14970 results for "cancer studies using rna-seq"

in 43.12 milliseconds.

• single-nuclei RNA-seq of primary pineal parenchymal tumors

  Raw fastq files for 10x Chromium snRNA-seq of pineal parenchymal tumors profiled in the study "A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies".

  Dataset EGAD50000002101

• Single-cell RNA-Seq (Chromium Next GEM Single Cell 3' Reagent Kits v3.1 from 10X Genomics )

  Human data for transcriptome (scRNA-Seq) in CD34+ B cell precursors.

  Dataset EGAD00001010907

• EGAD00000000046

  RNA-SEQ data from 3 recurrent and 1 ovarian primary Granulosa Cell Tumour samples

  Dataset EGAD00000000046

• Single-cell RNA-seq data from 3 HGSOC patient-derived organoids and corresponding tumor or ascites

  Study EGAS00001006246

• Uni_Wue_Chair of Microbiology

  Dual RNA seq datasets of M2 sequenced macrophages after chlamydia infection for 30 hours.

  Dac EGAC50000000577

• ssRNA

  single cell RNA-seq

  Dataset EGAD00001008996

• Long-read RNA-seq from 5 patients with stereotyped subset CLL

  Oxford Nanopore Technologies based long-read RNA sequencing data from 5 patients with stereotyped subset CLL. The BAM files were aligned against hg19 reference genome.

  Dataset EGAD50000000755

• RNA-seq of frontal post-mortem human brain tissue

  RNA-sequencing dataset of post-mortem human brain tissue of FTD patients with mutations in GRN, MAPT and C9orf72 and healthy controls.

  Dataset EGAD00001008014

• RNA sequencing of human lung fibroblasts

  Bulk RNA seq data from human lung fibroblasts isolated from fresh and cryopreserved lung tissue (18 samples, 3 donors)

  Dataset EGAD00001010252

• Italian Primary Biliary Cirrhosis Study

  A Genome-wide association study of primary biliary cirrhosis (PBC) with an Italian cohort and loci meeting suggestive criteria were confirmed using a replication dataset from a previous Canadian study. The results confirmed associations for IL12A, IL12RB2, and HLA (peak between DQA1 and DQB1) and identified novel associations with IKZF3/ORMDL3 on chromosome 17, SPIB on chromosome 19, and IRF5 on chromosome. These studies also provided definition of haplotypic associations, differences between the PBC associated chromosome 17 haplotype and that of pediatric asthma and suggested several other genes as candidates for PBC susceptibility including DENND1B.

  Study phs000444

• 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

  Study EGAS00001006535

• 10X snRNA-seq data from human FCDII postoperative brain tissues with mTOR pathway mutations

  Focal cortical dysplasia type II (FCDII) is linked to mTOR pathway mutations and drug-resistant epilepsy. Using 10X snRNA-seq on postoperative FCDII brain tissues, we characterized transcriptional alterations across cell types, revealing mTOR-related dysregulation. These findings provide insights into FCDII pathology and potential therapeutic target

  Study EGAS50000000964

• Epigenetic analysis of clear cell renal cell carcinoma using ChIP-seq

  To investigate the epigenetic landscape of clear cell renal cell carcinoma (ccRCC), we performed ChIP-seq data for the CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, and HIF1A marks in the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as the 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 narrowPeak formats. Data were processed using the nf-core chipseq pipeline.

  Dataset EGAD50000001886

• Exome sequencing data from tumor progression cohort

  This dataset, named Stockholm tumor progression cohort, contains exome-sequencing samples of matched primary and metastasis samples from 20 metastatic breast cancer patients. All patients have one or more sequenced normal samples as well. The total number of samples is 125. The dataset has been used, apart from other studies, to explore tumor evolution patterns in metastatic breast cancer at Karolinska Institute Stockholm.

  Dataset EGAD00001003837

• single-cell RNA-sequencing of human/mouse colonic crypts

  Human colonic stem cells are slow cycling compared with murine rapid cycling stem cells. Our study aims to identify slow cycling stem cell in human normal colon in vivo and to analyze gene signatures among rapid cycling stem cells, slow cycling stem cells and secretory progenitor cells using single cell RNA-seqencing . We further investigated in vivo dynamics of human colonic stem cell using patient-derived gene-enginered organoids and orthotopic xenotransplantation.

  Study JGAS000550

• Epigenomic dataset of Human Hepatocellular Carcinoma for EpiHK

  This dataset is generated for EpiHK. It contains Histone PTM ChIP-seq, WGBS, RNA-seq of 7 Human Hepatocellular Carcinoma and 7 tumor adjacent normal tissue sample.

  Dataset EGAD50000000058

• Esophageal Squamous Cell Carcinoma Precursor Study

  Esophageal cancer is the sixth most common cause of cancer death in the world. High-risk areas occur across central Asia and from eastern to southern Africa, and in these populations, nearly all of the cases are esophageal squamous cell carcinoma (ESCC). ESCC has a dismal prognosis, largely because symptoms usually appear late in the course of the disease, when the tumors are incurable. Early detection and treatment of curable precursor lesions and early invasive ESCC in asymptomatic high-risk adults offers the potential for long-term survival and reduced mortality from this disease. Previous studies have shown that routine cytology of non-endoscopically collected esophageal cell samples is not sensitive and specific enough to be clinically useful, so we are now looking for molecular markers of high-grade esophageal squamous dysplasia (HGD), the proven clinically important precursor lesion of ESCC, that can be used to increase the accuracy and utility of this initial screening exam. National Cancer Institute (NCI) and Cancer Institute and Hospital, Chinese Academy of Medical Sciences (CAMS) began collaborative studies of ESCC since the mid-1980s in China. The present proposal is designed to characterize the type and prevalence of DNA mutations in tissue samples of HGD and to establish biologic and questionnaire resources for further study. The proposed study has two components, a field study to obtain questionnaire data and biological samples, and a genomic analysis to perform sequencing of the biological samples and bioinformatics analysis of the sequencing. 

  Study phs002814

• RNA-seq of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Study EGAS00001008182

• 10x Genomics single-cell RNA sequencing of cerebrospinal fluid

  This dataset contains fastq files from single-cell RNA sequencing of cerebrospinal fluid of 81 patients with multiple sclerosis (n=33) or other neurological disease (n=48) using the 10x Genomics Chromium single cell 3’ v2 chemistry. Sequencing was performed using an Illumina HiSeq4000 sequencer.

  Dataset EGAD50000000184

• Single-cell RNA-sequencing of peritoneal fluid from patients with achalasia

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peritoneal fluid (PF) from patients with achalasia. Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000251

• Gene Fusion Discovery through RNA Sequencing of Human Glioblastoma Stem Cell Lines

  We used massively parallel, paired-end sequencing of expressed transcripts (RNA-seq) to detect novel gene fusions in short-term cultures of glioma stem-like cells freshly isolated from nine patients carrying primary glioblastoma multiforme (GBM). The culture of primary GBM tumors under serum-free conditions selects cells that retain phenotypes and genotypes closely mirroring primary tumor profiles as compared to serum-cultured glioma cell lines that have largely lost their developmental identities.

