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• TS and WGS data

  The dataset contains the targeted sequencing (TS) and the whole genome low pass (WGS) BAM files of the study. For the TS: Samples: TS_XXX There are normal and tumor DNA samples. Each DNA strand has been sequenced independently (PoolA and PoolB). A TruSeq Custom Amplicon panel of 20 genes frequently mutated in ILC and/or ER-positive BC in general was designed using DesignStudio from Illumina: AKT1, ARID1A, CDH1, ERBB2, ERBB3, ESR1, FOXA1, GATA3, IGF1R, JAK2, MAP2K4, MAP3K1, NF1, PIK3CA, PTEN, RB1, RUNX1, STAT3, TBX3, and, TP53. For the WGS: Samples: WGS_XXX There are normal and tumor DNA samples. Samples were sequenced to an average target coverage of 0.5X.

  Dataset EGAD00001006393

• Chracterising cellur pathways underlying CD3/CD28 activation of human CD4+ cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. 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 EGAD00001006612

• Chracterising cellur pathways underlying CD3/CD28 activation of human CD4+ cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. 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 EGAD00001006610

• Single cell RNA sequencing data in "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2"

  This dataset includes a total of 5 single cell RNA sequencing (scRNAseq) data of SARS-CoV-2 infected human alveolar stem cell culture models. Two scRNAseq data were obtained from SARS-CoV-2 infection with MOI of 1.0 (1 for control and 1 for infected case) and the other three were obtained from SARS-CoV-2 infection with MOI of 0.1 in the study entitled "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2". The 10x Chromium Single Cell 3' Reagent kits were used to generate libraries.

  Dataset EGAD00001006242

• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  We carried out WGS and RNAseq on a cohort of 48 children and young adults with induction failure in T-cell Acute Lymphoblastic Leukemia (T-ALL) to identify genomic drivers of treatment resistance. The study includes WGS for 33 tumour/normal pairs and 15 tumour-only samples. In addition, there is RNAseq data for 37 cases.

  Dataset EGAD00001009058

• Single cell sequencing of human normal luminal cells

  The dataset includes 12 paired FASTQ files (6 samples) with single cell transcriptome sequencing data of normal breast luminal cells from ducts and TDLUs derived from reduction mammoplasties from three patients. Chromium Single Cell 3’ Reagent Kit v2 or v3 (10x Genomics) were used for processing of cells, whereafter sequencing was performed using the Illumina® NextSeq500/550 High Output Kit v2. Cell Ranger was used for generating FASTQ files and files from different lanes were concatenated prior to uploading the data to EGA. "R1" files include the feature barcodes and UMIs, while "R2" files include the reads.

  Dataset EGAD00001008499

• Single-cell omics data for COVID-19 patients

  Single-cell RNA-seq, single-cell ATAC-seq, and genotypes used in the analysis for the study "Altered and allele-specific open chromatin landscape reveal epigenetic and genetic regulators of innate immunity in COVID-19". The RNA-seq and ATAC-seq are raw data in FASTQ format while the genotypes are in the VCF format which was filtered and imputed (more details are available in the main text of the study).

  Dataset EGAD00001009331

• Whole exome and transcriptome sequencing of BPDCN

  This data set contains whole exome and transcriptome data from 47 case with BPDCN. For exome data, bam files are provided (mapped against GRCh38), for transcriptome raw fastq-files (paired-end data).

  Dataset EGAD00001008692

• Summary Statistics GWAS SSNS

  Column 1 “rsid”: SNP identifier Column 2 “chromosome”: name of chromosome on which the SNP is located Column 3: “position”: base pair position on the chromosome Column 4 “minor_test_allele”: the base that constitutes the minor allele Column 5 “major_allele”: the base that constitutes the major allele Column 6 “maf”: the frequency of the minor allele, indicated as a fraction of 1 Column 7 “allele_freq_cases”: the minor allele frequency in cases Column 8 “allele_freq_controls”: the minor allele frequency in controls Column 9 “regression_pvalue”: the p-value for the difference in allele frequency between cases and controls Column 10 “odds_ratio”: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00001008782

• Immune Response Targeted Panel + B/TCR Profiling + AbSeq + Sample Tag Multiplexing

