IKZF5 RNAseq samples for platelets, neutrophils, monocytes and CD4+ T-cells.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing (WGS) data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor (TF)-encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy (EM) revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4+ T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes (DEGs) in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

  Dataset EGAD00001005107

• Transcriptome sequencing of cancer cell lines

  This dataset contains RNA sequencing data for 675 cancer cell lines. RNA libraries were made with the TruSeq RNA Sample Preparation kit (Illumina) according to the manufacturer protocol. The libraries were sequenced on an Illumnia HiSeq 2000

  Dataset EGAD00001000725

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281

• A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

  A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

  Study phs003762

• CATNON: IDH-mutant astroctyoma RNA FASTQ

  Raw fastq files obtained by RNA sequencing 138 IDH-mutant astrocytomas included in the CATNON trial. RNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue blocks using the RNeasy FFPE kit. RNA sequencing was performed on an Illumina NovaSeq 6000 (GenomeScan BV, Leiden, The Netherlands) with 150bp paired-end reads including UMI tags.

  Dataset EGAD50000000558

• International Consortium to Identify Genes and Interactions Controlling Oral Clefts

  Oral clefts represent the most common group of craniofacial birth defects in humans, and include cleft lip with or without cleft palate (CL/P) and cleft palate (CP). Oral clefts have a complex and heterogeneous etiology, with strong evidence for both genetic and environmental causal factors. Candidate gene studies and genome wide linkage studies have yielded compelling but inconsistent evidence that multiple genes control risk, and several studies have shown evidence for interaction between genes and environmental exposures, especially maternal smoking and nutrient intake. This consortium pulls together a very large collection of cases and their parents from multiple populations, and offers a unique opportunity to expand the search for genes controlling risk to the genome wide level. The specific aims are: To conduct a genome wide analysis on 2000+ case-parent trios ascertained through a case with isolated, non-syndromic CL/P or CP to test for linkage and disequilibrium. Initial analysis will consist of individual tests for gene effects while simultaneously testing for GxE interaction with common maternal exposures including vitamin supplementation, cigarette smoking and alcohol consumption (which have all been implicated as environmental risk factors for oral clefts). To use haplotypes in tests for GxE interaction incorporating population specific estimates. Since haplotype frequencies vary among populations, trios will be assigned haplotypes in a stratified estimation and then a pooled test statistic will be constructed. To test for interaction between SNPs in different genes showing evidence of influencing risk in a test for GxG interaction. To test for interaction between genes and maternal biomarkers using trios from Utah where measures of plasma folate, vitamin B-6, homocysteine and zinc in mothers are available. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to oral clefts through large-scale genome-wide association studies of well-characterized cases and their parents from multiple populations. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000094

• Somatic Mutations in Single Human Neurons from Patients with Congenital Neurodegenerative Diseases

  It has been hypothesized that accumulating DNA lesions in neurons contribute to aging and neurodegeneration. Despite their pathophysiological importance, the DNA lesions have not been systematically examined with effective methods. In this study, we developed a computational method for detecting genomic deletions in single-cell whole-genome sequencing (scWGS) data, and analyzed the whole genome of human single neurons. Single neurons were obtained from neurotypical individuals of various ages and from patients with three different congenital neurodegenerative diseases: Ataxia telangiectasia (AT), Cockayne syndrome (CS), and Xeroderma pigmentosum (XP). Single-neuron WGS data of AT brains are released here, and the data of other two diseases are released in a separate dbGaP study (phs001485).To understand the molecular mechanisms underlying AT, we performed single-nucleus RNA-sequencing (snRNA-seq) of postmortem cerebellar vermis and prefrontal cortex from individuals with AT and controls. To genetically confirm the diagnosis of AT, we also performed WGS on postmortem brain tissue from each individual with AT. Induced pluripotent stem cells (iPSCs) from individuals with AT and controls were differentiated into microglia, and the transcriptomes were profiled with bulk RNA-sequencing (RNA-seq).

  Study phs003005

• Genome-wide association study identifies common variants associated with breast cancer in South African Black women

  Genome-wide association studies (GWAS) have characterized the contribution of common variants to the development of breast cancer (BC) in populations of European descent, however no GWAS have been reported in resident African populations. This GWAS included 2,485 resident African BC cases and 1,101 population matched controls. Two risk loci were identified, one on chromosome 15, located between UNC13C and RAB27A (rs7181788, p = 1.01x10-08) and a second in an intron of USP22 on chromosome 17 (rs899342, p = 4.62x10-08). RAB27A is a member of the RAS oncogene family associated with invasive growth and metastasis, and UNC13C is involved in tumor progression. The rs899342 SNP is an eQTL for expression of USP22 in a wide range of tissues. Several genome-wide significant signals were detected in a hormone receptor subtype analysis. Comparison of a meta-analysis of other African ancestry BC GWAS datasets predominantly of West African ancestry with our South African data showed limited evidence of shared risk loci, suggesting potential heterogeneity in genetic risk factors for breast cancer in different African populations. A European ancestry derived polygenic risk model for BC was applied to our data, explaining only 0.79% of variance, with an area under the curve of 0.56. This study identified genetic risk factors for BC in a resident African population, but larger studies in this and other African populations are needed to further define the contribution of common variants to BC risk.