  Study phs000505

• Expression profiling of Gorlin iPSCs in the osteoblast induction culture

  In this study, we utilized human induced pluripotent stem cell (iPSC)-based models of the two diseases, named Gorlin syndrome and McCune Albright synfrome, to understand the roles of Hh signaling in osteogenesis, especially in mineralization. To examine which signaling pathways and genetic networks were affected by Gorlin syndrome-associated PTCH1 mutation in human osteoblastogenesis, we performed RNA sequencing (RNA-seq) analysis in the osteoblast induction culture of WT and Gorlin iPSCs.

  Study JGAS000218

• Circulating Genomic Determinants of Treatment Failure in Hodgkin Lymphoma

  In this study, we show that the plasma representation of mutations exceeds the bulk tumor representation in most cases, making classic Hodgkin Lymphoma (cHL) particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumors, we demonstrate hazard ratios (HRs) circulating tumor DNA (ctDNA) shedding to be shaped by DNASE1L3, whose increased tumor microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R-mutations that are dependent on IL13 signaling and therapeutically targetable with IL4R blocking antibodies. Finally, we demonstrate the clinical value of pre- and on-treatment ctDNA levels for longitudinally refining cHL risk prediction, and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL as well as capturing molecularly distinct subtypes with diagnostic, prognostic, and therapeutic potential.Methods utilized include a) targeted genotyping of baseline plasma samples, b) whole exome sequencing (WES) of baseline plasma samples, c) epigenetic expression inference from cell-free DNA-sequencing (EPIC-Seq) to infer gene expression from cell-free DNA (cfDNA) fragmentation profiles, d) ctDNA tracking in on-treatment samples, e) RNA-Sequencing, and f) Phased variant Enrichment and Detection Sequencing (PhasED-Seq).All patients were treated at cancer centers across Europe and North America between 2011 and 2020. The following 3 cancer centers, Stanford (CA, USA), Bellinzona [Confoederatio Helvetica (CH) or Switzerland], and Leuven (Belgium), were included. The 6 clinical trial collectives included in this study are the Phase III trial AHOD1331 trial (NCT02166463) and the Phase II cHOD17 study (NCT03755804) for enrolled pediatric patients, the Phase III AHL2011 (NCT01358747), the Phase II BREACH trial (NCT02292979), a pilot study evaluating concurrent Pembrolizumab with AVD (Doxorubicin, also known as Adriamycin, Vinblastine, and Dacarbazine; NCT03331341), and a Phase II study evaluating PVAB (Prednisone, Vinblastine, Doxorubicin and Bendamustine; NCT02414568) in older patients (61 years and older). In addition, lymph node specimens from a biorepository at St. Jude Children's Research Hospital (TN, USA) were included.

  Study phs003435

• Epigenomic atlas of organoid development

  To investigfate the epigenomic basis of fate decisions in the central nerveous system, we recorded a epigenomic timecourse of human brain organoid development using Cut&Tag with paired scRNA-seq. We further performed perturbation experiment inhibiting EED and profiled the response with scRNA-seq and Cut&Tag. Finally, we profiled a sample of the developing human brain using multiome sequencing and Cut&Tag. In our study, we uncover epigenomic switches during brain region diversification and show that epigenetic activation precedes gene expression during neurogenesis in organoids and in primary tissue. Lastly, we show that transcriptional repression by H3K27me3 is required to stabilize neuroectoderm induction from pluripotency.

  Study EGAS50000000155

• Transcriptomic analysis of metastatic colorectal cancer

  Metastatic colorectal cancer (mCRC) is the main cause of CRC mortality, with limited treatment options. Although immunotherapy has benefited some cancer patients, mCRC typically lacks the molecular features that respond to this treatment. However, recent studies indicate that the immune microenvironment of mCRC may be modified to enhance the effect of immune checkpoint inhibitors. This dataset was used to explore the metastatic immune microenvironment by comparing immune cell populations in colorectal liver (CLM), lung (mLu) and peritoneal (PM) metastases.

  Dataset EGAD50000000926

• Population Architecture using Genomics and Epidemiology (PAGE)

  PAGE II (2013-2017) seeks to expand understanding gained during PAGE I and similar studies of how ancestry-specific differences in allele frequencies and LD may explain differences in risks of common traits and conditions. Recent studies have identified rare genetic variants that are likely to contribute to common diseases and traits and observed that rare variants likely to be functional, such as those in coding and regulatory regions, tend to be population-specific. PAGE II has genotyped over 50,000 samples using MEGA, an Illumina high density custom exomechip array. The MEGA data is being imputed in PAGE to the 1000 Genomes panel. PAGE also sequenced 1,000 samples representative of 21 populations from the Americas. PAGE has harmonized phenotype data for ~300 trait variables. These datasets will be analyzed to continue emphasis on characterizing population-level disease risks in non-European-descent individuals. Cohorts in PAGE II are: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, HCHS/SOL, Strong Heart Studies), ISMMS (Mount Sinai BioMe Biobank), MEC (Multiethnic Cohort), WHI (Women's Health Initiative), and Stanford University (PAGE Global Reference Panel). Genotyping services were provided by the Center for Inherited Disease Research (CIDR) and sequence data were provided by the McDonnell Genome Institute at Washington University School of Medicine. PAGE I (2008-2013): The first phase of PAGE examined putative causal genetic variants across approximately 100,000 African Americans, Asian Americans, American Indians, European Americans, Hispanic Americans, and Native Hawaiians from four groups representing nine large U.S.-based cohorts. Two genotyping approaches were employed - targeted genotyping of selected SNPs identified in genome-wide association studies of common disease, and a large-scale effort focused on the Metabochip array, which facilitated trans-ethnic fine mapping of several diseases of public health importance. Cohorts in PAGE I were: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, CHS, HCHS/SOL, Strong Heart Cohort Study, Strong Heart Family Study), EAGLE (Epidemiologic Architecture for Genes Linked to Environment, based on 3 National Health and Nutrition Examination Surveys (NHANES)), MEC (Multiethnic Cohort) and WHI (Women's Health Initiative). Logistical and scientific support is provided by the PAGE Coordinating Center and the NHGRI Division of Genomic Medicine. PAGE II is funded by the NHGRI and the NIMHD. To access PAGE studies currently available in dbGaP, please click on the links below.Please note that some PAGE studies belong to larger cohorts and have been included as PAGE substudies. For those studies, there is an additional link to the parent study. phs000223 PAGE-ARIC and phs000280 ARIC Cohort phs000236 PAGE-CARDIA and phs000285 CARDIA Cohort phs000301 PAGE-CHS and phs000287 CHS Cohort phs000559 PAGE-EAGLE-BioVu phs000208 PAGE-EAGLE-NHANES phs000555 PAGE-HCHS/SOL and phs000810 HCHS/SOL Cohort phs000220 PAGE-MEC phs000580 PAGE-SHS and SHFS phs001033 PAGE Global Reference Panel phs000227 PAGE-WHI and phs000200 WHI Cohort

  Study phs000356

• The Landscape of N-6 Methyladenosine in Primary Localized Prostate Cancer

  Using meRIP-sequencing, we profiled N-6 methyladenosine (m6A) in a cohort of 148 primary prostate cancer samples as part of the Canadian Prostate Cancer Genome Network project (CPC-GENE). Paired-end sequencing of 150 bp reads were mapped to GRCh38.p13 using annotations from gencode.v34.chr_patch_hapl_scaff.annotation.gtf. Peaks were called using MeTPeak, joint peaks were identified and IP reads were quantitated, normalized and adjusted using Input reads to obtain estimates of m6A abundance.