  Multiomics data for a cohort of 20 COVID-19 patients (10 patients mild, 3 patients moderate, 4 patients severe, 3 patients critical) obtained from peripheral blood mononuclear cells (PBMCs) from longitudinally sampled at hospital admission, discharge, and 1 month thereafter. The data has been obtained a multiwell-based single-cell technology (BD Rhapsody) that includes the targeted expression of BD Immune Response Targeted Panel, the TCR/BCR profiling and a set of 52 surface proteins. The samples of the different patients at different collection times were labelled using a cell hashing strategy with the BD Single-Cell Multiplexing Kit (6 samples for each run).

  Dataset EGAD00001011319

• A new subgroup of hepatocellular adenomas with sonic hedgehog pathway activation

  Using sequencing and gene expression analyses, we identified a subgroup of HCA characterized by fusion of the INHBE and GLI1 genes and activation of sonic hedgehog pathway. Molecular subtypes of HCAs associated with different patients’ risk factors for HCA, disease progression, and pathology features of tumors. This classification system might be used to select treatment strategies for patients with HCA. Related Publication: Molecular Classification of Hepatocellular Adenoma Associates With Risk Factors, Bleeding, and Malignant Transformation Nault, Jean-CharlesLaurent, Christophe et al. Gastroenterology , Volume 152 , Issue 4 , 880 - 894.e6 http://dx.doi.org/10.1053/j.gastro.2016.11.042

  Dataset EGAD00001003092

• Identification of drug resistance genes in melanoma

  Our aim is to analyze the genome of human melanoma cell lines and short term culture from human melanoma samples in order to identify genes that confer drug resistance to clinically relevant targeted therapies. We will perform whole-exome sequencing, copy number variation analysis and methylome analysis in a collection of human melanoma cell lines and short term culture that will be then screened for drug sensitivity/resistance through a library of clinically relevant drugs and drug combinations. By the combined analysis of the genomic lesion and the drug sensitivity/resistance profile of different cell lines, we will look for genes whose mutation is associated to the sensitivity or resistance to a specific drug in different samples.

  Dataset EGAD00001001124

• SCLC study George et al. - WGS data set

  Whole genome sequencing was performed with DNA extracted from fresh-frozen tumor and normal material. Short insert DNA libraries were prepared with the TruSeq DNA PCRfree sample preparation kit (Illumina) for paired-end sequencing at a minimum read length of 2x100bp. Human DNA libraries were sequenced to an average coverage of minimum 30x for both tumor and matched normal. Murine DNA libraries of tumor and matched normal were both sequenced to a coverage of 25x.

  Dataset EGAD00001001273

• Tam-Seq of HGSOC samples for fixative comparison study

  Targeted amplicon sequencing of samples as part of the study "Methanol-based fixation is superior to buffered formalin for next-generation sequencing of DNA from clinical cancer samples. The amplicon panel consists of 48 amplicons in TP53, PTEN, EGFR, PIK3CA, KRAS and BRAF genes as described previously [Forshew, STM 2012]. All libraries were pooled and quantify using DNA 1000 kit on Agilent 2100 Bioanalyzer and KAPA SYBR FAST ABI Prism qPCR Kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations. Reads were aligned using bwa-mem v0.7.12-r1039 to the 1000 genomes version of human genome build GRCh37, retaining duplicate reads.

  Dataset EGAD00001001937

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

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

  Dataset EGAD00001003433

• Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes

  The dataset consists of Oxford Nanopore targeted RNA-based amplicon data of 12 classical HLA genes (HLA-A, -B, -C, -DRA, -DRB1, -DRB3, -DRB4, -DRB5, -DQA1, -DQB1, -DPA1, and DPB1) of 50 healthy individuals. The 12 classical genes were sequenced in two separate gene pools on R9.4 flowcells using MinION sequencer. Per individual, gene pool 1 contains HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, and -DPB1 and gene pool 2 HLA-DRA, -DQA1, -DQB1, and -DPA1. The dataset includes 100 fastq files of Oxford Nanopore 2D reads (50 for gene pool 1 and 50 for gene pool 2).