  Study EGAS00001008032

• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

  Study phs002637

• Different malignant tumor samples including lung cancer, colon cancer and breast cancer.

  Genomic DNA was purified from tumor cells and normal cells in cancer patients; We sequenced those genomic DNAs using 10X Genomics sequencing technologies, and analyzed genomic structural variations.

  Study JGAS000360

• Modulation of the peripheral blood immune cell transcriptome by vitamin D3 supplementation in people with a first demyelinating event: a randomized placebo-controlled trial

  Vitamin D deficiency is a risk factor for developing multiple sclerosis (MS). Both in vitro and animal studies suggest an immunomodulatory effect of vitamin D. The PrevANZ trial, a phase IIb randomized placebo-controlled trial of oral vitamin D3 supplementation in people with a first demyelinating event (FDE), was conducted to determine if supplementation can prevent recurrent disease activity in this cohort at high risk of developing definite MS. As a sub-study of this trial, we used whole blood transcriptomic analyses to investigate the effect of vitamin D3 supplementation on peripheral immune cells in people with an FDE, and to gain insight into potential mechanisms by which vitamin D3 may regulate MS risk and disease activity. The PrevANZ trial randomized participants to 1000 IU, 5000 IU or 10,000 IU daily of oral vitamin D3 or placebo. Peripheral blood was collected at baseline and 12 weeks in PAXgene Blood RNA tubes. Transcriptomic datasets were generated by RNA sequencing.

  Study EGAS00001007346

• Sequence analysis of colorectal serrated lesions

  Recent studies have shown that colorectal serrated lesions, which include sessile serrated adenomas (SSAs) and traditional serrated adenomas (TSAs), are precursors of colorectal cancer. However, the molecular mechanisms underlying the carcinogenesis, particularly in TSAs, remain largely uncharacterized. To clarify their molecular and clinicopathological characteristics, we performed mutation and methylation analyses of cancer-associated genes in 78 serrated lesions, including TSAs, SSAs and microvesicular hyperplastic polyps. Target exon sequence analysis was performed with 39 genes, including genes known to be frequently mutated in colorectal cancers and/or serrated lesions. We also used bisulfite pyrosequencing to assess the methylation status of various cancer-associated genes and marker genes of the CpG island methylator phenotype (CIMP). The prevalence of mutations in genes associated with Wnt signaling was significantly higher in TSAs than SSAs (65% vs. 28%, p < 0.01). Among those, RNF43 mutations were observed in 38% of TSAs and 17% of SSAs. In immunohistochemical studies of 39 serrated lesions, the prevalence of abnormal nuclear ?-catenin accumulation was significantly higher in TSAs (57%) than SSAs (8%) (P = 0.01). SMOC1 methylation was detected in 54% of TSAs but in no SSAs (p < 0.01). Additionally, SMOC1 methylation was more prevalent among TSAs with KRAS mutation (82%) than with BRAF mutation (38%, p = 0.03). Lesions with CIMP-high or RNF43 mutations were detected only in TSAs with BRAF mutation, suggesting two distinct carcinogenic pathways in TSAs. Mutations in genes associated with Wnt signaling play a greater role in the carcinogenesis of TSAs than SSAs.

  Study JGAS000217

• RNA-seq, WGS and WES of Hepatocellular carcinomas, enriched in fibrolamellar carcinomas

  Dataset EGAD00001005308

• bulkRNA

  Bulk RNA-seq for cALL patient-derived PDX samples

  Dataset EGAD00001006133

• Myeloma XI trial data

  The dataset contains WGS and RNA-seq from Myeloma XI trial

  Dataset EGAD00001005491

• RNA-seq of human embryonic heart, lung, and cerebellum

  Characterization of cell types in the human embronic heart, lung, and cerebellum.

  Study EGAS00001004375

• RNAseq data

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes raw FASTQ files.

  Dataset EGAD00001011168

• Gene expression of transduced human primary germinal centre B-cells

  RNA-seq sequencing data of human germinal centre B-cells (42 samples)

  Dataset EGAD00001005281

• Berlin Neuroblastoma Dataset

  Paired tumor/normal WGS and RNA-seq of primary neuroblastoma.