  Study EGAS00001006925

• Genomic Characterization CS-MATCH-0007 Arm N

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH clinical trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm N is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PTEN mutation, or deletion with PTEN expression on IHC, are treated with the drug GSK2636771. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002151

• Adjuvant nivolumab in resected esophageal or gastroesophageal junction cancer: exploratory biomarker analyses from CheckMate 577

  Adjuvant nivolumab demonstrated a significant improvement in disease-free survival (DFS; primary endpoint) versus placebo in patients with resected esophageal or gastroesophageal junction cancer and residual pathologic disease following neoadjuvant chemoradiotherapy (CRT) in the phase III CheckMate 577 study, leading to global approval and widespread adoption. Exploratory biomarker analyses were performed using whole-exome sequencing, RNA sequencing, and immunohistochemistry. Hazard ratios for DFS favored nivolumab versus placebo in patients with higher inflammation and proliferation gene expression signature scores; lower M2 macrophage, endothelial, and stromal GES scores; and higher densities of CD3+/CD8- T cells and natural killer cells. Assessments of pre-CRT and post-CRT tumor tissue found post-CRT increases in programmed death ligand 1 combined positive score in 51% of patients, which appeared to be associated with greater DFS benefit. Through these analyses, we identified patient subpopulations that appear to derive improved DFS benefit from adjuvant nivolumab in this setting.

  Study EGAS50000001663

• The paired FF/FFPE colon set, RNA-Seq

  Dataset EGAD00001000831

• RNA-seq of CML074 Tumor tissue; Timpepoint 1

  Dataset EGAD00001001259

• RNA-seq of CML074 Tumor tissue; Timpepoint 2

  Dataset EGAD00001001260

• Transcriptional profiling of tauopathies in human IPS-derived neurons (2019-08-21)

  This project is a pilot study, in collaboration with Maria Grazia Spillantini and Mariangela Iovino (Cambridge Centre for Brain Repair), to investigate the utility of IPS-derived neurons for the study of neurodegenerative disorders. Our aim is to characterise the transcriptional consequences of tauopathies using neurons derived from differentiated IPSCs as a model system. We will use IPS cells derived from six individuals, four with known mutations in the tau protein, 2 without. RNA will be extracted at Day 0 and Day 65 of differentiation by which time the neuronal tauopathy is apparent. RNA will be extracted and the transcriptome of each line characterised using RNAseq. We will then search for genes that are differentially expressed between the transcriptomes of individuals with tau mutations versus those in controls. My lab will analyse the RNAseq data, comparing both affected and controls and both time-points, to establish candidate genes. Darren Logan’s lab, along with our collaborators, will experimentally verify and further investigate these genes in additional lines and animal models. From this analysis we will generate a list of candidate genes that are differentially expressed between cases and controls. This study will not only help us understand the molecular basis of tauopathies, but also identify gene candidates for biomarkers of neurodegenerative disease. It will serve as a proof of principle for future planned studies into generating and transcriptomically analysing an allelic series of Tau mutations in IPSCs with a controlled genetic background. 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 2019-08-21.

  Dataset EGAD00001005277

• A Genome-Wide Association Study of Sporadic ALS in an Irish Population (SIALS) and Sequencing and Analysis of an Irish Human Genome

  Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by loss of motor neurons. Epidemiological studies indicate that 2-5% of cases are familial, usually with an autosomal dominant pattern of inheritance. For a portion of these, causative genes have been identified. The remaining 95% of ALS cases are described as sporadic, and believed to result from a combination of genetic and environmental factors. This study utilized samples from Irish patients with sporadic ALS and Irish control individuals. The aim of the study was to identify susceptibility alleles for ALS in the Irish population. Genome-wide, single-nucleotide polymorphism (SNP) genotyping was undertaken using Illumina 550K version 3 chips. Genotyping data are available on 221 SALS patients and 211 controls. Future work will aim to examine ALS genetic risk at individual sequence level. As an initial step, as of September 2010 we have made available the human genome sequence from a single anonymous male control individual from the SIALS collection. Recent studies generating complete human sequences from Asian, African and European subgroupings have revealed population specific variation and illuminated disease susceptibility loci. The Irish population is of interest because of its location at the periphery of Europe and also the impact its emigrants have had on the genetics of populations in a number of other countries. We have identified sequence variants that may be specific to this population and have identified potentially novel disease associated variants. We describe a novel method for improving SNP calling accuracy at low genome coverage using haplotype information. Overall we demonstrate utility in generating whole genome sequences to test general principles and reveal specific instances of human biology. With increasing access to low cost sequencing we would predict that similar studies will emerge.

  Study phs000127

• Dataset for breast_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 12 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008867

• NIH Roadmap Epigenomics Program - Broad Institute

  For the NIH Roadmap Epigenomics project, we applied ChlP-Seq, HTBS and WGBS pipelines to generate comprehensive high-resolution maps of chromatin state and DNA methylation for 100 diverse cell types. Cell types were selected for their biological and medical importance, and for their potential to maximize the comprehensiveness of acquired epigenomic data. They include human ES cells, ES-derived cells, mesenchymal stem cells, reprogrammed stem cells and primary tissues. Comprehensive characterization of epigenetic marks ("the epigenome") is a critical step towards a global understanding of the human genome in health and disease. In this study we provide unprecedented views of the human epigenetic landscape and its variation across cell states, which offer fundamental insight into the functions and interrelationships of epigenetic marks, and provide a framework for future studies of normal and diseased epigenomes. The Roadmap Epigenomics Broad cohort is utilized in the following dbGaP sub-study. To view molecular data and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000700 the Roadmap Epigenomics Broad cohort. phs000610 RM_Epigenomics_Broad_Alz

  Study phs000700

• Dataset for RNA sequencing glioblastoma data

  This dataset contains RNA sequencing data of 36 glioblastoma samples. Sequencing was performed on Illumina NovaSeq 6000 using TruSeq Stranded RNA Kit. The sequencing was always paired.

  Dataset EGAD50000000688

• Paired-end Whole Exome-seq analysis of the Hypermutation and Malignant Progression in Low-grade Glioma Patients

  113 DNA samples were derived from the tumors of the low grade glioma patients and sequenced using Illumina WES (exome seq) paired-end technology. Dataset contains 113 BAM files aligned to hg19 using BWA v.0.5.9. After mapping duplicated reads were removed, reads were re-aligned around InDels and read base quality score was re-calibrated.

  Dataset EGAD00001005386

• scRNA-seq raw data

  This dataset contains scRNA-seq fastq files (trimmed for quality and adapters using Trim Galore) for 3739 intestinal plasma cells of known or unknown antigen specificities from in total 12 individuals (4 untreated coeliac disease patients, 3 treated coeliac disease patients, 5 controls). The data was generated using the Smart-seq2 protocol and sequenced on the Illumina NextSeq500 platform with 75 bp paired-end reads.

  Dataset EGAD00001006436

• Human dorsal root ganglia after plexus injury - RNA-fragment sequencing from histological slices dataset

  Transcriptome profiling of Human dorsal root ganglia after plexus injury based on low Input Total RNA-seq from FFPE material

  Dataset EGAD50000000959

• Transcriptome Analysis of Treg and Tfh cells

  Treg and Tfh cells (8 Samples)from the same donors was subject to RNA-seq (TruSeq Stranded Total RNA) processing. Single end fastq-files are supplied.

