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• Molecular profiling of DLBCL patients treated in the PETAL trial

  Shallow whole genome sequencing and targeted sequencing of DLBCL patients treated in the PETAL trial

  Dataset EGAD00001008386

• RNA-seq of PDAC patient-derived xenograft tumors

  This dataset contains single cell RNA-seq data of stromal cells derived from two PDX models (N = 2 in total) and bulk RNA-seq data of two PDX models treated with gemcitabine and our novel antibody-drug conjugate, C6-EBET (N = 59 in total). Bulk RNA-seq experiments were performed with Agilent SureSelect Strand Specific RNA Library Prep Kit (Agilent). Single cell RNA-seq experiments were performed with Chromium Single Cell 3' Reagent Kits v2 Chemistry (10x Genomics).

  Dataset EGAD00001010130

• 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

• Targeted resequencing of Acute Myeloid Leukemia patients with an acquired inv(3)(q21q26) or t(3;3)(q21;q26).

  Targeted resequencing on the specific regions chr3:126036241-130672290 and chr3:157712147-175694147 in hg19 centered on the chromosomal regions 3q21 and 3q26 respectively. The focus lies on the detection of the exact breakpoints in Acute Myeloid Leukemia (AML) patients having acquired a inv(3)(q21q26) or t(3;3)(q21;q26). This dataset contains all information to detect all structural variants contained within these regions, including the 3q-aberrations inducing the overexpression of the proto-oncogene EVI1.

  Dataset EGAD00001000727

• RNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Fresh peripheral blood mononuclear cells of four human donors were cultured together with either lung adenocarcinoma A549 cancer cells or A549-expressing H1N1 Sialidase cancer cells. These treatments induced the differentiation of donor cells into immunosuppressive MDSC-like cells, which were further subjected to bulk RNA sequencing. RNA-seq TruSeq libraries were generated from polyA-enriched mRNA isolated from the samples, and sequenced in paired-end mode on 4 lanes of an Illumina NextSeq 500 flow-cell

  Dataset EGAD00001012437

• Sequencing probands and families with severe insulin resistance syndromes

  This is an ongoing project and continuation to all the sequencing we have been doing over the last few years. We have some additional families and probands with syndromes of insulin resistance not previously sequenced within uk10k or other core funded projects. We would like to complete the sequencing in all of the good quality families and probands we have, this would require another ~50 samples to be WES sequenced. This cohort has already proven to be a rich source of interesting findings with papers in Science and Nature genetics.

  Dataset EGAD00001000694

• Single cell RNA-seq from AD and PS patients

  We applied single cell immune profiling to gain a holistic view from immune cells infiltrating the skin to circulating immune cells, facilitating a better understanding of the two diseases in their entirety, and the identification of potential type-2 or type-3-disease-driving mechanisms.

  Study EGAS00001007055

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

  human induced pluripotent stem cells constitutely expressing the CRISPRi machinery were transduced with gRNAs targeting genomic regions of transposable elements (TEs), and differentiated to neural progenitor cells. The aim of the study was to annotate the function of these TEs in the context of early neurodevelopmental processes.

  Study EGAS00001008265

• EGAD00010000560

  SNP array of 7 HCCs and matched background liver in children with bile salt export pump deficiency

  Dataset EGAD00010000560

• Mutational landscape and clonal architecture in grade-II/III gliomas

  Dataset EGAD00001001213

• preQC Genotypes

  preQC genotype data from the Affymetrix AxiomTM HGCoV2 1 array in plink ped/map format

  Dataset EGAD00010002437

• Integration of metabolomics, genomics and immune phenotypes reveals the causal roles of metabolites in disease

  Study EGAS00001005348

• Multi-omics integration reveals only minor long-term molecular and functional sequelae in immune cells of individuals recovered from COVID-19

  Dac EGAC00001002267

• MiRNA_Validation

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002752

• MiRNA_TrainTest

  Rounded Log2 CPM well-expressed miRNA levels in plasma; determined using the HTG EdgeSeq miRNA Whole Transcriptome Assay

  Dataset EGAD00010002754

• A single cell view on host immune transcriptional response to in vivo BCG-induced trained immunity

  Study EGAS00001006990

• Genome-wide association study of esophageal squamous cell cancer identifies shared and distinct risk variants in African and Chinese populations