  Dataset EGAD00001005488

• Prostate Cancer Genome Sequencing Project

  Prostate cancer is a prevalent cause of cancer morbidity and mortality in men. In order to characterize the full range of somatic mutations in protein-coding genes that may drive the growth of prostate cancer, we sequenced the exonic regions of genomic and tumor DNA from over 100 patients with high-risk primary prostate cancer. Using hybrid capture and paired end DNA sequencing, we identified mutations in several novel putative prostate cancer genes. We interrogated copy number changes across tumor genomes using high-density SNP arrays, and identified a molecular subtype of cancer characterized by mutation of the ubiquitin ligase subunit SPOP and copy number loss at specific genomic loci.

  Study phs000447

• Single cell RNA sequencing of bone marrow mononuclear cells

  Bone marrow aspirates were obtained from patients with relapsed/refractory large B cell lymphoma (rrLBCL), mononuclear cells isolated by ficoll density-gradient centrifugation, and loaded onto a 10X Chromium for single cell RNA-sequencing using 5’ chemistry without prior cryopreservation. Healthy donor bone marrow mononuclear cells were obtained from healthy allogeneic stem cell transplant donors and analyzed following viable cryopreservation.

  Study EGAS00001006836

• High-throughput determination of the antigen specificities of T cell receptors in single cells

  High-throughput linking of T cell receptor (TCR) sequences to their binding antigens is vital for immune profiling, yet challenging. We present Tetramer associated TCR Sequencing (TetTCR-Seq) to address this challenge. Binding is determined using a library of DNA-barcoded antigen tetramers that are rapidly and inexpensively generated using an in vitro transcription/translation platform. We included CMV+ donors (CMV seropositive donors who are infected with Cytomegalovirus) to screen for CMV specific TCRs.

  Study phs001678

• ChIP-seq of plasma cell-free nucleosomes identifies gene expression programs of the cells-of-origin

  Cell-free DNA in human plasma provides access to molecular information about the pathological processes in the organs or tumors from which it originates. These DNA fragments are derived from fragmented chromatin in dying cells, and retain some of the cell of origin histone modifications. Here, we apply chromatin immunoprecipitation of cell-free nucleosomes carrying active chromatin modifications followed by sequencing (cfChIP-seq) to 268 human samples. In healthy donors, we identified bone marrow megakaryocytes, but not erythroblasts, as major contributors to the cfDNA pool. In patients with a range of liver diseases, we show that we can identify pathology-related changes in hepatocyte transcriptional programs. In metastatic colorectal carcinoma patients, we detected clinically relevant, and patient-specific information, including transcriptionally active HER2 amplifications. Altogether, cfChIP-seq using low sequencing depth, provides systemic and genome-wide information, can inform diagnosis, and facilitate interrogation of physiological and pathological processes using blood samples.

  Study EGAS00001004913

• Prader-Willi Syndrome and Early-onset Morbid Obesity Natural History Protocol

  This observational study will involve the comprehensive assessment of the medical, behavioral and nutritional history and the clinical features of individuals with Prader-Willi syndrome and individuals with features of PWS-like/EMO. A blood sample will be obtained from the participants in order to create a DNA and RNA repository. In those PWS participants with a known deletion a blood sample will be collected for DNA in order to perform array comparative genome hybridization (aCGH) microarray or Methylation-Specific Multiplex Ligation-dependent Probe Amplification (MS-MLPA) studies to characterize the extent of the deletion. DNA samples will be sent to the Consortium Center at Baylor College of Medicine for the performance of the aCGH studies and to either Dr. Driscoll or Dr. Butler lab for MS-MLPA analysis. No drugs or treatments will be administered through this protocol. Our goal is to enroll as many participants as possible over a 8 year period. Currently we have enrolled 297 total subjects of which 265 have PWS and 32 EMO. Our original goal was to have enrolled over the first 5 years a clinical database of 200 individuals with PWS and 100 with EMO. We have exceeded expectations in PWS enrollment, but have fallen short in the enrollment of individuals with EMO. Therefore, we would like to reset our goals. We now propose to have an enrollment goal of 400 total subjects of which 350 will have PWS and 50 will have EMO. Eligible participants will be initially enrolled in the natural history study from the 4 clinic sites currently involved with PWS (University of Florida, Kansas University Medical Center, Vanderbilt University and University of California at Irvine). Participants assessed will serve to provide a background of information and a willing cohort for future interventional studies. All participants will have had standard genetic testing at a commercial laboratory prior to entry into the study. The PWS participants will be classified into one of the 3 main molecular classes (deletion, UPD and ID). The EMO participants will have had laboratory testing ruling out PWS and chromosomal aneuploidy (e.g., trisomy 21, Klinefelter syndrome, etc.). Going forward we feel it is important that all newly recruited EMO subjects have an aCGH as part of their evaluation so we can identify those with discrete deletions, duplications or copy number variants (CNV) and compare them to those without aCGH abnormalities. The participants will be assessed annually (0-3 years of age) or biennially (&#62; 3 years) in the Clinical Research Center (or equivalent facility) using standardized protocol including photographs for documentation purposes to compare the evolution of the clinical phenotype.