  Dataset EGAD00001007662

• RNA-seq dataset of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Dataset EGAD00001015771

• Evolutionary Analysis of Chronic Lymphocytic Leukemia Cells During Relapse After Allogeneic Hematopoietic Stem Cell Transplant

  We investigated the molecular dynamics driving relapse of chronic lymphocytic leukemia (CLL) following allogeneic hematopoietic stem cell transplant (allo-HSCT) through an integrated analysis of whole exome, bulk transcriptome, bulk methylome and single cell transcriptional data from paired leukemic samples representing 19 patients. We found that their clinical kinetics corresponded to distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are distinct from those imposed by chemotherapy.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out ribosome profiling (Ribo-seq) and RNA-sequencing on CLL samples and isolated primary B cells from healthy donors. We discovered novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001998

• Whole Genome, Exome, Transcriptome and Validation Sequencing of an Acute Lymphoblastic Leukemia

  We used massively parallel sequencing technology to profile the genomic DNA and RNA of tumor cells (leukemic bone marrow) and normal cells (skin biopsy) obtained from a single patient with Acute Lymphoblastic Leukemia (ALL), referred to throughout this study as 'ALL1'. Included in this study are samples obtained from a primary tumor, first relapse, second relapse and several intermediate timepoints. We identified somatic mutations present in each tumor by analysis of whole genome (WGS) and exome sequence data. Single nucleotide variants (SNVs) and small insertions and deletions were identified in both the exome and WGS data. Large copy number variations (CNVs) and structural variants (SVs) were identified in the WGS data. A custom capture reagent was designed to target most variants and used to generate deep validation sequence data. The expression status of all somatic variants was assessed by RNA-seq. The RNA-seq data was also used for gene expression analysis and gene fusion detection.

  Study phs001066

• ERa ChIP-seq in breast healthy, primary cancer and metastatic tissues

  ChIP-seq has been perfomed on fresh-frozen tissue derived from healthy breast (HB), primary breast cancer (PB), BCa-derived liver metastasis (LM). Immunoprecipitation has been performed for ERa (sc-542, SantaCruz). Raw paired-end fastq.gz files are provided for both immunoprecipitated DNA and input samples.

  Dataset EGAD50000000642

• CITE-seq for peripheral blood samples of 5 breast cancer patients

  We have 5 breast cancer patients who received VEN therapy. We collected their peripheral blood samples before and after long-term Venetoclax treatment. We apply CITE-seq protocol to these samples. This collection contains the all CITE-seq data for patients.

  Dataset EGAD00001008751

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Study EGAS50000000156

• 'Targeted High Throughput Sequencing in Clinical Cancer Settings: Formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity'

  "Background: Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings. Methods: Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.Results: We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance. Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations, but is of minor importance for the detection of somatic variations.Conclusions: The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies taken, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - on a long-range - result in a more reliable prediction of individual cancer therapies."

  Study EGAS00001000136

• RNA-seq analysis of transcriptome variation with human ESC subclones

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny 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 EGAD00001004266

• Molecular profiling of longitudinally observed small colorectal polyps: a cohort study

  Knowledge of the natural history of colorectal adenomas is limited because these lesions are removed upon detection. The few studies in which small adenomas have been left in situ for a limited period of time have shown that most lesions remain stable or even completely vanish. Lesions that have grown in size more often turn out to be advanced adenomas when resected. Specific DNA copy number changes (cancer associated events or CAEs) are associated with progression of adenomas to cancer. The aim of the study was to evaluate whether growth of small colorectal polyps left in situ is associated with specific molecular features.

  Study EGAS00001003284

• ATAC-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015509

• scRNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015510

• ICARUS-LUNG01 dataset

  A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

  Dataset EGAD50000001014

• Genomic Answers for Kids (GA4K)

  Identification of complex genetic variants including defects in gene regulatory circuits and uncharacterized genes present challenges for rare disease diagnosis. In Genomic Answers for Kids program we apply the joint interpretation of patient genome sequence with genomic endophenotypes to expand the clinically actionable genome among pediatric cases of suspected genetic disease. Our objective is to examine the role of novel and under-interpreted sequence variation by combining complete DNA sequences, personal epigenetic variations and massively parallel functional screens. To achieve this we perform augmented whole genome sequence (WGS) interpretation including reanalysis of clinical exomes as well as generating WGS for patients with negative exome results all be subject to family-based semi-automated recall pipeline to discover missed diagnostic variation. We use linked-read and long-read sequencing technologies to focus on putative structural variants missed in short-read genome and exome analysis by the optimized integration of linked and long read technologies that also improve identification of transmission patterns of all variants, as well as resolving genomic regions resistant to standard alignment. We also include tissue DNA sequencing to investigate somatic mosaicism. To further assist with WGS interpretation for uncommon variation we capture snapshots of patient transcriptomes and epigenomes in individual cells using single-cell RNA (scRNA) and sc open chromatin (scATAC) as well as bulk whole genome bisulphite genome sequencing for methylome interpretation. Alternative splicing is functionally assessed in available patient tissues using RNA-seq, including full length cDNA sequences by IsoSeq (PacBio) methodology. Our overarching goal is an increase rate of diagnostic genomic findings up to two-fold among rare disease, resulting in the majority (>50%) of patient cases resolved by the integrated system developed in our program.

  Study phs002206

• The Epigenomic Atlas of Early Human Craniofacial Development

  Parallel profiling of six distinct histone modifications via ChIP-Seq in craniofacial tissue samples from individual human embryos was performed. Epigenomic marks imputed with ChromImpute and a 25-state chromatin state model of uniformly processed epigenomic data was produced through ChromHMM. Samples were obtained from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) tissue bank. HDBR provided karyotypically and developmentally normal pharyngeal arch or craniofacial tissue from embryos between 4.5 and 10 post-conception weeks. This repository contains raw data (fastq) files from ChIP-seq and RNA-seq experiments associated with this project. Processed ChIP-seq data and imputed data for additional histone marks are available at GEO (Series GSE97752).

  Study phs002008

• ICGC prostate cancer RNA sequencing

  ICGC prostate cancer RNA sequencing

  Dataset EGAD00001000305

• Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer

  We generated a collection of patient-derived pancreatic normal and cancer organoids. We performed whole genome sequencing, targeted exome sequencing, and RNA sequencing on organoids as well as matched tumor and normal tissue if available. This dataset is a valuable resource for pancreas cancer researchers, and those looking to compare primary tissue to organoid culture. In our linked publication, we show that pancreatic cancer organoids recapitulate the mutational spectrum of pancreatic cancer. Furthermore, RNA sequencing of organoids demonstrates the presence of both transcriptional subtypes of pancreas cancer.

  Study phs001611

• Chordoma_Targeted_Sequencing_Study

  This Study uses a focused bespoke bait pull down library method to target findings of Chordoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Study EGAS00001000280

• Osteosarcoma_Targeted_Sequencing_Study

  This Study uses a focused bespoke bait pull down library method to target findings of Osteosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Study EGAS00001000278

• Meningioma_Targeted_Sequencing_Study

  This Study uses a focused bespoke bait pull down library method to target findings of Meningioma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Study EGAS00001000282

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models enables specific monitoring of tumour-derived extracellular RNA

  Total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v2) data of extracellular RNA (exRNA) from liquid biopsies of a BRC0004PR PDX and SK-N-BE(2C) CDX mouse model, and total RNA sequencing profiles of the matching PDX tumors.