  Study EGAS00001007477

• Targeted Sequencing of GWAS Loci in Cleft Lip and Palate

  Nonsyndromic cleft lip and palate (NSCL/P) is a complex disorder caused by both genetic and environmental factors and has been the focus of an extensive effort to identify genetic risk factors. A number of candidate gene studies have been performed but have not been widely replicated. To date, four independent genome wide association studies have been performed as well as a meta-analysis. Together these studies have identified many loci associated with NSCL/P. The goal of this project is to use targeted sequencing to further characterize these regions and to progress from the association signals identified by GWAS to the identification of causative genes and/or variants. This study is part of the GWASeq project, a collaboration of five disease studies, which will sequence genomic regions from GWAS to characterize the genetic variation underlying these diseases and to compare study design and methods for the follow-up of GWAS studies by sequencing. The goal of this study is to sequence 1000+ NSCL/P case-parent trios from China and the Philippines and 400 trios of European ancestry. Targeted sequencing was performed on intervals ranging between 60kb to 1Mb surrounding 13 genes/loci previously associated with NSCL/P including: IRF6, MAFB, ARHGAP29, 8q24, PAX7, VAX1, NTN1, NOG, FOXE1, MSX1, BMP4, FGFR2, PTCH1.

  Study phs000625

• Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade

  Following the pivotal Phase III IMpower133 study, atezolizumab (anti–PD-L1), combined with carboplatin and etoposide (CE), was the first immune checkpoint inhibitor approved for first-line treatment of extensive-stage small cell lung cancer (ES-SCLC) and is now a standard of care. A clearer understanding of therapeutically relevant SCLC subsets is needed to improve outcomes and to identify rational combination strategies. Transcriptomic analyses and nonnegative matrix factorization were conducted on 271 pre-treatment patient tumor samples from IMpower133 and four subsets with general concordance to previously reported SCLC subtypes were identified. Deeper investigation into the immune heterogeneity relevant to clinical outcomes uncover two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes that demonstrated hallmarks of immune cell infiltration. The balance of tumor-associated macrophage (TAM) to T-effector signals distinguished these inflamed subsets. Tumors with low TAM but high T-effector signals had a NE phenotype and demonstrated longer overall survival with PD-L1 blockade and CE versus CE alone than did tumors with high TAM and high T-effector signal, which had a non-NE phenotype. The delineation of SCLC immune heterogeneity offers a clinically relevant approach to discriminate SCLC patients likely to benefit most from immunotherapeutic approaches and highlights the complex mechanisms underlying response and resistance to immune checkpoint blockade. 

  Study EGAS50000000138

• GeneScreen, a Population Based, Targeted Genomic Screening Study

  The GeneScreen research study was based at the University of North Carolina (UNC) at Chapel Hill. It brought together researchers from different disciplines, including genetics, clinical medicine, bioethics, sociology, anthropology, psychology, and public health, to study the best ways to offer targeted genetic screening to the general adult population. DNA samples were collected from people who joined GeneScreen to look at a targeted panel of 17 genes. It tested for genetic differences (called mutations) that can cause one of 11 rare, but preventable or treatable conditions, including certain types of cancer and heart disease. Each condition has specific medical advice people can follow with their doctors to prevent or treat a serious health problem. The GeneScreen study was approved by the UNC Institutional Review Board and by the Kaiser Permanente Center for Health Research Institutional Review Board. GeneScreen is funded by the National Human Genome Research Institute of the National Institutes of Health.

  Study phs001817

• HSC_colony_many_years_post_allogeneic_bone_marrow_transplant_TGS

  This study looks at human donors and recipients of allogeneic blood & marrow marrow transplantation. Each transplant "pair" (donor & recipient) underwent the transplant procedure 10 -30 years prior to sampling - the majority for an underlying diagnosis of leukemia. We will perform whole-genome sequencing on tens to hundreds of single HSPC (haematopoietic stem and progenitor cell)-derived colonies per individual. We will infer the phylogeny of these cells (those from both donor & recipient within a pair) by analysing the somatically acquired mutations within each cell. The structure of the phylogeny will allow estimates of hitherto unknown parameters such as the number of HSCs that engraft long-term, the dynamics of the engraftment process on the HSC level, and the additional mutation burden acquired through the arduous transplant procedure. This TGS part of the study is used for assessing the contribution of clones to mature blood subsets, and better timing mutations relative to transplantation.