  Dataset EGAD00001006814

• A108768B

  Whole genome sequencing for single cells for library A108768B 1126 cells; filetype=bam

  Dataset EGAD00001007089

• cis-eQTL mapping of TB-T2D comorbidity in a five-way admixed SA cohort

  The aim of the study was to identify ancestry-specific genetic variants associated with differentially expressed genes in TB-T2D comorbid patients compared to T2D patients, as well as between TB patients and healthy controls. Both global and local ancestry was incorporated in regression models to account for the genetic heterogeneity in our complex multi-way admixed population.

  Study EGAS00001007059

• Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  The intra- and inter- tumoral heterogeneity of glioblastoma represents a significant therapeutic challenge, as well as difficulty in generating reliable models for in vitro studies. Here, we quantify the tumor cell composition from matched patient-derived neurospheres (PDN) and organoids (PDO) established from the same primary tumor using a series of multi-omic interrogations, relative to primary tissue

  Study EGAS00001008023

• Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation

  We tested the efficiency and reproducibility of 10 RNA isolation methods on 5 different biofluids. Pooled human plasma and serum, bile and urine were used along with cell culture supernatants from human embryonic stem cells (hESC), primary neonatal rat ventricular myocytes (NRVM) and human cholangiocarcinoma cells (KMBC). 4 RNA isolation methods designed to isolate total RNA from bio fluids without enrichment of exRNA carriers were used. 6 methods that preferentially enriched for exRNA carriers were also compared. Small RNA libraries were constructed using the NEBNext small-RNA library prep. The efficiency and reproducibility of the different RNA isolation methods was compared using small-RNA seq.

  Study phs002143

• Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) Center for Environmental Health Disparities

  MADRES is a prospective pregnancy cohort based in urban Los Angeles, recruiting predominantly low income Hispanic mothers-to-be as part of a children's health study, funded by Environmental Influences on Child Health Outcomes (ECHO). Participants were measured for a number of chemical exposures and biomarkers. Two epigenetic markers will be available through dbGaP: miRNA expression in pregnancy (measured via Nanostring human assay, v3) and DNA methylation from pregnancy and children's cord blood (measured via EPIC array). Principal findings of this research described differences in miRNA expression profiles between early and late pregnancy, as well as miRNA expression affected by psychosocial stress.

  Study phs003194

• PAX4 loss of function increases diabetes risk by altering human pancreatic endocrine cell development

  The coding variant (p.Arg192His) in the transcription factor PAX4 is associated with an altered risk for type 2 diabetes (T2D) in East Asian populations. In mice, Pax4 is essential for beta cell formation but its role on human beta cell development and/or function is unknown. Participants carrying the PAX4 p.His192 allele exhibited decreased pancreatic beta cell function compared to homozygotes for the p.192Arg allele in a cross-sectional study in which we carried out an intravenous glucose tolerance test and an oral glucose tolerance test. In a pedigree of a patient with young onset diabetes, several members carry a newly identified p.Tyr186X allele. In the human beta cell model, EndoC-βH1, PAX4 knockdown led to impaired insulin secretion, reduced total insulin content, and altered hormone gene expression. Deletion of PAX4 in human induced pluripotent stem cell (hiPSC)-derived islet-like cells resulted in derepression of alpha cell gene expression. In vitro differentiation of hiPSCs carrying PAX4 p.His192 and p.X186 risk alleles exhibited increased polyhormonal endocrine cell formation and reduced insulin content that can be reversed with gene correction. Together, we demonstrate the role of PAX4 in human endocrine cell development, beta cell function, and its contribution to T2D-risk.

  Dataset EGAD50000000516

• Peripheral blood RNA sequencing of samples for a healthy cohort and a cohort with cancer patients