  Dataset EGAD00001008318

• RNA Sequencing datasets - Project "Multi-omics analysis of Parkinson’s disease midbrains"

  The dataset contains FASTQ files referring to the study "Multi-omics analysis of Parkinson’s disease midbrains". For this project, RNA was isolated from human postmortem midbrain tissue (PD and Control samples). Libraries were prepared with the TruSeq Small RNA library prep (Small RNA Seq) and the TruSeq Stranded Total RNA Kit (for transcriptomics), both from Illumina. Sequencing for both experimental setups was conducted in the Illumina HiSeq4000.

  Dataset EGAD00001006883

• Single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with achalasia

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peripheral blood mononuclear cells (PBMC) from patients with achalasia. Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000250

• Circulating immune cell landscape in colorectal cancer patients

  To understand the circulating immune cells in colorectal cancer patients, we performed single-cell RNA sequencing for 14 PBMC samples from 14 colorectal cancer patients.

  Study EGAS50000000590

• Bulk RNA sequencing data of peripheral blood mononuclear cells obtained from 7 ATL patients and 9 HTLV-1-infected asymptomatic carriers.

  Bulk RNA sequencing (RNA-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 7 ATL patients (9 samples) and 9 HTLV-1-infected asymptomatic carriers.

  Dataset EGAD00001007018

• Single nucleus and bulk transcriptomics in prefrontal cortex of individuals with alpha synucleinopathies

  We explore cell-specific changes in gene expression across different α-synucleinopathies. We perform single nucleus RNA sequencing using 10X Genomics, and bulk RNA sequencing from the prefrontal cortex of individuals with alpha synucleinopathies - Parkinson's Disese (PD), monogenic LRRK2 PD, and multiple system atrophy (MSA), together with neurologically healthy controls.

  Study EGAS50000000301

• 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

• Sequence data of 28 Samples (19 chronic lymphocytic leukemia, 9 control)

  Sequence data of 28 Samples (19 chronic lymphocytic leukemia, 9 control) Including RNA-Seq and ChIP-Seq of following histone modifications: H3, H3K4me1, H3K4me3, H3K9ac, H3K9me3, H3K27ac, H3K27me3, H3K36me3 Project see: http://www.cancerepisys.org/

  Dataset EGAD00001003421

• bulkRNA seq from fibroblasts stimmulated with bead or CD8 T cell supernatant

  CD8 T cells (5 Samples treated, 5 samples control) form the same donors (5 donors, paired design) was subject to RNA-seq (Illumina stranded mRNA) processing. Single end fastq-files are supplied.

  Dataset EGAD00001010004

• Gut microbiome profiles according to sex, body mass index and dietary fiber intake

  Findings from recent studies suggest that the community of microbes residing in the human body is important in disease etiology; however, it remains unclear whether personal factors modulate human microbial composition. Studies based on animal models indicate that differences in composition might be attributed to sex-mediated effects. We analyzed the relationship of sex, adiposity, and dietary fiber intake with gut microbial composition using fecal samples from human subjects. We explored the associations of these factors with metrics of community composition and specific taxon abundances. We found that men and women had significantly different microbial community composition and that women had reduced abundance of a major phylum. Adiposity was associated with gut microbiome composition and specifically in women but not in men. Fiber from fruits and vegetables and fiber from beans were each associated with increased abundance of specific bacterial taxa. These findings provide initial indications that sex, adiposity, and dietary fiber might play important roles in influencing the human gut microbiome. Better understanding of these factors may have significant implications for gastrointestinal health and disease prevention.

  Study phs000884

• Assessment_of_epigenetic_variation_in_human_iPS_cells_Medip

  n order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The methylation status of these iPS cells will be compared.Protocol:Primary cell cultures were generated and reprogrammed to iPS cells. DNA was extracted and immunoprecipitated using anti-methyl cytosine and anti-hydroxymethyl cytosine antibodies.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/

  Study EGAS00001000741

• 10x genomics single cell RNA-seq and ATAC-seq from 10 pre-menopausal patients fimbriae and ampullary part of the fallopian tube

  The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.

  Study EGAS50000000628

• Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing

  Adapted from manuscript in review: Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC) but there have been few whole genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. These include highly recurrent tandem duplications involving an upstream enhancer of AR. A subset of cases also displayed a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC nominate new alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the noncoding mCRPC genome remain to be discovered.

  Study phs001577

• GoDARTS T2D-GENES Exome Sequencing Study is a subset of the ~52,000 Type 2 diabetes exome sequencing project.

  The GoDARTS T2D-GENES Exome sequencing study is a subset of a larger Type 2 Diabetes Exome Sequencing project. This effort is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date and includes samples from: T2D-GENES, GoT2D, ESP, SIGMA T2D, LuCAMP, and ProDIGY. This data generated from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for T2D through multiethnic sequencing studies. Sequencing for the GoDARTS study was performed at the Broad Institute using Illumina Rapid Capture on Illumina HiSeq machines.

  Study EGAS00001002937

• RNA-seq bulk

  This dataset gather all RNA-sequencing data in MM.1S cell line in control and Dex condition; both in 3 biological replicates

  Dataset EGAD00001011137

• RNA sequencing of osteoarthritis patients in subchondral bone

  This dataset contains RNA-seq (Illumina Hiseq 4000) from macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N=48).

  Dataset EGAD00001006197

• RNA sequencing of PTCL-NOS

  This dataset contains raw .fastq files of a paired-end RNA-seq experiment on 15 PTCL-NOS samples. Samples were prepared with Truseq stranded mRNA library kit.

