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• A98253A

  Whole genome sequencing for single cells for library A98253A 1250 cells; filetype=bam

  Dataset EGAD00001007629

• A98253B

  Whole genome sequencing for single cells for library A98253B 1388 cells; filetype=bam

  Dataset EGAD00001007630

• A98254A

  Whole genome sequencing for single cells for library A98254A 1490 cells; filetype=bam

  Dataset EGAD00001007631

• A98255B

  Whole genome sequencing for single cells for library A98255B 1394 cells; filetype=bam

  Dataset EGAD00001007632

• A98271A

  Whole genome sequencing for single cells for library A98271A 1190 cells; filetype=bam

  Dataset EGAD00001007633

• A98289A

  Whole genome sequencing for single cells for library A98289A 1066 cells; filetype=bam

  Dataset EGAD00001007634

• A98290B

  Whole genome sequencing for single cells for library A98290B 869 cells; filetype=bam

  Dataset EGAD00001007635

• A98305A

  Whole genome sequencing for single cells for library A98305A 986 cells; filetype=bam

  Dataset EGAD00001007637

• A108732A

  Whole genome sequencing for single cells for library A108732A 1139 cells; filetype=bam

  Dataset EGAD00001007592

• A108833B

  Whole genome sequencing for single cells for library A108833B 866 cells; filetype=bam

  Dataset EGAD00001007594

• A108842A

  Whole genome sequencing for single cells for library A108842A 1477 cells; filetype=bam

  Dataset EGAD00001007595

• A108863A

  Whole genome sequencing for single cells for library A108863A 1301 cells; filetype=bam

  Dataset EGAD00001007597

• A110618A

  Whole genome sequencing for single cells for library A110618A 1184 cells; filetype=bam

  Dataset EGAD00001007599

• Single Cell Genome Sequence for DLP+ library A118389B

  Single Cell Genome Sequence for Telomerase immortalized breast epithelium cell line 184-hTERT 85.14 p20 cell line AT135 on DLP+ library A118389B

  Dataset EGAD00001009433

• Single Cell Genome Sequence for DLP+ library A118782A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050B passage 1, patient-derived xenograft SA1050E passage 1 on DLP+ library A118782A

  Dataset EGAD00001009435

• Single Cell Genome Sequence for DLP+ library A118808A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096B passage 1 on DLP+ library A118808A

  Dataset EGAD00001009440

• Single Cell Genome Sequence for DLP+ library A118812B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118812B

  Dataset EGAD00001009442

• Single Cell Genome Sequence for DLP+ library A118816A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118816A

  Dataset EGAD00001009444

• Single Cell Genome Sequence for DLP+ library A118857B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1184D passage 1 on DLP+ library A118857B

  Dataset EGAD00001009445

• Single Cell Genome Sequence for DLP+ library A95663A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053F passage 1 on DLP+ library A95663A

  Dataset EGAD00001009446

• Single Cell Genome Sequence for DLP+ library A95668A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A95668A

  Dataset EGAD00001009447

• Single Cell Genome Sequence for DLP+ library A95670A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 5 on DLP+ library A95670A

  Dataset EGAD00001009448

• Single Cell Genome Sequence for DLP+ library A95670B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6 on DLP+ library A95670B

  Dataset EGAD00001009449

• Single Cell Genome Sequence for DLP+ library A95717A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096A passage 1 on DLP+ library A95717A

  Dataset EGAD00001009450

• Single Cell Genome Sequence for DLP+ library A95722A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A95722A

  Dataset EGAD00001009451

• Single Cell Genome Sequence for DLP+ library A96109A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A96109A

  Dataset EGAD00001009452

• Single Cell Genome Sequence for DLP+ library A96113A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage on DLP+ library A96113A

  Dataset EGAD00001009453

• Single Cell Genome Sequence for DLP+ library A96130A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 8 on DLP+ library A96130A

  Dataset EGAD00001009454

• Single Cell Genome Sequence for DLP+ library A96142B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A96142B

  Dataset EGAD00001009455

• Single Cell Genome Sequence for DLP+ library A96154A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1135, patient SA1162SA on DLP+ library A96154A

  Dataset EGAD00001009456

• Single Cell Genome Sequence for DLP+ library A96161A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96161A

  Dataset EGAD00001009457

• Single Cell Genome Sequence for DLP+ library A96173A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 15 on DLP+ library A96173A

  Dataset EGAD00001009459

• Single Cell Genome Sequence for DLP+ library A96174A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 11 on DLP+ library A96174A

  Dataset EGAD00001009460

• Single Cell Genome Sequence for DLP+ library A96175A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96175A

  Dataset EGAD00001009461

• Single Cell Genome Sequence for DLP+ library A96177C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96177C

  Dataset EGAD00001009462

• Single Cell Genome Sequence for DLP+ library A96180A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96180A

  Dataset EGAD00001009463

• Single Cell Genome Sequence for DLP+ library A96187A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 11, patient-derived xenograft SA609 passage 7 on DLP+ library A96187A

  Dataset EGAD00001009464

• Single Cell Genome Sequence for DLP+ library A96189A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049C passage 1 on DLP+ library A96189A

  Dataset EGAD00001009465

• Single Cell Genome Sequence for DLP+ library A96190B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96190B

  Dataset EGAD00001009466

• Single Cell Genome Sequence for DLP+ library A96192A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1093C passage 1, patient SA1147 on DLP+ library A96192A

  Dataset EGAD00001009467

• Single Cell Genome Sequence for DLP+ library A96194A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053B passage 1 on DLP+ library A96194A

  Dataset EGAD00001009468

• Single Cell Genome Sequence for DLP+ library A96194B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053E passage 1 on DLP+ library A96194B

  Dataset EGAD00001009469

• Single Cell Genome Sequence for DLP+ library A96200B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052D passage 1 on DLP+ library A96200B