  Study phs000575

• MuTHER_adipose_tissue_small_RNA_expression

  We investigate the naturally occurring variation of small RNA expression in conjunction with genetic and gene expression variation. We shall assess the variation in subabdominal fat tissue small RNA levels in 168 unrelated MuTHER individuals. Using gene expression data from the same samples, we can survey how much the small RNA expression contributes to the variance in gene expression profiles. We can also take advantage of the high density genotyping data on these samples to identify genetic associations of small RNA expression levels, and the downstream effect of the genetic variants in small RNA sequence. Previous small RNA sequencing efforts have also extended the repertoire of small RNAs, and we hope to potentially find additional small RNAs active in adipose tissue biology. Altogether, the project should provide an exciting view into small RNA biology in humans, and lead to development of new methodology for analysis of molecular phenotype data.

  Study EGAS00001000212

• BLUEPRINT RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000327

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• scRNAseq + TCRseq of n-irAE patients

  Here we performed multimodal analysis (5'scRNAseq and TCR-seq) on PBMCs from cancer patients developing or not neurological adverse events (n-irAEs) following immune checkpoint inhibition (ICI) treatment.

  Study EGAS50000000603

• Sperm sequencing reveals extensive positive selection in the human germline -NanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015590

• Sperm sequencing reveals extensive positive selection in the human germline -TargetedNanoSeq

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015591

• Sperm sequencing reveals extensive positive selection in the human germline -WGS

  Mutations that occur during human ageing in the cell lineages of sperm or eggs have the potential to be transmitted to offspring. In males, positive selection of driver mutations during spermatogenesis is known to increase the birth prevalence of certain developmental disorders and cancer predisposition syndromes. However, direct observation of the scope of this selection in sperm has been limited by the error rates of sequencing technologies. Using the duplex sequencing method known as NanoSeq, we sequenced bulk sperm samples from individuals aged 24 to 75 years. Our findings revealed a linear accumulation mutations per year and mutational signatures consistent with pedigree studies. Deep targeted and deep exome NanoSeq of sperm samples identified genes subject to significant positive selection in the male germline, which are linked to diverse cellular pathways including RAS/MAPK and BMP signaling. Strikingly, nearly all positively selected genes are associated with developmental or cancer predisposition disorders in children. We find that this effect drives an elevated risk of known likely disease-causing mutations in sperm across a wide age range. This implies that the disorders attributed to these genes likely exhibit elevated birth prevalence in human populations, particularly among older fathers. These findings shed light on the dynamics of germline mutations and highlight an increased disease risk for children born to fathers of advanced age.

  Dataset EGAD00001015592

• Whole Genome Sequencing in the Inner City Asthma Consortium (ICAC) Cohorts

  We performed whole-genome sequencing on individuals from the Asthma Phenotypes in the Inner City (APIC) and Urban Environment and Childhood Asthma (URECA) study cohorts, which consist of children with asthma who live in low-income neighborhoods across 10 U.S. cities. APIC was a one-year, prospective, observational study of children ages 6-17 with asthma. URECA was a prospective, observational study featuring a birth cohort of children with a high risk of developing asthma based on family history. We performed whole-genome sequencing on 1,035 individuals (ages 5-17 yrs; 67% Black, 25% Hispanic; 66% with MD-diagnosed asthma; APIC=508, URECA=527). Sequence read processing, quality control, and variant calling were performed using the Genome Analysis Toolkit suite (GATK v4). Variant call sites were annotated according to the filters applied in our common variant (minor allele frequency &#8805; 1%) association studies, based on predicted false positive rates, genotype quality and depth, and population-adjusted Hardy-Weinberg equilibrium. Principal components of ancestry were calculated using high quality, linkage-disequilibrium-pruned single-nucleotide variants, accounting for subject relatedness, using PC-Air and PC-Relate.

  Study phs002921

• CD4+ T cell subsets stratified by complement receptor type 2 (CR2) expression

  FACS-sorted CR2+ and CR2- naive and memory CD4+ T cells from healthy donors, plus CR2+ naive CD4+ T cells activated using CD3/CD28 beads, were analyzed ex-vivo. Exome-enriched RNA sequencing was carried out for all subsets.