  Study EGAS00001005298

• HSC_colony_many_years_post_allogeneic_bone_marrow_transplant___Bait_set_2

  This study looks at human donors and recipients of allogeneic blood & marrow marrow transplantation. Each transplant "pair" (donor & recipient) underwent the transplant procedure 10 -30 years prior to sampling - the majority for an underlying diagnosis of leukemia. We will perform whole-genome sequencing on tens to hundreds of single HSPC (haematopoietic stem and progenitor cell)-derived colonies per individual. We will infer the phylogeny of these cells (those from both donor & recipient within a pair) by analysing the somatically acquired mutations within each cell. The structure of the phylogeny will allow estimates of hitherto unknown parameters such as the number of HSCs that engraft long-term, the dynamics of the engraftment process on the HSC level, and the additional mutation burden acquired through the arduous transplant procedure. This TGS part of the study is used for assessing the contribution of clones to mature blood subsets, and better timing mutations relative to transplantation.

  Study EGAS00001005534

• HSC_colony_many_years_post_allogeneic_bone_marrow_transplant___Bait_set_3

  This study looks at human donors and recipients of allogeneic blood & marrow marrow transplantation. Each transplant "pair" (donor & recipient) underwent the transplant procedure 10 -30 years prior to sampling - the majority for an underlying diagnosis of leukemia. We will perform whole-genome sequencing on tens to hundreds of single HSPC (haematopoietic stem and progenitor cell)-derived colonies per individual. We will infer the phylogeny of these cells (those from both donor & recipient within a pair) by analysing the somatically acquired mutations within each cell. The structure of the phylogeny will allow estimates of hitherto unknown parameters such as the number of HSCs that engraft long-term, the dynamics of the engraftment process on the HSC level, and the additional mutation burden acquired through the arduous transplant procedure. This TGS part of the study is used for assessing the contribution of clones to mature blood subsets, and better timing mutations relative to transplantation.

  Study EGAS00001006572

• Genomics of Malignant Peripheral Nerve Sheath Tumor (MPNST)

  The Genomics of MPNST (GeM) Consortium dataset includes de-identified whole genome sequencing data (.bam) for germline samples (DNA primarily derived from blood) sequenced at standard (30x) coverage (n=88) and for tumor samples (DNA derived from fresh frozen tissue) sequenced at 90x coverage (n=105). This dataset also includes transcriptome profiling data (.fastq) for paired normal nerve samples (n=7) and for tumor samples (n=132).

  Dataset EGAD00001008608

• Data Access Committee for Deciphering Developmental Disorders (DDD) Project

  Dac EGAC00001000282

• Oncotrack_450K_tumor

  Oncotrack primary tumor samples using 450K. The dataset includes shared AF analysis files oncotrackDNAmAnalysis.R and oncotrackDNAmBetaScores.txt which were applied for both Oncotrack_450K_tumor (EGAD00010001162) and Oncotrack_450K_metastatic (EGAD00010001161) datasets.

  Dataset EGAD00010001162

• Whole genome sequencing of 63 single cells isolated from bone marrow aspirates of six non-metastatic breast cancer patients after staining for disseminated tumor cells.

  Dataset EGAD00001002745

• Copy Number Arrays for study EGAS00001004165

  Copy Number Alterations arrays from 153 samples performed by Affymetrix 6.0 and Oncoscan CNV platforms

  Dataset EGAD00010001841

• SAFIR02_Cytoscan

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Dataset EGAD00010002239

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

  Dataset EGAD00001005383

• Sequencing data for oesophageal and related samples - Normals release 6 (RNA)

  Dataset EGAD00001005376

• Sequencing data for oesophageal and related samples - BOs release 6 (RNA)

  Dataset EGAD00001005377

• Sequencing data for oesophageal and related samples - OACs release 4 (RNA)

  Dataset EGAD00001004021

• Clinical data IMvigor130 cohort

  Clinical data for IMvigor130 cohort of patients, including treatment, response, survial time, and tumor PDL1-IC staining score.