  Dataset EGAD00001009470

• Single Cell Genome Sequence for DLP+ library A96205B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A96205B

  Dataset EGAD00001009471

• Single Cell Genome Sequence for DLP+ library A96206B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050F passage 1 on DLP+ library A96206B

  Dataset EGAD00001009472

• Single Cell Genome Sequence for DLP+ library A96207A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96207A

  Dataset EGAD00001009473

• RNA sequencing data of 257 samples from the CORALLEEN trial

  Early-stage Luminal B breast cancer is frequent and is a major cause of breast cancer death due to its poor prognosis. Our proposal aims to study the biology behind the sensitivity and resistance of Luminal B breast cancer to chemotherapy (CHT) or a non-CHT regimen composed of hormone therapy in combination with ribociclib, a CDK4/6 inhibitor. To accomplish this, we first completed the SOLTI-1402 CORALLEEN phase II trial, a study where 106 patients with early-stage Luminal B breast cancer were randomized to standard neoadjuvant CHT for 6 months, or neoadjuvant letrozole and ribociclib for 6 months. After treatment, patients underwent surgery. The primary results of the study, which showed that the response rate to letrozole+ribociclib was similar to CHT, was reported (Prat et al; Lancet Oncol). Tumor biopsies were available at baseline, week 3 and surgery. A total of 257 samples were analyzed using the Illumina TruSeq Stranded Total RNA w/Ribo Zero Gold with MiSeq in TGL (Sequencer NovaSeq S4/PE/100x)

  Dataset EGAD00001010121

• RNA sequencing in primary human macrophages overexpressing ETS2

  This dataset consists of RNA sequencing data from an ETS2 overexpression experiment in M0 macrophages. Controlled overexpression of ETS2 mRNA or control mRNA (an equivalent amount of mRNA encoding the reverse complement of ETS2 – thereby controlling for the quantity, length and purine/pyrimidine composition of the transfected RNA but with a transcript that would not be translated) was induced in resting, non-activated (M0) macrophages by transfecting predefined amounts of in vitro transcribed mRNA. To minimise non-specific activation due to the transfected RNA, in vitro transcription was performed using co-transcriptional capping (to minimise uncapped products), and incorporating modified, minimally immunogenic nucleotides (replacing uridine with N1-methyl-pseudouridine and cytidine with methylcytidine). After 18 hours, transfected cells were were activated with low dose LPS and harvested for RNA-sequencing 6 hours later. Sequencing libraries were prepared from 10ng RNA using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara) following the manufacturer’s instructions. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 and the libraries were sequenced on a NovaSeq6000. Raw data are provided as 100 bp paired-end Illumina reads from n = 8 donors.

  Dataset EGAD00001011341

• Insertion Site Analysis of T cells in a CD19-CAR Study on the T-SCM effect in B-cell malignancies

  Integration site analysis (ISA) was performed using a previously described non-restrictive vector-genome Junction amplification method combined with high-throughput sequencing59. Briefly, amplified gDNA was fragmented by sonication to generate ~1000 bp fragments and ligated to a linker cassette (LC) with a known sequence. Two rounds of exponential PCRs (35 cycles each) were conducted using primers specific to the vector long terminal repeats (LTRs) and the LCs. A final PCR step introduced Illumina adapter sequences and a unique index for each sample, enabling multiplexing for next-generation sequencing on the Illumina NextSeq 2000. A set of 24 fusion PCR primers was designed to bind the vector LTR, and a set of 24 fusion PCR primers designed to bind the LC (all primers were purchased from Integrated DNA Technology). Fusion PCR products were purified, quantified, and pooled in an equimolar fashion. Prepared pooled libraries were quantified and loaded onto the Illumina NextSeq 2000. Sequencing reads were demultiplexed based on the sample-specific indices and analysis of sequencing reads including mapping and annotation to the human genome (hg18 version) was performed using the IS-Seq bioinformatic pipeline.

  Dataset EGAD00001015540

• Mapping Cells and Interactions in the Thymus Across Development and Aging (2025-07-28)

  Single cell RNA sequencing on thymic cells from children with syndromic diseases such as Trisomy 21 and inflammatory/autoimmune diseases such as myasthenia gravis. Our group has previously performed atlasing of the healthy human thymus using single cell transcriptomics and obtained an unprecedented understanding of human thymus throughout development. In this study, we intend to survey diseased human thymus and compare this to healthy to obtain a better understanding of thymic dysfunction in human diseases. The diseases we will survey include congenital conditions such as Down's syndrome, CHARGE syndrome, DiGeorge syndrome as well as acquired diseases such as myasthenia gravis and thymic hyperplasia. We intend to perform genetic and genomic study on the samples, including expression analysis. This will not only help us to understand the cells and molecular pathways affected in dysfunctional thymus; but may also lead to generalisable understandings in human genetic diseases and inflammatory/autoimmune diseases. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2025-07-28.

  Dataset EGAD00001015660

• Comprehensive Deep Sequencing Atlas in HCC tumors

  Establishment of a comprehensive deep sequencing atlas focused on Hepatocellular Carcinoma (HCC) tumors, employing Whole Genome Sequencing (WGS), RNA Sequencing (RNAseq), and Whole Exome Sequencing (WES). The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with this liver cancer. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Study EGAS00001007694

• Single-cell profiling of neoantigen-specific T cells in lung cancers treated with neoadjuvant PD-1 blockade

  We study the expression profile of MANA-specific T cells, we used the MANA functional expansion of specific T cells (MANAFEST) assay in neoadjuvant anti-PD-1-treated lung cancers and applied their T cell receptor’s (TCR) complementarity-determining region 3 (CDR3) as a “barcode” to track and analyze their transcriptional programs in the tumor microenvironment using single cell TCR sequencing coupled with single cell RNA sequencing. We revealed distinct phenotype for MANA- and virus-specific clones in TIL and adjacent normal lung, regardless of response. MANA-specific T cells show features that drive the differences between responders and non-responders.