  Dataset EGAD00001006925

• Women's Health Initiative Clinical Trial and Observational Study - Imaging

  Objectives: The clinical trial assessed the safety and efficacy of three interventions. Specifically, it evaluated (1) the major health benefits and risks of estrogen plus progestin and estrogen alone, (2) the effects of a low-fat eating pattern on risk of colorectal cancer, and (3) the efficacy of calcium with vitamin D supplementation for preventing hip and other fractures. The objective of the memory study was to determine whether estrogen plus progestin therapy protects global cognitive function, and evaluate the therapy's effect on the incidence of dementia and mild cognitive impairment.The observational study is examining the relationship between lifestyle, socioeconomic, health, and other risk factors with cardiovascular, breast cancer, colorectal cancer and osteoporotic fracture outcomes. Secondary objectives include providing more reliable estimates of the extent to which known risk factors predict disease, more precise estimates of new occurrences of disease, and to provide a future resource for the identification of new or novel risk factors especially factors found in blood. Background: The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing the major causes of death, disability, and frailty in postmenopausal women, specifically heart disease, cancer, and osteoporotic fractures. The WHI is primarily composed of an observational study (OS), as well a clinical trial (CT) with three components: Hormone Replacement Therapy (HT), Dietary Modification, (DM) and Calcium/Vitamin D supplementation (CaD).Prior to the WHI, observational studies suggested that postmenopausal hormone therapy was associated with a decreased risk of coronary heart disease (CHD). Potential cardioprotection was based on generally supportive data on lipid levels in intermediate outcome clinical trials, trials in nonhuman primates, and a large body of observational studies suggesting a 40% to 50% reduction in risk among users of either estrogen alone or, less frequently, combined estrogen and progestin. Observational studies primarily examining unopposed estrogen preparations have suggested a 30% to 50% reduction in coronary events, and an 8% to 30% increase in breast cancer with extended use. Other research findings indicated that hormone therapy was also associated with a decreased risk of osteoporosis and increased bone density. The WHI HT trials were designed to test the effects of postmenopausal hormone therapy on risk for coronary heart disease and assess overall risks and benefits in predominantly healthy women. The Women's Health Initiative Memory Program (WHIMS) consists of a suite of studies which include cohorts of women who participated in the WHI HT trials. Postmenopausal women have a greater risk than men of developing Alzheimer's disease, but studies of the effects of estrogen therapy on Alzheimer's disease have been inconsistent. Additionally, observational studies have suggested that postmenopausal hormone treatment may improve cognitive function, but data from randomized clinical trials have been sparse and inconclusive. International comparisons and migration studies have suggested that countries with 50% lower fat intake than the US population had approximately one third the risk of colorectal cancer. Additionally, fairly consistent evidence existed for an effect of dietary fat, vegetables and fruits, and grains on colorectal cancer risk from within-country observational studies, although the protective effect of lower fat intake was no longer clear after adjusting for energy intake. The WHI DM trial was the first randomized trial to directly address the health effects of a low-fat eating pattern in predominantly healthy postmenopausal women from diverse racial/ethnic, geographic, and socioeconomic backgrounds. Osteoporosis is a major cause of injury, loss of independence, and death, and contributes to hip fractures. Observational evidence and data from previous randomized clinical trials suggest that calcium and/or vitamin D supplements may slow bone loss and reduce the risk of falls in postmenopausal and elderly women. However, evidence from trials, observational studies, and meta-analyses of calcium and vitamin D supplementation with respect to hip and other fractures was limited at the time the WHI was initiated. In two prior randomized trials, calcium plus vitamin D supplements did not reduce the risk of nonvertebral fractures among older women. When the WHI CaD trial was designed, guidelines recommended daily intakes of 800 to 1200 mg of calcium with 400 IU of vitamin D for the prevention of osteoporosis, which was not met by many American women. Therefore, the WHI CaD trial was designed to test the primary hypothesis that postmenopausal women randomly assigned to calcium plus vitamin D supplementation would have a lower risk of hip fracture and, secondarily, of all fractures than women assigned to placebo. Subjects: Postmenopausal women ages 50 to 79 were eligible to participate. A woman was considered postmenopausal if she had experienced no vaginal bleeding for 6 months (12 months for women under 55 years of age), had had a hysterectomy, or had ever used postmenopausal hormones. Recruitment was carried out in 40 US clinical centers in 1993-1998. The clinical trial components had additional specific inclusion or exclusion criteria.A total of 68,132 women were randomized into at least one component of the clinical trial. 27,347 women were enrolled in the hormone therapy component with 16,608 in the estrogen plus progestin trial and 10,739 in the unopposed estrogen trial, 48,835 women were enrolled in the diet modification component, and 36,282 women were enrolled in the calcium/vitamin D component. 7,479 women 65 years of age and older at baseline and that participated in the HT trial component were enrolled in the ancillary memory study. Women who were either ineligible or unwilling to participate in the clinical trial component were enrolled in the observational study. For example, many potential participants to the clinical trial component of the study were already undertaking a low fat diet or were using hormone replacement therapy. The effect of the selection process was that women enrolled in the observational study tended to have healthier lifestyles compared to those enrolled in the clinical trial. In total, 93,676 subjects were enrolled in WHI OS, with over 16% being members of a racial/ethnic minority group. The first WHI Extension Study enrolled 115,407 consenting participants from all components of the original WHI study for an additional five years of follow-up, from 2005 to 2010. In 2010, 93,567 women consented to continued follow-up. Design: The clinical trial component of the WHI included three randomized comparisons: hormone therapy, dietary modification, and calcium/vitamin D supplementation. Women could have been randomized into one, two or all three trials.The hormone therapy trial enrolled women to one of two double-blinded trials: estrogen (0.625 mg of conjugated equine estrogens daily) plus progestin (2.5 mg of medroxyprogesterone acetate daily) or estrogen alone. Women with a prior hysterectomy were eligible for the trial of unopposed estrogen. Women with an intact uterus at screening were initially also eligible for unopposed estrogen, but were reassigned to the trial of combined postmenopausal hormones beginning in 1995. Both trials randomized participants 1:1 to either hormone therapy or placebo. A 3-month washout period was required before baseline evaluation of women using postmenopausal hormones at initial screening. Study participants were contacted by telephone 6 weeks after randomization to assess symptoms and reinforce adherence. Follow-up contacts by telephone or clinic visit occurred every 6 months, with clinic visits required annually. The estrogen plus progestin trial was halted in July 2002 after a mean 5.2 years of follow-up because health risks, including increased risk of breast cancer and cardiovascular disease, exceeded benefits. The estrogen alone trial was stopped early in March 2004, because an increased risk of stroke was found with no benefit for coronary heart disease. The primary outcome was coronary heart disease (CHD) (nonfatal myocardial infarction and CHD death), with invasive breast cancer as the primary adverse outcome. The dietary modification trial evaluated the effect of a low-fat, high fruit, vegetable, and grain diet on preventing cardiovascular disease and cancer. Participants were randomly assigned to an intervention or a comparison group in the ratio of 2:3 for cost-efficiency. The intervention was an intensive behavioral modification program, using 18 group sessions in the first year and quarterly sessions thereafter, led by specially trained and certified nutritionists. The program was designed to promote dietary change with the goals of reducing total fat to 20% of energy intake, increasing vegetables and fruits to at least 5 servings daily and grains to at least 6 servings daily. The intervention did not include total energy reduction or weight loss goals. Comparison group participants received a copy of the US Department of Health and Human Services' Dietary Guidelines for Americans and other health-related materials but were not asked to make dietary changes. Dietary intake was monitored using the WHI food frequency questionnaire at 1 year and in a rotating one-third subsample every year thereafter. Women completed a medical update questionnaire every 6 months, and medical records were sought for all women reporting colorectal cancer. The primary outcome was invasive colorectal cancer incidence. Participants in the calcium/vitamin D trial were randomized 1:1 to either supplements or placebo. Active tablets contained 500 mg of elemental calcium (as calcium carbonate) and 200 IU of vitamin D3, to be taken twice daily with meals. The presence and severity of symptoms, safety concerns, and outcomes were ascertained at annual clinic visits and telephone or clinic visits at intervening six-month intervals. Risk factors for fracture were assessed by questionnaire, interview, and clinical examination. The primary outcome was incidence of hip fracture. Participants in the observational study attended a baseline examination and were re-examined three years later. Participants completed annual updates of exposures and clinical outcomes by mail. Final data were collected by mail during the close-out period in April 2004 to March 2005. The major clinical outcomes of interest were coronary heart disease, stroke, breast cancer, colorectal cancer, endometrial cancer, ovarian cancer, osteoporotic fractures, diabetes, and total mortality. Most outcomes were initially ascertained by self-report on an annual questionnaire and documented by hospital and related records. Charts with potential cardiovascular, cancer, and fracture outcomes were sent to the local physician adjudicator for evaluation and classification. Staff at the Clinical Coordinating Center coded and adjudicated all cancers of major interest in the study using standardized SEER guidelines. In 2005, WHI participants were invited to join the Extension Study for an additional five years of follow-up in order to collect long-term outcomes. Participants completed annual data collection forms primarily by mail, similar to the OS follow-up. Women reporting study outcomes were contacted by WHI field center staff to obtain additional details and medical records, which were evaluated by physician adjudicators. In 2010, the woman remaining were invited to join the next Extension Study. In the second extension, women were divided into two groups, one of which would have outcomes documented with medical records (the Medical Records Cohort, MRC), and the other would just be followed by self-report (the Self-Report Cohort, SRC). The MRC consists of women who were in the hormone therapy trials, and all African-American and Hispanic women. In 2012-2013, a subset of the MRC was identified for a potential in-home visit to collect blood and several objective measures of physical functioning. Conclusions: Overall health risks exceeded benefits from use of combined estrogen plus progestin after an average 5.2 year follow-up among healthy postmenopausal US women (Rossouw et al., 2002, PMID:12117397). Among postmenopausal women aged 65 years or older, estrogen plus progestin did not improve cognitive function when compared with placebo (Rapp et al., 2003, PMID: 12771113), increased the risk for probable dementia, and did not prevent mild cognitive impairment (Shumaker, et al., 2003, PMID: 12771112). The use of conjugated equine estrogen increased the risk of stroke, decreased the risk of hip fracture, and did not affect CHD incidence in postmenopausal women with prior hysterectomy after an average of 6.8 years of follow-up (Anderson et al., 2004, PMID: 15082697). Over approximately 8 years of follow-up, a low-fat dietary pattern did not reduce the risk of colorectal cancer (Beresford, et al., PMID: 16467233). Calcium with vitamin D supplementation resulted in a small but significant improvement in hip bone density; however, no significant difference was observed in hip fractures (Jackson, et al., 2006, PMID: 16481635). A recent review summarizes the conclusions from the WHI clinical trials with a focus on clinical practice (Manson, et al., 2024, PMID: 38691368).Description of ECG Imaging Data: Electric cardiograms (ECGs) were given to all clinical trial participants at baseline and in years 3, 6, and 9 of the original WHI study.EKG data consist of 12 lead 10 seconds ECGS sampled at 500Hz via GE ECG machines and process via GE MUSE system. The ECG waveform were directly exported from GE MUSE using MUSE export function in XML format, which include EKG waveform data as well as other ECG characteristics. Waveform data is in base64 encoded format, when it is decoded, it is a binary data that can be used to draw waveform graph. Many programming languages and data tools have built in functions to decode base64 strings. All the other necessary information is included in the LeadData section, total byte size, total sample size etc. (usually 1 sample is 2 bytes). See example below: encoded-data (base64 encoded string) JwAoAC0AKAAiACIAJAAkACQAIwAiACIAHgAcABwAGwAZABgAGAAYABcAEwAQABAAEAAL^/AAsADAAM... decoded-binary-data (1 sample is 2 bytes) 270028002D002800220022002400240024002300220022001E001C001C001B00 1900180018001800170013001000100010000B000B000C000C000D000D000D00 0A000A000A0009000600040004000700070005000500020... These binary values are integers (Y axis data of the graph), hence it is a straightforward process to draw the waveform graph. Acquisition dates have been redacted from this ECG data to comply with WHI policy. All acquisition dates within files and in file names have been set to January 1, 1900 (19000101) to comply with this policy.