  Dataset EGAD50000000143

• CD8 T cell PBMC metadata

  Cell annotation for single CD8 T cells of PBMC collected from 113 patients, including UMAP coordinates and annotation

  Dataset EGAD50000000144

• Single Cell RNA-Seq

  Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq. Nine techniques applied to samples from four PDX models: #105, #177, #233, #264

  Dataset EGAD50000000216

• PREGO

  Core set of the PREGO biobank containing experimental genotypes at 209,706 autosomal sites measured on Affymetrix PMRA Axiom array plates for a group of 3,234 individuals from Western France.

  Dataset EGAD00010002661

• sWGS for 92 samples of mCRC

  Shallow Whole Genome Sequencing of 92 mCRC samples. Chromosomal copy number alterations analysis was performed with the samples to predict response to bevacizumab.

  Dataset EGAD50000000992

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

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

  Dataset EGAD50000000747

• Picuris Pueblo Genomic Project – Modern Dataset

  Please refer to the Supplemental Materials of the paper for more information.

  Dataset EGAD50000001245

• WES PTCL Data

  Whole Exome Sequencing (WES) of 153 FFPE DNA samples of Peripheral T-Cell Lymphoma. Associated with "Molecular biomarkers for stratification periheral T cell lymphoma" study.

  Dataset EGAD50000001250

• DAC policy The Kids Research Institute Australia

  DAC policy related to the study: Visium CytAssist Spatial Gene Expression analysis for FFPE glioblastoma samples. Committee: Emily Fletcher emily.fletcher@thekids.org.au Anya Jones anya.jones@thekids.org.au Emma Stone emma.stone@thekids.org.au

  Dac EGAC50000000734

• Brain Mapping by Integrated Neurotechnologies for Disease Studies: Human Brain Aging Imaging Study

  Compare the MRI data with amyloid PET images and cognitive data.

  Study JGAS000277

• RNA sequencing study for 8 pairs of primary NSCLCs and distant metastases

  This study is to understand of the molecular mechanisms driving metastasis.

  Study EGAS00001004078

• Whole exome sequencing study for 8 pairs of primary NSCLCs and distant metastases

  This study is to understand of the molecular mechanisms driving metastasis.

  Study EGAS00001004077

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0740_SA609X6

  60 samples; filetype=bam

  Dataset EGAD00001004821

• Reference epigenome KNIH005 WGBS data generated from KEP study

  A KNIH005 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002753

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0680_SA501X10A

  61 samples; filetype=bam

  Dataset EGAD00001004816

• Reference epigenome ADMSC02_smRNA-Seq data generated from KEP study

  A ADMSC02_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003868

• Reference epigenome KNIH003 WGBS data generated from KEP study

  A KNIH003 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002751

• Reference epigenome ADMSC03_smRNA-Seq data generated from KEP study

  A ADMSC03_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003869

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0837_SA501X2

  40 samples; filetype=bam

  Dataset EGAD00001004812

• JIA family

  Exome sequencing data for two sibs with juvenile idiopathic arthitis and one unaffected sib

  Dataset EGAD00001004806

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0443_SA501X7A

  48 samples; filetype=bam

  Dataset EGAD00001004813

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0739_SA609X6

  52 samples; filetype=bam

  Dataset EGAD00001004820

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0650_SA532X6

  71 samples; filetype=bam

  Dataset EGAD00001004818

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0738_SA609X6

  48 samples; filetype=bam

  Dataset EGAD00001004819

• long RNA data

  long RNA data for 27 CLL samples (8 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005968

• Lund RNAseq data

  RNAsequencing data from human pancreatic islets from 191 donors, Lund University. Processed for the Inspire consortium.

  Dataset EGAD00001005512

• Neoantigen study samples for prostate cancer

  Whole exome sequencing and RNA sequencing data from 30 patients with prostate cancer.

  Dataset EGAD00001005713

• Whole Genome Sequencing of INTERVAL (2019-06-12)

  Whole genome sequencing of participants from the INTERVAL study. . This dataset contains all the data available for this study on 2019-06-12.