  Study EGAS00001005343

• Sequential single-cell transcriptional and protein marker profiling reveals TIGIT as a marker of CD19 CAR-T cell dysfunction in patients with non-Hodgkin’s lymphoma

  Employed single cell RNA sequencing and protein surface marker profiling of serialCAR-T cell samples from patients with non-Hodgkin’s lymphoma (NHL) to reveal CAR-T cell evolution, identify biomarkers of response, and test for evidence of exhaustion inCAR-T cells of poor responders. At the transcriptional and protein levels, we note the evolution of CAR-T cells toward a non-proliferative, highly-differentiated, andexhausted state that is enriched in CAR-T cells of patients with poor response.Furthermore, we identified the checkpoint receptor TIGIT as a novel prognosticbiomarker and potential driver of CAR-T cell exhaustion.

  Study EGAS00001005356

• Transcriptome analysis of endometrial organoids derived from patients with Mayer-Rokitansky-Küster-Hauser syndrome

  The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. The cause of the disease is still enigmatic. Here, we developed organoid cultures from endometrium found in uterine rudiment horns of MRKH patients. Phenotypically they share great similarity between healthy control organoids and are fully hormone responsive. Transcriptome analysis using RNA-seq identified possible disease-causing pathways altered in MRKH patients during development of the female reproductive tract. Thus, the organoid cultures provide a powerful research model for further insight into disease-causing alterations.

  Study EGAS00001005908

• TRACERx100 metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature, http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Dataset EGAD00001003301

• Ovarian Cancer Organoid Biobank

  WGS of ovarian cancer organoids, tumor samples and blood references. Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Dataset EGAD00001004387

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004192

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

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

  Dataset EGAD00001002693

• SNV and indel calls from 8921 individuals in the British Autozygosity Populations BioResource dataset

  This includes variant calls (single nucleotide variants and small insertions/deletions) from 8086 (mostly British Pakistani/British Bangladeshi) individuals from the following studies: 1. 5236 British Pakistani/British Bangladeshi adults from East London Genes and Health (ELGH) 2. 2624 British South Asian mothers from Born in Bradford (mostly Pakistani) (BiB) 3. 1061 British South Asian adults from Birmingham (mostly Pakistani) (Birm) All of the Birmingham and most of the Born in Bradford samples were previously sequenced as part of PMID: 26940866. In the sample list file, the columns of interest to most people will be: vcf.id - sample ID from the vcf cohort - which cohort they're in sex.assigned - sex inferred from coverage on the X and Y chromosomes. Individuals for whom this did not match their reported sex have been discarded total, chrX and chrY - coverage within bait regions across all chromosomes, chrX and chrY respectively Mapping was done with bwa-mem and variant calling was carried out with GATK HaplotypeCaller. We removed variant sites for which the following was true: SNPs: "QD < 2.0 || FS > 30 || MQ < 40.0 || MQRankSum < -12.5 || ReadPosRankSum < -8.0" Indels: "QD < 2.0 || FS > 30 || ReadPosRankSum < -20.0"

  Dataset EGAD00001005469

• Resuscitation Outcomes Consortium (ROC) Amiodarone, Lidocaine or Neither for Out-Of-Hospital Cardiac Arrest Due to Ventricular Fibrillation or Ventricular Tachycardia (ALPS)(ROC-ALPS-BioLINCC)

  Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Objective To compare the effects of amiodarone, lidocaine, and placebo on survival to hospital discharge after out-of-hospital cardiac arrest due to shock-refractory ventricular fibrillation or pulseless ventricular tachycardia. Background Ventricular fibrillation (VF) or pulseless ventricular tachycardia (VT) are common causes of out-of-hospital cardiac arrest, but are considered the most responsive to shock and therefore the most treatable. Nonetheless, most defibrillation attempts do not result in sustained return of spontaneous circulation, and VF or VT may persist or recur after shock. There is also evidence that longer durations of VF or VT are associated with decreases in the likelihood of resuscitation. Amiodarone and lidocaine are commonly used to promote successful defibrillation of shock-refractory VF or VT and prevent recurrences. Previous trials have shown amiodarone to be more effective than placebo or lidocaine for return of spontaneous circulation and survival at hospital admittance. This study sought to further extend the research and examine whether amiodarone would improve survival to hospital discharge and neurologic outcomes, as compared to placebo or lidocaine. Participants 3,026 eligible participants were enrolled, with 974 assigned to amiodarone, 993 assigned to lidocaine, and 1,059 assigned to placebo. An additional 1,627 participants that received a study intervention, but did not meet eligibility criteria, were included in analysis of the intention-to-treat population. Design The study interventions (amiodarone, lidocaine, and saline) were packaged in indistinguishable sealed kits and randomly distributed in to Emergency Medical Services (EMS) providers in a 1:1:1 ratio, stratified by participating site and agency. Each kit contained three syringes, and each syringe held 3 ml of colorless fluid containing 150 mg of amiodarone, 60 mg of lidocaine, or normal saline. Participants with out-of-hospital cardiac arrest were treated in accordance with local EMS protocols, in compliance with American Heart Association (AHA) guidelines. If VF or VT persisted or recurred after one or more shocks, eligible participants received a vasopressor and the masked kit containing amiodarone, lidocaine, or placebo. Approximating current clinical practice, the initial dose consisted of two syringes administered by rapid bolus. If the estimated body weight of the patient was less than 100 lbs., then one syringe was used. If VF or VT persisted, standard resuscitation measures, additional shocks, and an additional syringe of the study drug were administered. At that point the trial interventions were completed and standard interventions for advanced life support were employed. Upon arrival at the hospital, providers were notified of the patient's enrollment in the trial and encouraged to provide usual care in accordance with AHA guidelines, including open-label amiodarone or lidocaine if necessary. Components of hospital care were monitored but not standardized by the trial protocol. Participants, providers, and trial personnel were blinded to the trial drug assignments, with the exception of treating physicians if emergency un-blinding was required for care. Data from pre-hospital patient care records, CPR process measures, and hospital medical records were collected. The primary outcome of the trial was survival to hospital discharge, and the secondary outcome was survival with favorable neurologic status at discharge, defined as a score on the modified Rankin scale of 3 or less. Conclusions Neither amiodarone nor lidocaine resulted in a significantly higher rate of survival to hospital discharge or favorable neurologic outcome, as compared to placebo, among participants with out-of-hospital cardiac arrest due to initial shock-refractory ventricular fibrillation or pulseless ventricular tachycardia.