  Study EGAS00001001870

• Cell type-specific transcriptomics of esophageal adenocarcinoma as a scalable alternative for single cell transcriptomics

  We developed a protocol for the separation of esophageal carcinoma tissue into leukocytes (using CD45 as a marker), epithelial cells (EpCAM), and fibroblasts (two out of PDGFRA, CD90, anti-fibroblast) by fluorescence-activated cell sorting followed by RNA-sequencing

  Study EGAS00001004053

• Fusion gene analysis using multiplex single primer extension-based RNA-sequencing

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains fusion gene analysis using multiplex single primer extension-based RNA-sequencing for a subset of 25 patients of the screening cohort. Data was generated on Illumina NexSeq 550 device in paired-end mode and is stored in compressed FASTQ file format.

  Dataset EGAD00001011326

• snRNA-seq/snATAC-seq multiome of first and second trimester human gonads - HUGODECA dataset

  Comprehensive map of first- and second-trimester gonadal development in humans using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays, and imaging. ArrayExpress Accession: E-MTAB-11708

  Dataset EGAD00001009388

• Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA-sequencing the pros and cons

  RNA sequencing data of a collection of 6 pediatric ependymoma cases

  Dataset EGAD00001009301

• Dataset for melanoma-WHOLE_GENOME

  Rare cancer sequencing data of 22 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008889

• Dataset for cancer_of_unknown_primary-EXON

  Rare cancer sequencing data of 62 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008870

• Dataset for synovial_sarcoma-EXON

  Rare cancer sequencing data of 34 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008898

• Dataset for bone_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008866

• Dataset for upper_gastrointestinal_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008901

• Dataset for GIST-WHOLE_GENOME

  Rare cancer sequencing data of 18 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008876

• Comprehensive molecular profiling with whole-exome sequencing (WES) and RNA sequencing (RNA-seq) of PDX tumors

  To identify biomarkers of the antitumor efficacy of molecular targeted therapies, patient-derived xenograft (PDX) mouse models established from 52 patients with solid tumors were treated.

  Study JGAS000707

• RNA-seq of iPSC-derived microglia treated with miRNA mimics and inhibitors

  Microglia were derived from iPSCs and treated with mimics and inhibitors of the miRNAs hsa-miR-150-5p, hsa-miR-193a-3p and hsa-miR-19b-3p. RNA-sequencing was then performed to examine the effects of up- and down-regulation of the respective miRNAs.

  Dataset EGAD00001006842

• Establishment and characterization of a new Pseudomonas aeruginosa infection model using 2D airway organoids and dual RNA sequencing

  Study EGAS00001007463

• Transcriptome analysis of kidney organoids lacking NPHP1gene

  To explore the molecular mechanisms of cyst formation in kidney organoids lacking NPHP1, we performed RNA-seq transcriptome experiments. Because the potential for cyst formation by suspension culture should already be derived from kidney organoids at the adherent culture, we compared the global gene expression pattern of kidney organoids on day 18 between healthy group and NPHP1-deficient group

  Study JGAS000683

• RNA-seq data of proliferative vitreoretinal diseases and healthy human retinal pigment epithelium

  This Data Access Committee (DAC) evaluates access requests for RNA-seq data generated from: - Membranes from proliferative vitreoretinal diseases, including proliferative vitreoretinopathy and epiretinal membranes. - Retinal pigment epithelial cells isolated from healthy ocular globes obtained from deceased donors. Collection and analysis of these residual human materials were conducted with the approval of the ULB-Erasme Ethical Committee (P2019/066 A2022/136) and of the Eye Bank (CHU Liège), with no need for informed consent in compliance with Belgian law. All data are pseudonymised, and access is restricted to qualified researchers whose proposed use of the data is consistent with the applicable ethical approval and legal requirements, including the General Data Protection Regulation (GDPR).

  Dac EGAC50000000721

• RNA-Seq data of hepatoma (Huh7 derived) and Ph5CH cells and primary hepatocytes

  The innate immune response of cells of hepatic origin (Huh7, Huh7.5, PH5CH and primary human hepatocytes (PHH), 66 samples) was analyzed by transcriptome analysis (RNAseq) upon supernatant delivery or transfection of synthetic dsRNA (poly(I:C)). Expression of TLR3 and RIG-I was reconstituted by lentiviral transduction in Huh7 and Huh7.5 cells. The sequencing is single RNA-Seq on an Illumina HiSeq 4000 with the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001007083

• RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003433

• Multi-omic dataset of neuroendocrine neoplasm organoids

  This dataset corresponds to one of the first biobanks for the understudied neuroendocrine neoplasms from multiple grades and body sites (lung, pancreas, small intestine). It contains whole-genome sequencing data for original tumors, patient-derived tumor organoids at multiple passages, and matched normal tissue, and RNA-seq data for the original tumor and patient-derived tumor organoids.