  RNA sequencing (fastq files) of white blood cells (WBCs) from healthy donors (n=376) and cancer patients (n=421) with different diagnoses, stages of disease and previously administered treatments, was performed. Samples from cancer patients were collected from the BostonGene clinical program; all patients provided written consent per IRB-approved protocols. Blood samples from healthy donors were purchased from multiple collection centers throughout the United States. Whole blood samples (3 ml) in K2-EDTA tubes received within 24 hours of collection at RT underwent red blood cell (RBC) lysis to isolate WBCs. Isolated WBCs for RNA sequencing were centrifuged at 300 x g for 5 minutes with a maximum of 10^6 cells per vial. The supernatant was removed, and the cells were resuspended in cold Homogenization Buffer (2% 1-Thioglycerol, Promega). Samples were then frozen at -80°C until extraction. RNA extraction was performed from frozen samples with Maxwell RSC simplyRNA Cells Kit (Promega) using the benchtop automated Maxwell RSC Instrument (Promega). Libraries were prepared with Illumina TruSeq® Stranded mRNA Library Prep (Poly-A mRNA; stranded). Libraries were sequenced on NovaSeq 6000 as Paired-End Reads (2x150) with targeted coverage of 50 mln reads.

  Dataset EGAD50000000414

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  This study introduces MorphoITH, a framework for deconvolving intra-tumor heterogeneity (ITH) in clear cell renal cell carcinoma (ccRCC) based on tissue morphology from histopathological slides. The study tested MorphoITH's ability to capture different aspects of morphology and to reflect genetic ITH. The data deposited here is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. This dataset consists of whole exome sequencing of tumor from multiple sites and adjacent normal samples which were collected from two patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital.

  Study EGAS50000001064

• Development of Novel Histiocytic Sarcoma Organoid Model for Drug Discovery

  Histiocytic sarcoma is an extremely rare and aggressive hematopoietic malignancy. Its pathogenesis remains poorly understood and effective treatments are lacking. We treated a patient with histiocytic sarcoma of soft tissue in Osaka International Cancer Institute and established an organoid culture from a resected tumor specimen using a modified air���liquid interface method. After serial passaging, the organoid was successfully xenografted into NOD-scid IL2Rgnull (NSG) mice. The established organoid retained key histological features and genetic characteristics of the original tumor. This organoid model offers a novel and reliable platform for studying the biology of histiocytic sarcoma and may contribute to the development of future therapeutic strategies.

  Study JGAS000807

• Whole-genome bisulfite sequencing for high-grade glioma

  We conducted whole-genome bisulfite sequencing to delineate base-resolution methylomes of gliomas harboring G34R mutation as well as those harboring K27M and no mutations in H3F3A. Comparative analysis of these three glioma subgroups revealed that G34 subgroup exhibited lower global methylation levels, comparable CpG island (CGI) methylation levels, and compromised hypermethylation of telomere-proximal CGIs, compared to the other two subgroups. Genomic regions specifically hypermethylated in G34 subgroup were enriched for CGIs. CGIs with G34V-mutated histone H3.3 in the glioma cell line KNS-42 were hypermethylated compared to those without it, suggesting a correlation between G34-mutated histone H3.3 in CGI hypermethylation.

  Study JGAS000197

• Development of hunanized mice for human hematopoisis and immunity research

  We obtained peripheral blood or bone marrow samples from 112 acute myeloid leukemia patients and examined sensitivity and resistance of the AML samples to molecular targeting drugs. By doing RNA sequencing using AML cells, we found heterogenous gene expression patterns in AML with different mutational landscapes. From the RNA sequencing, we identified anti-apoptosis, cell cycle progression, and immune-related signals as pathways up-regulated in AML cells as compared with normal CD34+ cells. From the pathway analyses, we further setup in vitro experiments to find vulnerability genes in clinically-aggressive AML. BIRC, BCL2, MCL1, AURKB, and KIF10 may be essential molecules for AML cell survival and proliferation.

  Study JGAS000253

• How are we funded?

  How are we funded? The EGA is provided infrastructure, administrative support, advisory input, and other relevant and necessary aspects by: CRG The EGA at the CRG is funded and supported by “La Caixa Foundation”, The Generalitat de Catalunya (Catalan Government), the Spanish Ministerio de Asuntos Económicos y Transformación Digital (Spanish Government) and the Instituto de Salud Carlos III. The Generalitat de Catalunya contributes with funding to the CRG and to the Barcelona Supercomputing Centre (BSC). The Barcelona Supercomputing Center is decisively contributing to EGA by providing the required compute, storage and networking resources, as well as key personnel for shared operations of EGA infrastructure. EMBL-EBI As part of the European Molecular Biology Laboratory (EMBL), the EGA at EMBL’s European Bioinformatics Institute receives funding from the governments of EMBL’s member states. The UK government, via UK Research and Innovation, also continues to support EMBL-EBI technical infrastructure, with EMBL supporting operational costs. A major source of funding for the EGA both at CRG and EMBL-EBI are competitive projects.The EGA resource continues to be funded through strategic engagement in collaborative partnerships and projects. Please see our projects page for more information. Other funders include the European Commission, the US National Institutes of Health, the Wellcome Trust, UK Research Councils, and our Industry Programme partners. Last updated on October, 2024.