  Study phs003784

• National Cancer Institute (NCI) Adding Hispanics to Ongoing GWAS in Colorectal Cancer

  Genome-wide association studies (GWAS) of colorectal cancer (CRC) have been instrumental in identifying a number of common susceptibility loci in Non Hispanic (NH)-White populations, and a NCI priority is to extend GWAS findings to other populations to address racial/ethnic disparities in cancer susceptibility. Currently, GWA studies of CRC in NH-Whites, Japanese and African-Americans are ongoing. We propose a complementary study to address this critical research area in Hispanics. Hispanics represent the fastest growing ethnic population in the U.S. and have been largely understudied in terms of genetic susceptibility to cancer. There are noted differences in incidence, survival and mortality in CRC by ethnic/racial groups. Hispanics often present with CRC at a younger age and have a significantly greater incidence of stage IV tumors or metastatic disease compared to NH-Whites. We propose to conduct a large, cost-efficient, population-based GWAS in Hispanics by building upon existing NIH-funded resources, the Colon Cancer Family Registry (Colon CFR) and the Multiethnic Cohort Study (MEC). We plan to recruit 2,500 Hispanic men and women diagnosed with CRC between 01/2008 to present using cancer registries in California, physican referrals and familial referrals. Risk factor/diet questionnaires, pathology reports, Oragene saliva samples (for genotyping), optional blood samples (for genotyping and biometric analysis) and tumor blocks (for MSI testing) will be collected using methodologies developed in the Colon CFR/MEC. Cases of CRC in the MEC (currently 473; anticipated 600 at end) will also be included. Population-based Hispanic individuals without a diagnosis of CRC participating in other GWA studies in the MEC (n=3,900, U01HG004726, Haiman) will be used as controls. We will genotype all 3,100 cases using the Illumina 1M array and use available genotype and epidemiologic data collected on 3,900 controls. Our statistical analyses will include: single-SNP and haplotype effects, gene-environment interactions and heterogeneity by MSI, tumor subtype and family history of CRC. We will replicate findings in a second-stage using CRC cases and controls from Mexico (1,000 cases and 1,000 controls, EU FP7 funding, CHIBCHA, Carvajal-Carmona/Tomlinson). We will also examine heterogeneity of the risk estimates by ethnicity/race by leveraging GWA data on NH-Whites (2,142 cases, 1,909 controls, U01 CA122839, Casey), (4,000 cases, 6,000 NH-White controls, UK-CHIBCHA, Tomlinson), Colombians (2,000 cases and 2,000 controls, CHIBCHA), Japanese (1,000 cases and 1,000 controls) and African-Americans (1,500 cases and 1,500 controls, R01CA126895, Le Marchand). We will genotype replicated significant SNPs in our main and combined analysis in several Hispanic populations (note: studies funded by EU or NIH for data collection but not GWAS), including 800 Puerto Ricans, 2,000 Brazilians, 2,000 Argentineans and 3,000 Spanish/Portuguese, to assess generalizability of findings. We will examine the differences in inflammatory gene transcription dynamics in leukocytes (from blood sample collection) by fatigue level (as assessed from study questionnaire data). This study will have a high impact by addressing the key question of racial/ethnic disparities related to genetic susceptibility to CRC, will provide translational guidelines on biological mechanisms during the cancer survivorship period to increase quality of life among cancer survivors, and will enable further growth and investment into research among Hispanics by providing a resource of genetic data and biospecimens, which is lacking.

  Study phs001193

• Genome-Wide Analysis of Diffuse Large B-Cell Lymphoma (De Novo and Derived from the High Grade Transformation of Follicular Lymphoma)