  Dataset EGAD00001005084

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_005A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_005A for Lymph node patient sample RLN_03_5Prime

  Dataset EGAD00001010238

• DLP+ Single Cell Genomic Library 98211

  DLP+ Single Cell Genomic Library 98211 for Diffuse large B-cell lymphoma patient sample TFRIPAIR11_DLBCL

  Dataset EGAD00001010239

• Reference epigenome KNIH004 WGBS data generated from KEP study

  A KNIH004 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002752

• Reference epigenome DB31_N_Alpha_smRNA-Seq data generated from KEP study

  A DB31_N_Alpha_smRNA-Seq single end data for alpha cells(PSA-NCAM(-), pancreas)

  Dataset EGAD00001003494

• Reference epigenome KNIH002 WGBS data generated from KEP study

  A KNIH002 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002750

• Glioblastoma stem cell lines RNA-seq

  RNA-seq data for three Glioblastoma stem cell (GSC) lines exposed to PRMT5 inhibitor and control samples.

  Dataset EGAD00001006095

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_004A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_004A for Lymph node patient sample RLN_02_5Prime

  Dataset EGAD00001010237

• RNA-Seq Single End

  RNA analysis of six patients 34, 35, 36, 37, 38 and 39 with WGS done on Illumina HiSeq2500. For research purpose and authorised user only.

  Dataset EGAD00001003430

• Reference epigenome KNIH009 WGBS data generated from KEP study

  A KNIH009 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for preadipocytes

  Dataset EGAD00001002757

• Reference epigenome DB31_N_Alpha_mRNA-Seq data generated from KEP study

  A DB31_N_Alpha_mRNA-Seq paired end data for alpha cells(PSA-NCAM(-), pancreas)

  Dataset EGAD00001003485

• FPKM expression values of the CUP/reference/validation cohort (H021)

  FPKM expression values of the CUP/reference/validation cohort used for tissue-of-origin prediction based on transcriptomic data

  Dataset EGAD00001008638

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0741_SA609X6

  55 samples; filetype=bam

  Dataset EGAD00001004822

• Single-nucleus RNA-sequencing of meningiomas

  Single-nucleus RNA-sequencing of meningiomas for integrative molecular classification

  Dataset EGAD00001007677

• Raw count matrix for 418 baseline samples

  Count matrix from 418 pre-treatment (Ven-Obi or Clb-Obi) CD19+ B cells

  Dataset EGAD00001009501

• liCHi-C Samples of B-ALL

  Libraries of liCHi-C for 2 B-ALL (B Acute Lymphocytic Leukaemia) from human patients. Fastq file format.

  Dataset EGAD00001008829

• Reference epigenome KNIH006 WGBS data generated from KEP study

  A KNIH006 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for beta cells

  Dataset EGAD00001002754

• Reference epigenome KNIH007 WGBS data generated from KEP study

  A KNIH007 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for adipocytes

  Dataset EGAD00001002755

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0472_SA501X7A

  50 samples; filetype=bam

  Dataset EGAD00001004814

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0582_SA501X10A

  45 samples; filetype=bam

  Dataset EGAD00001004815

• Hi-C of cohesin-mutated and wildtype adult AMLs

  High-throughput chromosome conformation capture (Hi-C) data generated for cohesin-mutated (STAG2 or RAD21) and cohesin-wildtype AMLs.

  Dataset EGAD00001011198

• FMI data

  This dataset contains somatic alteration calls summarized at the gene level for 715 patients profiled by FoundationOne (Foundation Medicine).

  Dataset EGAD00001006616

• DLP+ Single Cell Genomic Library A98167

  DLP+ Single Cell Genomic Library A98167 for Diffuse large B-cell lymphoma patient sample TFRIPAIR4_DLBCL

  Dataset EGAD00001010249

• Reference epigenome ADMSC01_smRNA-Seq data generated from KEP study

  A ADMSC01_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003867

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0544_SA532X6

  68 samples; filetype=bam

  Dataset EGAD00001004817

• Whole exome sequencing of inflammatory bowel disease cases

  Whole exome sequencing of around 700 inflammatory bowel disease cases.This data can only be used for the identification of IBD/immune-mediated disease loci.

  Dataset EGAD00001001354

• Reference epigenome KNIH001 WGBS data generated from KEP study

  A KNIH001 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002749

• CYP2C19 long-read sequencing

  We have assessed the added value of long-read sequencing for PGx focusing on the clinically important and highly polymorphic CYP2C19 gene within 48 samples.