  Study EGAS00001005752

• Cellular and Molecular Characterization of Renal Cell Carcinoma

  We are performing a comprehensive cellular and molecular characterization of renal cell carcinoma. This work includes an initial cohort of patients whose tumors (and adjacent normal tissue) underwent single cell analysis. Single-cell RNA sequencing (scRNA-seq) and TCR sequencing (scTCR-seq) analysis of untreated clear cell renal cell carcinoma tumor and adjacent normal tissue was performed across disease stages. This initial cohort includes 13 patients: 4 with early stage disease (stage I/II), 4 with locally advanced disease (stage III), and 5 with advanced/metastatic disease (stage IV). Whole exome sequencing on tumor and normal tissue was also performed.&nbsp;

  Study phs002252

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

• Bulk RNA-sequencing of AML blasts pre and post culture

  This dataset contains 18 Fastq files from 9 samples (pre-culture (n=3), post culture in standard (n=4) or niche-llike (n=2) conditions) from 4 patients.They correspond to bulk RNA sequencing on Illumina instrument of libraries prepared using SMARTer Universal Low Input RNA Kit.

  Dataset EGAD00001008773

• Combinatorial Indexed 10x Genomics Single-Cell ATAC-seq on Human Cerebral Cortex

  Single-cell chromatin accessibility profiling (scATAC) using droplet fluidics (10x Genomics) is inherently limited in throughput due to the number of available indexed droplets. This study leverages single-cell combinatorial indexing workflows with modified adapter designs to enable indexed tagmentation and superloading of pre-indexed nuclei into the 10x Genomics scATAC workflow, enabling a substantial increase in the number of cell profiles that can be obtained per channel. This workflow, 10x single-cell combinatorial indexed ATAC-seq (txsciATAC), is demonstrated on human brain tissue (middle frontal gyrus), along with mouse brain tissue to enable doublet and crosstalk assessment. This study includes all human data and includes a single preparation taken through nuclei isolation and indexed tagmentation using 96 indexes then split to produce two datasets, one targeting 20k cells and one targeting 70k, each using a single channel of the 10x Chromium controller.

  Study phs003497

• WTCCC case-control study for Breast cancer

  WTCCC genome-wide case-control association study for Breast cancer (BC) using the 1958 British Birth Cohort collection as controls.

  Study EGAS00000000024

• scRNA-seq of Patient-derived tumor fragments (PDTFs)

  scRNA-seq of Patient-derived tumor fragments (PDTFs) which were treated with either Isotype (DP47), Isotype-IL2v (DP47-IL2v), anti-PD1 (PembroPGLALA) or PD1-IL2v (PembroPGLALA-IL2v) for 48 hours. Dataset content: 10 samples from 3 donors File type: paired-end fastq files Protocol: Chromium Single Cell 3' Reagent Kits User Guide (Dual Index) with Feature Barcoding technology for Cell Surface Protein (CG000317) Technology: Illumina sequencing Experimentation: scRNA-seq using the 10X technology

  Dataset EGAD50000000584

• H3K27ac ChIP-seq in primary prostate tumours

  H3K27ac ChIP-seq and input genome sequencing was performed in 19 primary prostate tumours classified as intermediate risk. Sequencing of ChIP DNA was performed on an Illumina HiSeq 2000 as either single end 50 bp reads (for 7 samples) or paired end 100 bp reads (for 12 samples). Input DNA from all samples was sequenced using single-end 50 bp reads. The files provided are in fastq format.

  Dataset EGAD00001003461

• Identifying the role of ID3 in DNA repair and maintenance of genome integrity (RNA-seq)

  Dataset EGAD00001008198

• tRCC UTSW 2024 Cohort

  This submission contains the WES and RNA-Seq raw data for the study titled 'Comparative Genomics of a Translocation Renal Cell Carcinoma Mouse Model Reveals Molecular Mechanisms of Tumorigenesis.

  Dac EGAC50000000105

• scRNA PDX

  Single cell RNA-seq for PT1-derived PDX samples

  Dataset EGAD00001006134

• RNA-seq data of LMS tumors

  This dataset contains paired fastq files for LMS tumor samples

  Dataset EGAD00001003828

• JMS dataset

  Juntendo Muscle Study (JMS) dataset comprises 23 samples of paired-end RNA-Seq sequences in fastq format.

  Dataset EGAD00001008983

• RNA-seq data of 196 nontumorous human breast tissue

  Transcriptome analysis of nontumorous human breast tissues. 196 cases were included in the dataset.

  Dataset EGAD00001006397

• Facioscapulohumeral muscular dystrophy (FSHD): RNA-seq of isogenic TIRM+, TIRM- muscle and PBMCs from patients and matched controls

  FASTQ files describing paired-end RNA-sequencing of isogenic TIRM+ and TIRM- muscle biopsies from 24 FSHD patients (48 samples) and vastus lateralis muscle biopsies from 11 matched control individuals. FASTQ files are also provided describing RNA-sequencing of 15 FSHD peripheral blood mononuclear samples and 14 matched controls. For muscle biopsies sequencing was at 21.7-35.5 million reads/sample. RNA was extracted from PBMCs followed by globin depletion with sequencing at 19.7-46.5 million reads/sample.