  Version 1. Diffuse Large B-cell Lymphoma (DLBCL) represents the most common form of B-cell non-Hodgkin Lymphoma (B-NHL), accounting for ~30% of the de novo diagnoses and also arising as a frequent clinical evolution of Follicular Lymphoma (FL). The molecular pathogenesis of DLBCL is associated with multiple genetic lesions that in part distinctly segregate with individual phenotypic subtypes, suggesting the involvement of distinct oncogenic pathways. However, the lesions identified so far likely represent only a fraction of those necessary for malignant transformation. In order to characterize the entire set of structural alterations present in the DLBCL genome, we have integrated next generation whole exome sequencing analysis of 6 DLBCL cases and genome-wide high-density SNP array analysis of 72 DLBCL cases. We report here that FL and DLBCL harbor frequent structural alterations inactivating CREBBP and, more rarely, EP300, two highly related histone and non-histone acetyltransferases (HATs) that act as transcriptional co-activators in multiple signaling pathways. Overall, ~37% of DLBCL and 36% of FL cases display genomic deletions and/or somatic point mutations that remove or inactivate the HAT coding domain of these two genes. These lesions commonly affect a single allele, suggesting that reduction in HAT dosage is important for lymphomagenesis. We demonstrate specific defects in the acetylation-mediated inactivation of the BCL6 oncoprotein and activation of the p53 tumor suppressor. These results identify CREBBP/EP300 mutations as a major pathogenic mechanism shared by common forms of B-NHL, and have direct implications for the use of drugs targeting acetylation/deacetylation mechanisms. Version 2. Follicular lymphoma (FL) is an indolent, but incurable disease that, in 30-40% of cases, undergoes transformation to an aggressive diffuse large B cell lymphoma (DLBCL). The history of clonal evolution and the mechanisms that underlie transformation to DLBCL (tFL) remain largely unknown. Using whole exome sequencing and copy number analysis of 39 tFL patients, including 12 with paired sequential FL/tFL biopsies, we show that, in most cases, FL and tFL arise by divergent evolution from a common mutated precursor cell through the acquisition of distinct genetic lesions. Mutations in epigenetic modifiers (e.g., MLL2, CREBBP, EZH2, ARID1A) and anti-apoptotic genes (BCL2, FAS) were observed in 93% (36/39) and 78% (30/39) of cases, respectively, and were invariably shared between the two disease phases, suggesting an early acquisition in the common mutated precursor. Conversely, the development of tFL is associated with deregulation of genes involved in the control of cell proliferation, cell cycle progression and DNA damage responses (CDKN2A/2B, MYC, TP53), as well as with an aberrant activity of the somatic hypermutation mechanism. Finally, we show that the genomic profile of tFL shares significant similarities with that of germinal center B-cell type de novo DLBCL, but also displays unique combinations of altered genes that may explain the dismal clinical course of tFL.Version 3. This version includes thirty-five additional de novo DLBCL samples, newly diagnosed, and their paired normal DNA from previously untreated patients, which were analyzed by whole exome sequencing (n=27T and 25N), whole genome sequencing (8T and 10N), and/or targeted HLA-next generation sequencing (n=26T/N pairs) in order to identify genetic alterations associated with loss of surface MHC-II expression.

  Study phs000328

• Adipose Tissue Omics In Obesity

  This project used a multi-omics approach to study the adipose tissue transcriptome in humans with and without obesity. Our human cohort included males and females between the ages of 18-80 who underwent elective abdominal surgery at the University of Michigan and the Ann Arbor Veterans Affairs Healthcare System.Patients with advanced cancer or immuncompromised status were excluded. Visceral adipose tissue (VAT/omental) and subcutaneous adipose tissue (SAT/abdominal wall) were collected from subjects with obesity (BMI>=35) at the beginning of elective surgical procedures, placed on ice, and transported back to the laboratory for immediate processing. For adipose tissue stromal cells (ASC) isolation, adipose tissue was digested with Type II collagenase (2 mg/mL in PBS/2% BSA) at 37oC, 60min, centrifuged at 250 rcf, and the stromal-vascular cell pellet was retrieved, plated overnight, and the adherent cells passaged three times to enrich for ASC, which were then frozen in DMEM/F12, 15% fetal calf serum, and 10% DMSO in liquid nitrogen until use. Single nuclear sequencing was performed on preparations from intact adipose tissue. Bulk RNA sequencing and single cell sequencing were performed on ASC isolated from intact adipose tissue and cultured in 2D and 3D culture systems. We currently apply bulk, single cell, and single nuclear sequencing analyses to these tissues. One component of this project studies single nuclear sequencing in nuclei isolated from intact adipose tissues from human subjects with obesity, focusing on depot comparisons (VAT vs. SAT). This cohort also permits comparisons of adipose tissue transcriptomes between male and female subjects, controlling for age and BMI. Primary findings to date include identification of multiple ASC, adipocyte, and endothelial cell (EC) subpopulations, T-cell, and macrophage (MAC) populations that are in concordance with and expand upon other published datasets. Of two dominant ASC subpopulations, one (inflammatory-mesothelial, IM- ASC) is present in VAT, but absent in SAT, while the other (fibroadipogenic, FA-ASC) is present in both VAT and SAT. We identified multiple EC subtypes with features of lymphatic, venous, and arterial EC, and a PRDM16 expressing population with features of an EC progenitor. Immune cell populations match recent experimental validation of lipid-activated macrophage (LAM) phenotypes, TIM4 macrophages, and a prominent population of MRC1/CD206+ resident AT macrophages with expression signatures related to glucocorticoid activation. These data support depot-specific differences in ASC subpopulations and previously unrecognized EC heterogeneity within human AT, with the potential to shed light on functional differences in AT depot and disease state. Planned future studies include ATAC-Seq and other omics analyses. Another component of this project studies transcriptional responses of ASC in vitro to various stimuli, including different matrix environments. Current data includes bulk RNA Sequencing of human ASC from VAT and SAT differentiated into mature adipocytes in hydrogels of differing stiffness (3%, 5%, 10%) to define transcriptional responses to matrix environments of different stiffness. Primary findings to date include enrichment of adipogenesis and lipid and oxidative metabolic gene pathways in adipocytes in 5% relative to 3% hydrogels, while fibrotic gene pathways have been enriched in 3% hydrogels. These data demonstrate that intermediate density matrix promotes a more adipogenic, less fibrotic adipocyte phenotype geared towards increased lipid and aerobic metabolism. Planned future studies include expansion of intact tissues from our cohort studied with single nuclear sequencing, as well as further study of ASC responses in vitro to different biologic stimuli, including different matrix environments.