  Dataset EGAD00001009883

• DLP+ Single Cell Genomic Library A98203

  DLP+ Single Cell Genomic Library A98203 for Diffuse large B-cell lymphoma patient sample TFRIPAIR8_DLBCL

  Dataset EGAD00001010242

• DLP+ Single Cell Genomic Library A98180

  DLP+ Single Cell Genomic Library A98180 for Diffuse large B-cell lymphoma patient sample TFRI_Pair_13_DLBCL

  Dataset EGAD00001010240

• DLP+ Single Cell Genomic Library A98225

  DLP+ Single Cell Genomic Library A98225 for Diffuse large B-cell lymphoma patient sample TFRIPAIR12_DLBCL_rel

  Dataset EGAD00001010246

• KCL PRECSION lpWGS

  KCL lpWGS samples for copy number analysis

  Dataset EGAD00001008380

• Exome sequencing of relapsed/refractory DLBCL

  This dataset consists of the exome sequencing data for 30 tumour and germline DNA pairs derived from relapsed/refractory DLBCL.

  Dataset EGAD00001003395

• Genome-wide data Iberian Roma

  VCF file with genome-wide data for 62 Iberian Roma samples.

  Dataset EGAD00001006358

• Biomarker data

  Biomarker data for KATHERINE: Biomarker data include RNA-seq time point, Percent of tumor content, PAM50 subtypes, normalized gene expression of ERBB2, CD8 and CD274, normalized immune signature expression.

  Dataset EGAD00001008786

• Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

  This observational study was designed to determine the cellular tropism of Influenza A and B Viruses (IAV, IBV) from samples taken from the upper respiratory tract collected during routine nasal washes during the 2017-2018 season. Using single-cell RNA sequencing (scRNA-seq) we sought to determine which cell types could be infected, what the cellular response was to infection in both infected and bystander cells, and to compare the intra/inter-host variability of IAV and IBV during a single season at a single healthcare provider location.

  Study phs002039

• Prediction of DNA Repair Inhibitor Response in Short Term Patient-Derived Ovarian Cancer Organoids

  In this study, 34 ovarian tumor organoids generated from 23 patients underwent paired DNA damage repair defect functional analyses and whole exome sequencing analysis to compare genetic mutational status to DNA repair functional capacity. 22 of the patients had high grade serous cancer and 1 of the patients had low grade serous cancer. A normal control, fresh parent tumor, and cells from the organoid culture generated from the parent tumor underwent whole exome sequencing analysis and the data from the sequencing analysis is provided here.

  Study phs001685

• Phenotypic Signatures of Circulating Neoantigen-Reactive CD8+ T Cells in Patients with Metastatic Cancers

  Following enrichment of neoantigen-reactive T cells using pHLA tetramers or cell-surface markers, we performed single-cell sequencing (RNA-seq and TCR-seq) of circulating CD8+ T cells from metastatic cancer patient samples (Melanoma, Colorectal, and Breast cancer). In samples from previously studied patients, we identified cells bearing neoantigen-reactive T cell receptors and were able to study their phenotypic program. By studying the circulating neoantigen-reactive T cell program, a gene-signature was derived to identify neoantigen-reactive T cells from blood samples prospectively.

  Study phs003064

• NHLBI TOPMed - NHGRI CCDG: AF Biobank LMU in the context of the MED Biobank LMU

  The Atrial Fibrillation Biobank Ludwig Maximilian University (AFLMU) Study contributes to the spectrum of disease by adding carefully characterized patients with atrial fibrillation. Atrial fibrillation, one of the most common human arrhythmias confers major morbidity, mortality and health care cost, and has been demonstrated to be caused and influenced by genetic and -omics factors. Particularly, AFLMU enrolled patients with an early onset of atrial fibrillation to increase the genetic burden on disease pathophysiology. All patients were recruited applying standardized protocols to maintain homogeneity in data and DNA quality.

  Study phs001543

• Metabolic Biomarkers in Thoracic Cancers

  Here we present RNA sequencing (RNA-Seq) of non-small cell lung cancer (NSCLC) and adjacent lung tissue. These samples were acquired from primarily untreated, surgically resected primary tumors. The first analysis published with this data was to determine the metabolic signatures between primary tumors and adjacent lung tissue.The associated clinical trial (NCT02095808) includes patients with many kinds of thoracic cancers, including NSCLC and other diseases, such as thymoma and esophageal adenocarcinoma. However, the current dbGaP data is focused on the NSCLCs described in the associated paper.

  Study phs003880