  Study phs003824

• RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

  Study EGAS00001005368

• Aggregated count table

  RNA-seq count matrix for 296 bulk pre-treatment tumors from IMblaze370

  Dataset EGAD00001008552

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588

• Single-cell RNA-seq of rheumatoid arthritis synovial tissue using low-cost microfluidic instrumentation

  Droplet-based single-cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $575. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single-cell transcriptome profiling of disaggregated synovial tissue from 5 rheumatoid arthritis patients. We sequenced 20,387 single cells from synovectomies, revealing 13 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling. Reprinted from [Stephenson et al., Nature Communications, 2018], with permission from the Nature Publishing Group.

  Study phs001529

• Mutational_burden_in_oesophagus__nanoseq_

  We wish to accurately assess mutational burden and signature from patients of different ages using clonal oesophageal epithelium and duplex-seq. We will also attempt to look for differences between smokers and non-smokers and individuals with different levels of alcohol consumption.

  Study EGAS00001007695

• Developing therapeutics for ovarian cancer using ovarian cancer organoids

  To identify effective drugs for clear cell ovarian cancer (CCC) and high-grade serous ovarian cancer (HGSC) through high-throughput drug screening using ovarian cancer organoids and to identify novel therapeutic targets based on the biological characteristics of CCC and HGSC through omics analysis.

  Study JGAS000764

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  We performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants associated with the disorder.

  Study EGAS50000000411

• RNA sequencing of 31 pancreatic cancer organiods

  RNA sequencing of 31 pancreatic cancer organiods

  Dataset EGAD00001005217

• Single-Cell Sequencing of Genomic DNA, RNA, and ADT in CRISPR-Edited Cells

  CRAFTseq data containing multi-modal single-cell genomic DNA amplicon, cDNA and surface-protein from various primary cell types and cell lines, including human CD4 T cells, Jurkat cells, HH cells, Daudi cells and HEK293T cells. Cells were edited with CRISPR HDR or base editing. Also contains bulk RNA-seq data for edited human primary CD4 T cells and Daudi cells.

  Study phs004042

• Genetic and Epigenetic Screens in Primary Human T Cells Link Candidate Causal Autoimmune Variants to T Cell Networks

  We aimed to define the target genes and pathways in which autoimmune disease-associated genetic variants operate. We performed single cell-CRISPR-interference screens in primary human T cells and bulk RNA-seq on T cells containing CRISPRi and single gRNAs to assess how T cell regulatory regions containing autoimmune-associated genetic variants affect nearby gene expression and cellular programs.

  Study phs004072

• RNA-seq and Hi-C data of a chromothripsis patient's iPS cells

  This dataset contains RNA-seq and Hi-C data files of induced pluripotent stem (iPS) cells and iPS cell-derived neural progenitors (NPCs) derived from a germline chromothripsis patient and both parents. iPS cells of the patient (cell lines 14 and 15), the father (lines 23 (with two replicates) and 32) and mother (line 30) were differentiated to NPCs and RNA was collected on day 0, day 7 and day 10 of differentiation. In addition, Hi-C data for two iPS cell-derived NPC lines from the patient (14 and 15) and two lines from the father (23 and 32) was generated.

  Dataset EGAD00001002242

• Genome_Diversity_in_Africa_Project___GemCode_libraries

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from Africa have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within Africa would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) will extend and expand the African Genome Variation (AGV) project, an international collaboration aimed to produce a comprehensive catalogue of human genetic variation in Sub-Saharan Africa (SSA). Using a sequencing-based approach, GDA project aims to capture human genetic variation in Africa, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in Africa, as well as providing a global resource to help design, implement and interpret genomic studies in African populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out whole genome sequencing at high depth (30x) of up to 1000 individuals across Africa (25 individuals from each ethnolinguistic group). We have already completed sequencing from 5 ethno-linguistic groups and we are now adding others.Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from Africa accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across Africa; 3) develop a cost-efficient, next-generation genotype array for diverse populations across Africa; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics.

  Study EGAS00001001589

• UROMOL 2020 - RNA-seq data

  The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we performed a large integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters.