  Study phs003390

• ARDSNet 07-08: Randomized, Blinded, Placebo-Controlled, Multi-Center Trial of Omega-3 Fatty Acid, Gamma-Linolenic Acid, and Antioxidants in Acute Lung Injury or ARDS (OMEGA) (ARDSNet-Omega-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-Omega include bronchial lavage, plasma, urine, and DNA. Please note that use of biospecimens in genetic research is subject to a tiered consent.Objectives: To determine if dietary supplementation of omega-3 (n-3) fatty acids, γ-linolenic acid and antioxidants to participants with acute lung injury would increase ventilator-free days to study day 28.Background: Early acute lung injury (ALI) is characterized by neutrophilic lung inflammation, permeability, and intravascular and alveolar fibrin deposition. The type and inflammatory activity of eicosanoids liberated during inflammation depends on the membrane phospholipid composition: omega 6 (n-6) fatty acid arachidonate yields highly reactive and inflammatory dienoic prostaglandins and series 4 leukotrienes, whereas omega-3 (n-3) fatty acids favor production of less active and potentially anti-inflammatory trienoic prostaglandins and series 5 leukotrienes. Participants at risk of developing ALI have n-3 levels approximately 25% of normal and those with established ALI have n-3 levels as low as 6% of normal, suggesting a potential role for n-3 dietary supplementation in participants with ALI.Three randomized controlled studies, conducted in participants with ALI or sepsis-induced respiratory failure, demonstrated an association between the administration of an enteral formula enriched in n-3 fatty acids, GLA, and antioxidants and improved oxygenation and respiratory physiology compared with an unenriched, high-fat formula. However, interpretation of these results is limited by the small sample sizes and as-treated analyses of only those participants who tolerated full enteral nutrition. Participants: The total number of participants in the study was 272.Design: Participants were stratified by hospital and the presence of shock at baseline and then randomized to receive either twice-daily enteral supplementation of n-3 fatty acids, GLA, and antioxidants (n-3 supplement) or an isocaloric-isovolemic carbohydrate-rich control. Participants were also simultaneously randomized to a separate ongoing trial (the EDEN study) comparing low- vs full-calorie enteral nutrition in a 2×2 factorial design.The n-3 or control supplement was administered enterally as twice-daily boluses of 120 mL beginning within 6 hours of randomization. Dosing continued until the earliest of 21 days, 48 hours of unassisted breathing, or extubation. The energy provided by the boluses supplemented that provided by each primary physician's choice of standard continuous non–n-3-enriched enteral formula. The rate of continuous enteral feeding was managed by a protocol with an algorithm for gastrointestinal intolerances. The supplement was administered even if enteral nutrition was interrupted, as long as the patient was tolerating enteral medications. Conclusions: The study was stopped by the DSMB for futility at the first interim analysis after 143 participants had been randomized to receive the n-3 supplement and 129 to receive the isocaloric control. Despite an 8-fold increase in plasma eicosapentaenoic acid levels, participants receiving the n-3 supplement had fewer ventilator-free days, intensive care unit–free days, and nonpulmonary organ failure-free days.

  Study phs003744

• Asthma in the Lives of Families Today (ALOFT)

  Social interactions and the overall psychosocial environment have a demonstrated impact on health, particularly for people living in disadvantaged urban areas. Here we investigated the effect of psychosocial experiences on gene expression in peripheral blood immune cells of 251 children with asthma in Metro Detroit. Participants were included from an ongoing longitudinal study Asthma in the Lives of Families Today (ALOFT; recruited from November 2010-July 2018. The ALOFT project was established to identify the behavioral and biological pathways through which family social environments impact youth with asthma.In version 1 we used RNA-sequencing and a new machine learning approach to identify transcriptional signatures of 19 variables including psychosocial factors, blood cell composition and asthma symptoms. Using longitudinal data collected from a subset of the participants we showed that transcriptional signatures track the longitudinal changes in measured phenotypes. Importantly, we found 169 genes associated with asthma that are regulated by psychosocial factors, and 344 significant gene-environment interactions for gene expression levels. These results demonstrate that immune gene expression mediates the link between negative psychosocial experiences and asthma risk.In version 2, we focused on pubertal development. We identified substantial gene expression changes associated with age and pubertal development. We showed that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.Version 3 uses single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.Version 4 adds scATAC-seq in activated peripheral blood mononuclear cells (PBMC) from 16 children with asthma with phytohemagglutinin (PHA) or lipopolysaccharide (LPS), and treated with dexamethasone (DEX), an anti-inflammatory glucocorticoid. We analyzed changes in chromatin accessibility, measured transcription factor motif activity, and identified treatment and cell-type specific transcription factors that drive changes in both gene expression mean and variability. We observed strong positive linear dependence between motif response and their target gene expression changes, but negative in variability changes. This result suggests that an increase of transcription factor binding tightens the variability of gene expression around the mean. We then annotated genetic variants in chromatin accessibility peaks and response motifs followed by computational fine-mapping of eQTL signals from a pediatric asthma cohort. We found that eQTLs were 5-fold enriched in peaks with response motifs and refined the credible set for 410 asthma risk genes, with 191 having the causal variant in response motifs. These results enhance the understanding of molecular mechanisms for asthma risk variants mediated by gene expression.

  Study phs002182

• DAC for study "Single-nucleus brain transcriptomics reveals microglia dysfunction in Multiple System Atrophy"

  Dataset containing snRNA-seq samples from MSA or PD patients, and healthy controls. We aimed at identifying molecular processes at the single cell level that could identify common and/or disease-specific differences between healthy controls and patient groups. Frozen tissue samples from healthy controls, and multiple system atrophy or Parkinson's disease patients were excised and single nuclei were isolated following the 10x Genomics Chromium workflow.

  Dac EGAC50000000809

• Bulk RNASeq of DLL1 positive or negative cells in two different metastatic colorectal cancer organoids under cetuximab treatment

  Standard Poly-A enriched stranded RNASeq libraries were obtained from DLL1 positive and negative subpopulations on two different mestastatic colorectal cancer organoids under cetuximab treatment. Paired sequencing was performed on a NovaSeq 6000 with 100bp reads aiming at 70M clusters. 8 fastq files have been deposited for the 4 samples.