  Dataset EGAD00001011077

• Identifying aberrant splicing isoforms and potential neoantigens in non-small cell lung cancer

  To identify aberrant splicing isoforms and potential neoantigens, we performed full-length cDNA sequencing of seven non-small cell lung cancer specimens using a long-read sequencer MinION. We detected aberrant splicing isoforms using our bioinformatics pipeline and constructed a comprehensive catalogue.

  Study JGAS000245

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from Schizophrenia individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000043

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from normal individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000042

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from Bipolar disorder individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000045

• Constructing database of magnetic resonance imaging of the brain and the ancillary clinical information for multisite collaboration studies: a dataset from Depression individuals

  Previously there was no neuroimaging database available for research community that incorporated a large Japanese sample of healthy people and patients with neuropsychiatric disorders. Establishing such a database will enable large-scale, neuroimaging-based investigations on pathophysiology of neuropsychiatric disorders by simply using the large data pool or by combining it with investigators' own data sets.

  Study JGAS000044

• Elucidation of the association between viruses and autoimmune diseases and COVID-19

  We determined the presence or absence of endogenous herpesvirus 6 (eHHV-6) and calculated annelovirus levels from whole genome sequencing of 2,238 patients with autoimmune diseases and 2,919 controls. We performed genome-wide association analysis using WGS of 22 eHHV-6B-positive cases and -negative cases. Single-cell RNA sequencing was performed using human peripheral blood mononuclear cells from 3 eHHV-6B-positive SLE patients and 5 -negative SLE patients.

  Study JGAS000741

• Bone morphogenetic protein-9 controls pulmonary vascular growth and remodeling

  Human PMECs from 10 donor lungs were isolated, cultured (passages 3 to 4), synchronized by serum starvation (0.3% FCS), and stimulated with 10 ng/mL BMP-9 for 4 h. Single-cell profiling was performed using the 10X Genomics Chromium RNA 3' V3.1 kit. Five experimental groups were analyzed using cell hashing and sequenced on an Illumina NextSeq500. Data were processed with Cell Ranger and Seurat for differential gene expression and functional enrichment analysis.

  Study EGAS50000001026

• RNA sequencing of Ewing sarcoma and CIC-DUX4 sarcoma

  RNA sequencing of a collection of 6 Ewing sarcoma and 3 CIC-DUX4 sarcoma tumoroids plus 3 matched patient tumors. Tumoroids were established from digested patient tumor material as 3D culture in Matrigel. After 2-3 month of growth, RNA was isolated from individual tumoroid models using the RNeasy Kit (Qiagen) and used for whole exome sequencing. RNA from corresponding patient tumors was tested in parallel, if available.

  Dataset EGAD50000000557

• MiRNome_pituitary_adenoma

  Small RNA (&lt;100 bases in length) were purified from total RNA using miRNeasy kit (Qiagen), then sequenced. Libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq small RNA protocol (Illumina), starting from 1 µg of high quality total RNA. Single read (1 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on miRBase v.2052, then counted with STAR (v.2.5.2a).

  Dataset EGAD00001004998

• WGS and WTS data of patients diagnosed with MEITL.

  WGS from 4 patients, WTS from only 3 patients (insufficient tissue from 4th patient for WTS). Whole-genome sequencing (WGS) was performed for 60 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000. Whole-transcriptome sequencing (WTS): Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on Illumina HiSeq 2500 with 2x101 bp read length. Description of prefix used in filenames: T: Tumor samples N: Normal samples (Blood) P: PDX samples

  Dataset EGAD00001005341

• Shallow whole genome sequencing of ctDNA samples from DETECT study

  A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival from the paper "A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival", by Beddowes et al. Mol.Onc.

  Study EGAS50000000911

• Pediatric HGG WES and RNA-Seq

  Paediatric high-grade glioma (pHGG) is the leading cause of paediatric brain tumour death. Here we performed RNA and whole exome sequencing on pHGG samples to analyse transcriptomic and genetic alterations associated with this devastating disease, and to understand the relationship between them.

  Study EGAS00001005687

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of severe COVID-19. In addition, we performed single-cell RNA-sequencing of SARS-CoV-2 stimulated classical blood monocytes. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001006827

• CITE-seq data of primary acute myeloid leukemia patient samples with complex karyotype

  In this study, we aimed to assess RNA expression and surface antigen expression of acute myeloid leukemia with complex karyotype (CK-AML) at the single-cell level. For this purpose, we performed cellular indexing of transcriptomes and epitopes (CITE-seq) of primary leukemia samples from four CK-AML patients.