  Documentation about/projects-and-funders/funders

• A personalised medicine approach for ponatinib-resistant chronic myeloid leukaemia

  Chronic myeloid leukaemia (CML) is characterised by the presence of a fusion driver oncogene, BCR-ABL1, which is a constitutive tyrosine kinase. Tyrosine kinase inhibitors (TKIs) are the central treatment strategy for CML patients and have significantly improved survival rates, but the T315I mutation in the kinase domain of BCR-ABL1 confers resistance to all clinically approved TKIs, except ponatinib. However, compound mutations can mediate resistance even to ponatinib and remain a clinical challenge in CML therapy. Here, we investigated a ponatinib-resistant CML patient through whole genome sequencing (WGS) to identify the cause of resistance and to find alternative therapeutic targets.

  Study EGAS00001001150

• Sequencing data of multiple sarcoma samples for personalized medicine and endotype identification

  Sequencing data derived from multiple patient samples was used to guide multiple patient-specific experiments and identify potential therapeutic options. These diseases are rare and high-risk (undifferentiated pleomorphic sarcoma, rhabdomyosarcoma) and thus have few available validated clinical options. This leaves the population of patients with few options if, and when, standard therapy fails to cure or control disease. An aspect of the personalize therapy design included the identification of broader disease endotypes (a combination of genetic and clinical data describing patient status) to identify subgroups of the individual disease that could better define treatments and could segment patient populations for deeper preclinical research.

  Study EGAS00001003981

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

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

  Study EGAS00001000327

• Field effect of healthy and diseased livers (2019-04-08)

  Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences). . This dataset contains all the data available for this study on 2019-04-08.

  Dataset EGAD00001004941

• Understanding Self- Organising Capacity of Stem Cells during Implantation and Early Post-implantation Development in vitro and in vivo: Implications for Human Development (2020-04-20)

  The aim of this project is to differentiate human embryonic stem cells to an extra-embryonic fate, specifically the hypoblast. This is of uttermost importance given the current lack of human hypoblast stem cells. We hypothesized that the pluripotent characteristics of the starting human embryonic stem cell population may dictate the competency for extra-embryonic cell fate specification. Based on this hypothesis and using human embryonic stem cells maintained in different naïve-like culture regimes, we have now developed conditions that allow the differentiation of human embryonic stem cells to a stable GATA6+ SOX2- population. This suggests that these cells may be putative human hypoblast stem cells. To validate this finding here we propose to perform RNA sequencing experiments of the differentiated human embryonic stem cells. By comparing their RNA expression profile to the single cell sequencing data of the human embryo that we are currently generating, we will be able to determine the identity of our GATA6+ SOX2- cells, and establish whether they represent the in vivo human hypoblast. This dataset contains all the data available for this study on 2020-04-20.

  Dataset EGAD00001006056

• A spatial human thymus cell atlas mapped to a continuous tissue axis

  T cells develop from circulating precursor cells, which enter the thymus and migrate through specialised sub-compartments that support their maturation and selection. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the micro-anatomical underpinnings of this process in pre- and early postnatal stages, we established a novel quantitative morphological framework for the thymus, the Cortico-Medullary Axis, and used it to perform a spatially resolved analysis. By applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics, and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions within the first trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall’s corpuscles and uncover divergence in the timing of medullary entry between CD4 vs. CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation, and Organ Axis construction (TissueTag), which can be applied to any tissue.