  Dataset EGAD50000002555

• 10X single-cell Multiome (RNA+ATAC) of cord blood-derived HSPC

  10X genomics chromium single-cell ATAC+RNA (Multiome) was use to prepare single-nucleus RNA- and ATAC-seq libraries, sequenced on an Illumina NovaSeq 6000 platform. BAM files are provided. Samples from 4 donors were sequenced after sorting for primitive HSPCs in 2 libraries, each with cells from 1 male and 1 female CB.

  Dataset EGAD50000002327

• ALS-FTD brain motor cortex single-nucleus RNA-seq of NeuN+ nuclei sorted for TDP-43 low vs. high

  A dataset of single-nucleus RNA-seq data of nuclei from the post-mortem human primary motor cortex from patients with ALS-FTD. The nuclei were sorted by flow cytomotetry into NeuN+ (neuronal) TDP-43 low vs. TDP-43 high fractions.

  Dataset EGAD50000002243

• Single-cell DNA sequencing dataset of aplastic anemia and RCC (31 samples)

  This dataset contains raw single-cell DNA sequencing data generated from 31 patients with aplastic anemia using the Mission Bio Tapestri platform. Libraries were prepared with a targeted DNA amplicon panel and sequenced on an Illumina platform. These raw data capture single-cell variant profiles and clonal architecture and serve as the basis for downstream analysis of somatic mutations and clonal hematopoiesis.

  Dataset EGAD50000002189

• MOSAIC Window Glioblastoma Data

  This dataset will include Spatial Transcriptomics, Single-Cell RNA-Seq, Bulk RNA-Seq, Clinical data, WES, and H&E data from 10 Glioblastoma (GBM) Cancer patients. Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001352

• Total RNAseq data from 8 patients with muscle invasive bladder cancer

  For this dataset we performed total RNAseq on blood samples from 8 patients with muscle invasive bladder cancer. The data consists of 8 sets of paired fastq files with accompanying UMI fastq files. Sequenced on the Illumina NoveSeq6000 platform using S2 flow cells (v1.5,2x150 cycles), with a mean yield of 313 million reads.

  Dataset EGAD50000001380

• ATAC-seq for 2 samples

  This dataset contains ATACseq data from ta primary sample and a patient derived model (PDX) of the novel FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001791

• RNA-seq for 8 samples

  This dataset contains RNA-seq data from 8 acute leukemia cases (diagnosis or relapse) belonging to a newly identified subtype, termed FOXF1/FENDRR ALL. All the 8 samples are in bam file type.

  Dataset EGAD50000001789

• 10x Genomics scRNA-seq for 3 samples

  This dataset contains 10x Genomics single-cell RNA-seq data from two primary leukemia samples and their corresponding patient-derived xenograft (PDX) models. All the 3 samples are in bam file type.

  Dataset EGAD50000001788

• Bulk RNA-sequencing data from five lines of human iPSC-derived (hiPSC-derived) astrocytes, both alone and in co-culture with neurons, to define the molecular response of astrocytes to misfolded alpha-synuclein.

  Samples were derived from five lines of human iPSC-derived (hiPSC-derived) astrocytes, both alone and in co-culture with neurons +/- alpha-synuclein oligomer treatment. Paired-end FASTQ files for each of the samples are provided.

  Dataset EGAD50000001109

• WES IDC samples

  PDX samples of breast cancer IDC mouse models created from patient tumor material of the NKI. Genomescan prepared the samples according to the procedure for Hybridization Capture using the Agilent SureSelectXT Human All Exon V7 kit. The prepared libraries were sequenced with Illumina sequencing technology. The samples are in fastq format and consist of the following PDX samples: IDC001, IDC125, IDC147, IDC200, IDC233, IDC244, IDC251, IDC272, IDC278, IDC281 and ILC120.

  Dataset EGAD50000001148

• Dataset for WGS and RNA samples of acute myeloid leukemia with MNX1 expression

  This dataset contains 10 samples of WGS, ATAC, 4C and RNAseq samples of patients with acute myeloid leukemia. The sequencing was performed on Illumina HiSeq 4000, 2000 and HiSeq X using Illumina TruSeq Nano DNA and Agilent Strand Specific RNA Kits. The sequencing was always paired.

  Dataset EGAD50000001098

• Dataset for Multiple Myeloma RNA data

  This dataset contains 371 case and control RNA sequencing samples of patients with multiple myeloma. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X, HiSeq 4000 and HiSeq 2000 using TruSeq Stranded RNA and TruSeq Stranded total mRNA Kits. The sequencing was always paired.

  Dataset EGAD50000000683

• mRNA-Sequencing of 73 primary multiple myeloma (MM) samples and human MM cell lines

  mRNA-Sequencing of 73 primary multiple myeloma (MM) samples and human MM cell lines before and after siRNA-mediated knockdown of ADAM8 (n=5 cell lines), ADAM9 (n=7 cell lines) and ADAM15 (n=5 cell lines). Paired-end sequencing was performed on a NovaSeq (Illumina). Fastq and bam files are provided for each sample.

  Dataset EGAD50000000575

• NSCLC ctDNA multigenic panel

  We analyzed cfDNA plasma samples of subjects with non-small cell lung cancer: treatment naïve (n=24) and prior-treated (n=8). Driver variants for 11 genes was available with Oncomine Lung cfDNA Assay, were assessed by Next-Generation Sequecing. Sequencing data were pre-processed in Ion S5 Torrent Server and aligned to the hg19 human reference genome. Variant calls were performed by IonReporter 5.10 software.