  Study EGAS00001004693

• WGBS data (CancerLocator study) of cell-free DNA derived from human blood

  The blood samples of eight lung cancer patients and one benign lung tumor patient are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001003168

• A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  iPSC-derived corneal endothelial cell substitutes recover pathological corneal edema. No adverse reactions are observed after one year follow-up. Gene mutations may appear despite whole genome sequencing of the master cell bank. This study contains the RNA-seq data.

  Study EGAS50000000673

• RNA-seq data for proximal and distal human LHBT UZH (CH)

  This dataset contains bulk RNA-seq data from 15 patients who underwent rotator cuff repair surgery, yielding paired proximal and distal samples of the long head of the biceps tendon (30 samples total). The submission includes 90 files, consisting of R1 and R2 FASTQ files for each sample as well asprocessed .TXT files containing gene-level counts generated after genome alignment. Raw sequencing reads were generated on an Illumina platform, aligned to the human reference genome GRCh38.p13, and quantified at the gene level.

  Dataset EGAD50000002095

• Microinjection_of_hIPSC_derived_intestinal_organoids_with_Salmonella_Typhimurium

  To generate an RNA-Seq dataset for organoids apically stimulated with Salmonella Typhimurium.These data are 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/

  Study EGAS00001001253

• BLUEPRINT release August 2016, RNA-Seq for memory B cell, on genome GRCh38

  RNA-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002347

• BLUEPRINT release January 2015, RNA-Seq for endothelial cell of umbilical vein (resting)

  RNA-Seq data for 1 endothelial cell of umbilical vein (resting) sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001142

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MS-275 (20h), on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MS-275 (20h) sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002500

• BLUEPRINT release August 2016, RNA-Seq for naive B cell, on genome GRCh38

  RNA-Seq data for 6 naive B cell sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002315

• BLUEPRINT release August 2016, RNA-Seq for CD38-negative naive B cell, on genome GRCh38

  RNA-Seq data for 3 CD38-negative naive B cell sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002438

• BLUEPRINT release August 2015, RNA-Seq for segmented neutrophil of bone marrow, on genome GRCh38

  RNA-Seq data for 3 segmented neutrophil of bone marrow sample(s). 3 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001579

• BLUEPRINT release August 2016, RNA-Seq for class switched memory B cell, on genome GRCh38

  RNA-Seq data for 3 class switched memory B cell sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002476

• BLUEPRINT release August 2014, RNA-Seq for CD14-positive, CD16-negative classical monocyte

  RNA-Seq data for 7 CD14-positive, CD16-negative classical monocyte sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000928

• BLUEPRINT release January 2015, RNA-Seq for endothelial cell of umbilical vein (proliferating)

  RNA-Seq data for 1 endothelial cell of umbilical vein (proliferating) sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001166

• BLUEPRINT release August 2016, RNA-Seq for unswitched memory B cell, on genome GRCh38

  RNA-Seq data for 1 unswitched memory B cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002414

• BLUEPRINT release August 2016, RNA-Seq for adult endothelial progenitor cell, on genome GRCh38

  RNA-Seq data for 2 adult endothelial progenitor cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002334

• BLUEPRINT release August 2016, RNA-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002295

• BLUEPRINT release August 2016, RNA-Seq for germinal center B cell, on genome GRCh38

  RNA-Seq data for 3 germinal center B cell sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002452

• BLUEPRINT release August 2016, RNA-Seq for inflammatory macrophage, on genome GRCh38

  RNA-Seq data for 6 inflammatory macrophage sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002417

• BLUEPRINT release January 2015, RNA-Seq for CD4-positive, alpha-beta T cell

  RNA-Seq data for 10 CD4-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001173

• BLUEPRINT release August 2015, RNA-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001489

• BLUEPRINT release August 2016, RNA-Seq for conventional dendritic cell, on genome GRCh38

  RNA-Seq data for 2 conventional dendritic cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002345

• BLUEPRINT release August 2016, RNA-Seq for immature conventional dendritic cell - GM-CSF_IL4_T=6_days, on genome GRCh38

  RNA-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002526

• BLUEPRINT release August 2016, RNA-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002289

• BLUEPRINT release August 2016, RNA-Seq for regulatory T cell, on genome GRCh38

  RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002351

• BLUEPRINT release August 2016, RNA-Seq for late basophilic and polychromatophilic erythroblast, on genome GRCh38

  RNA-Seq data for 1 late basophilic and polychromatophilic erythroblast sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002402

• BLUEPRINT release January 2015, RNA-Seq for cytotoxic CD56-dim natural killer cell

  RNA-Seq data for 3 cytotoxic CD56-dim natural killer cell sample(s). 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001159

• BLUEPRINT release August 2016, RNA-Seq for blast forming unit erythroid, on genome GRCh38

  RNA-Seq data for 1 blast forming unit erythroid sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002365

• BLUEPRINT release August 2016, RNA-Seq for plasma cell, on genome GRCh38

  RNA-Seq data for 7 plasma cell sample(s). 7 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002323

• BLUEPRINT release January 2015, RNA-Seq for erythroblast

  RNA-Seq data for 7 erythroblast sample(s). 29 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001177

• BLUEPRINT release January 2015, RNA-Seq for central memory CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001175

• BLUEPRINT release January 2015, RNA-Seq for CD38-negative naive B cell

  RNA-Seq data for 2 CD38-negative naive B cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001145

• BLUEPRINT release August 2016, RNA-Seq for segmented neutrophil of bone marrow, on genome GRCh38

  RNA-Seq data for 3 segmented neutrophil of bone marrow sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002380

• BLUEPRINT release August 2014, RNA-Seq for erythroblast

  RNA-Seq data for 4 erythroblast sample(s). 22 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000911

• BLUEPRINT release August 2015, RNA-Seq for CD38-negative naive B cell, on genome GRCh38

  RNA-Seq data for 2 CD38-negative naive B cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001500

• BLUEPRINT release August 2015, RNA-Seq for regulatory T cell, on genome GRCh38

  RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001546

• BLUEPRINT release January 2015, RNA-Seq for CD8-positive, alpha-beta T cell

  RNA-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001137

• BLUEPRINT release August 2015, RNA-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001478

• BLUEPRINT release August 2016, RNA-Seq for mature neutrophil, on genome GRCh38

  RNA-Seq data for 14 mature neutrophil sample(s). 14 run(s), 14 experiment(s), 13 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002409

• BLUEPRINT release August 2016, RNA-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002299

• Whole transcriptome sequencing of Acute Myeloid Leukemias with an acquired inv(3)(q21q26) or t(3;3)(q21;q26) aberration

  In total 30 Acute Myeloid Leukemias with an acquired inv(3)(q21q26) or t(3;3)(q21;q26) have been characterized by whole transcriptome sequencing (RNA-Seq). The 3q-aberration leads to overexpression of the proto-oncogene EVI1, but the mechanism of overexpression has thus far been elusive. The RNA-Seq was integral in determining the precise enhancer inducing the overexpression and led to other key discoveries.

  Dataset EGAD00001000726

• BLUEPRINT release January 2015, RNA-Seq for effector memory CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001153

• BLUEPRINT release August 2016, RNA-Seq for alternatively activated macrophage, on genome GRCh38

  RNA-Seq data for 7 alternatively activated macrophage sample(s). 9 run(s), 7 experiment(s), 7 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002387

• BLUEPRINT release August 2015, RNA-Seq for mature neutrophil, on genome GRCh38

  RNA-Seq data for 14 mature neutrophil sample(s). 14 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001474