  Dataset EGAD00001011171

• Epigenomics and Single-cell Sequencing Define Cellular Heterogeneity in Langerhans Cell Histiocytosis

  Epigenomic and transcriptomic analysis of Langerhans cell histiocytosis (LCH) biopsies. Single-cell RNA-seq (10x Genomics) of seven LCH biopsies. ATAC-seq data from four sorted cell populations (in duplicate) from one LCH biopsy.

  Dataset EGAD00001005280

• A comprehensive characterization of the cell-free transcriptome reveals tissue- and subtype-specific biomarkers for cancer detection

  Cell-free RNA (cfRNA) is a promising analyte for cancer detection. However, a comprehensive assessment of cfRNA in individuals with and without cancer has not been conducted. We performed the first transcriptome-wide characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Of 57,820 annotated genes, 39,564 (68%) were not detected in cfRNA from non-cancer individuals. Within these low-noise regions, we identified tissue- and cancer-specific genes, defined as "dark channel biomarker" (DCB) genes, that were recurrently detected in individuals with cancer. DCB levels in plasma were correlated with tumor shedding rate and RNA expression in matched tissue, suggesting that DCBs with high expression in tumor tissue could enhance cancer detection in patients with low levels of circulating tumor DNA. Overall, cfRNA provides a unique opportunity to detect cancer, predict the tumor tissue of origin, and determine the cancer subtype.

  Study EGAS00001004704

• Single-cell RNA sequencing analysis of corneal and limbal epithelial cells derived from a patient with congenital aniridia

  Aniridia-associated keratopathy (AAK) is a progressive condition characterized by conjunctivalization of the cornea, yet its molecular mechanisms remain largely unknown. This study aims to elucidate the transcriptional landscape of AAK by characterizing the gene expression profiles of corneal epithelial cells in a patient with congenital aniridia. Corneal and limbal epithelial tissues were collected from the patient during the cultivated oral mucosal epithelial transplantation (COMET) surgery. The tissues were dissociated into single cells and subjected to single-cell RNA-seq.

  Study JGAS000790

• Multivalent State Transitions Shape the Intratumoral Composition of Small Cell Lung Carcinoma

  Small cell lung carcinoma (SCLC) is an aggressive, tobacco-associated tumor characterized by rapid growth, early metastases, and initial response followed by almost invariable resistance to chemotherapy. Studies to date have not resolved the extent that diverse transcriptional programs drive SCLC and contribute to its lethality. We combined patient-derived xenograft (PDX) (n = 64) resources with multi-omic profiling, single-cell fluorescence tracking of ex vivo tumor cells, and mathematical and statistical models to study the topology of the SCLC transcriptional state space and its plasticity.

  Study phs003102

• Transcriptome analysis of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A (H3N2) virus.

  Transcriptome analysis of influenza A (H3N2) human challenge samples. Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Study EGAS50000000679

• Spatial Transcriptomics of Vaccine Therapy With or Without Cyclophosphamide in Treating Patients Undergoing Chemotherapy and Radiation Therapy for Stage I or Stage II Pancreatic Cancer That Can Be Removed by Surgery

  Pancreatic ductal adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. Here, spatial transcriptomics data were generated from 16 pancreatic cancer patients treated with GVAX, whose tumors presented with induced intratumoral TLS. Resected tumor specimens were embedded in OCT media and freshly frozen. Sections were cut into 6.5 x 6.5 mm dimensions compatible with Visium spatial transcriptomics slides. TLS-positive tumor sections from 14 patients (14 tumor samples in total) and lymph nodes from remaining patients (2 lymph node samples in total) were selected by an expert pathologist for profiling. We used 4 Visium slides and covered the 16 capture areas with sections cut in a cryostat at 10 &#181;m. The fresh frozen Visium protocol was followed according to manufacturer's recommendations (10x Genomics Spatial 3' v1). Tissue permeabilization and library construction was carried out according to the manufacturer's protocols. Permeabilization time was optimized to 30 minutes. The captured tissue sections were permeabilized to allow RNA to be captured onto the slide where it reverse-transcribed to cDNA. The cDNA was then amplified, and sequencing libraries were prepared using the 10x Genomics Visium Spatial Gene Expression Reagent Kit for Library Preparation. The libraries were then sequenced using an Illumina NovaSeq sequencer. The raw data obtained from the sequencing were processed using the SpaceRanger (spaceranger-1.2.0) pipeline for alignment onto the GRCh38-2020-A reference transcriptome quantification of gene expression. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation.

  Study phs003862

• RNA-seq data from 9 patients with peri-implantitis

  Fastq files + patients' characteristics

  Dataset EGAD50000000544

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Dataset EGAD50000000747

• RNA-Seq of SMARCB1 re-expression and HDAC+mTOR inhibition experiments in malignant rhabdoid tumor organoids

  Dataset EGAD00001006574