  Dataset EGAD50000000908

• Dataset for desmoplastic small round cell tumor - RNA

  This dataset contains 32 RNA sequencing samples of patients with desmoplastic small round cell tumor. Sequencing was performed on Illumina HiSeq 2500, Illumina HiSeq 4000, Illumina HiSeq X and NovaSeq 6000 using Illumina TruSeq RNA and TruSeq Stranded RNA Kit. The sequencing was always paired.

  Dataset EGAD50000000912

• CRC cell line ChIP-seq

  ChIP-Seq data for CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3 in C32, CL11, HT29, SW403, SW480, SW948 MSS CRC cell lines

  Dataset EGAD50000000295

• Exome sequencing of samples for Corvin_Dublin_BipEx

  This research project was a collaboration between Trinity College Dublin, Ireland and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 191 Bipolar case/control samples from collaborators in Ireland. Genomic DNA from each sample was sequenced to a mean depth of 20x. The project used Illumina WXS sequencing of DNA and the file type is cram.

  Dataset EGAD50000000392

• DNA sequening

  The dataset consist of DNA and RNA sequencing results and metadata of the samples. All sample numbers starting with 6716 are tumor samples which has been sequenced using WES (see BAM files). It concerns biopsies of metastatic lesions from patients with BRAFV600 mutated melanoma, obtained before, during and after the study treatment (see samples metadata) and in some cases blood for germline mutation analysis. Sequencing is performed using the Illumina Novaseq 6000 system.

  Dataset EGAD50000000382

• Suspected Lynch syndrome dataset

  This dataset comprises a genomic and a phenotypic excel sheet displaying 137 cases classified as suspected Lynch syndrome. Included are genotypic data such as tumour mutational burden, tumour mutational signatures and germline/somatic variant calls for each colorectal, endometrial or sebaceous skin tumour screened. Genomic data is derived from targeted multigene panel sequencing including ~300 hereditary cancer genes.

  Dataset EGAD50000000031

• H3Africa AWIGEN Pilot MetaboChip

  Pilot study on the interplay between genetic, epigenetic, and environmental risk factors for obesity and related cardiometabolic diseases with 973 samples from South Africa genotyped on Illumina Human MetaboChip array.

  Dataset EGAD00010001258

• Sequencing data for oesophageal and related samples - BOs release 5 (RNA)

  Dataset EGAD00001005385

• Mutation analysis in human iPS cells

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced by MiSeq. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000357

• WGS - germline - oral squamous cell carcinoma

  We conducted a retrospective, single-center Canadian cohort study of patients who underwent primary surgery for OSCC between 2010 and 2024. Nucleic acid quality was assessed using the 4150 TapeStation System (Agilent) prior to library preparation. WGS was performed on germline DNA, following Genome Analysis Toolkit’s (GATK) Best Practices and procedures, with a target of 30X deduplicated coverage per sample, using an Illumina NovaSeq 6000 instrument.

  Dataset EGAD50000002608

• Whole genome DNA sequencing for two long-lived humans.

  Two long-lived human samples were sequenced to a mean 20x coverage genome wide. Sequencing was done using the Illumina hi-seq platform, alignment to GRCh37/hg19 reference genome was done using the BWA alignment tool.

  Study EGAS00001000877

• arrayCGH for copy number profiling on tumor DNA from pediatric cancer tissue samples

  This dataset contains arrayCGH (HumanCytoSNP 850k and HumanCytoSNP v12.1) data from tumor DNA samples of various pediatric cancer entities. Files are provided in IDAT format and as text files processed with GenomeStudio 2.0.

  Study EGAS00001005197

• Mate Pair Sequencing data for Molecular Characterization of ETMRs

  This dataset contains Mate Pair Sequencing data from 15 samples from 13 patients. Mate pair DNA library preparation was carried out using the Illumina MP v.2 reagents and protocol. In brief, fragmentation of genomic DNA was performed using a Hydroshear device to an insert size of 4.5 kb followed by sequencing with Illumina HiSeq 2000 instruments resulting in 30 Fastq files (paired end).

  Dataset EGAD00001006207

• 10X 3' V2 data of single immune cells in hepatocellular carcinoma

  The immune microenvironment of hepatocellular carcinoma (HCC) is poorly characterized. Combining two single-cell RNA sequencing technologies, we produced transcriptomes of CD45+ immune cells for HCC patients from five immune-relevant sites: tumor, adjacent liver, hepatic lymph node (LN), blood, and ascites. This is the droplet data of this study

  Dataset EGAD00001005961

• scRNA primaries

  Single cell RNA-seq for primary samples

  Dataset EGAD00001006135

• scWGS chordblood

  Single cell WGS (low pass) for chord blood samples

  Dataset EGAD00001006136

• scWGS PDX

  Single cell WGS (low pass) for PT1-derived PDX samples

  Dataset EGAD00001006137

• scWGS primaries

  Single cell WGS (low pass) for primary samples

  Dataset EGAD00001006138

• Transcript read counts derived from RNA sequencing data collected for NABUCCO cohort 1 (NCT03387761)

  Data from NABUCCO cohort 1 (NCT03387761). This dataset includes the Transcript read counts derived from the RNA sequencing data. The samples are pre-treatment (n=18) and post-treatment (n=18), and not all samples are paired. The data processing pipeline can be found on the Methods section from the Nature Medicine paper (https://doi.org/10.1038/s41591-020-1085-z)

  Dataset EGAD00001006854

• PCCRC versus prevalent CRC

  To analyse genome wide DNA copy number changes in combination with mutation status of CRC-related genes, CIMP and MSI, in order to explore the biology of PCCRCs. Formalin-fixed, paraffin-embedded samples from 122 PCCRCs and 98 prevalent CRCs collected in 3 different hospitals in the region of South Limburg, the Netherlands, were used in this study. DNA was extracted for molecular analysis. Labels have been updated.

  Dataset EGAD00001006987