  Dataset EGAD00001015384

• Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

  Rituximab, a CD20+ B cell depletion therapy, is frequently used in the treatment of systemic lupus erythematosus (SLE). However, variability in patient response highlights the need for a deeper understanding of the underlying immune cell dynamics of B cell depletion and repopulation. In this study, we conducted longitudinal single-cell profiling of nine SLE patients treated with rituximab from pretreatment to up to 15 months post-treatment. These were compared to eight healthy controls. We profiled PBMCs via 10X Genomics single-cell RNA, surface protein (CITE-seq), B cell receptor (BCR), and T cell receptor (TCR) sequencing and sequenced bulk BCR repertoires in parallel. For single cell sequencing, 10 pools were created with an equal number of cells from 4 samples each. Samples collected at different timepoints from the same patient were distributed across different pools to allow demultiplexing of individuals using genotypes captured from the scRNA-seq data. Libraries were pooled using a ratio of GEX:CITE:TCR:BCR=9:2:1:1 and were sequenced across two lanes of the NovaSeq 6000. For bulk BCR sequencing, individual samples were demultiplexed using primer barcodes and paired-end BCR amplicon reads were merged prior to submission; data are provided as unmapped single-end reads.

  Dataset EGAD00001015817

• BLUEPRINT EpiVar ChIP-seq in lineage specifying transcription factors

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise "experimental noise" and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. This data set contains functional genomics data for gene expression and chromatin state.

  Dataset EGAD00001004571

• How to upload Crypt4GH files

  Uploading files Users who hold an ega-box-XXX account can upload files using either INBOX or FTP. Users who have a Submitter role associated with their email will only be able to upload files using INBOX. Before uploading your files, please make sure that any files that will be uploaded to EGA do not use special characters in their naming convention, such as # ? ( ) [ ] / \ = + < > : ; " ' , * ^ | &. This can cause issues with the archiving process, leading to problems for end users. The EGA is a shared, public service with limited storage. To manage the available resources, we enforce a limit of 10TB per submission account at any one time. If you exceed this limit, a “permission denied” message will be displayed. This will prevent you from uploading more files, but connecting to your inbox.For submissions larger than 10TB, please perform uploads in 10TB batches: register all the metadata and then finalise the submission. Upload the next batch of files and repeat the same metadata registration and finalisation process until you have completed the file upload. Further information can be found in the SP documentation. INBOX FTP The INBOX is only compatible with files encrypted using the Crypt4gh tool Before uploading If you are not a registered EGA user, you will first need an EGA user account. Please note that it may take a few days for your account to be activated, as it needs to be vouched for by the EGA Helpdesk. Once your account is validated, you will be able to request a submitter role. [Optional] Meanwhile, you can create and add your public key to your EGA account profile. This option is not available for old submission accounts (e.g., ega-box-NNN). As soon as you have been granted a submitter role, you will be able to connect with your username and password to the EGA inbox using the SFTP protocol. If you have also registered a public key in your profile, you can also connect using this key. To upload files to your account, you can use the graphical user interface (GUI) or the command line. Graphical User Interface (GUI)We recommend using FileZilla, a free, open-source FTP client. However, you can use any other GUI that allows connecting over the SFTP protocol. For FileZilla as your GUI, follow these steps to upload files: Create a new connection in Site Manager (File > Site Manager) and select the following options (Figure 1): Protocol: SFTP - SSH File Transfer ProtocolHost: __EGA_INBOX_DOMAIN__Logon Type: Key fileUser: your EGA usernameKey file: Path/to/your/private_keyFigure 1: Process of establishing a new connection to __EGA_INBOX_DOMAIN__ using a key file as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers.Click Connect, and you will log in remotely to your home directory. You can think of this folder as a storage "in the EGA cloud" in which you will add your files for the EGA. The uploading area has three folders:To-encrypt: Files uploaded in this folder will be encrypted automatically on the fly.Encrypted: Files uploaded in this folder must already be encrypted with Crypt4gh. Upload your files here if your connection is unstable or you have problems completing the upload into-encrypt.Etc: This folder contains two files that allow the server to show you your username and group instead of some internal numbers. Please do not upload files here; otherwise, you will obtain a permission denied error. Find the files you want to upload by browsing your local storage (left side of your screen in FileZilla). Select all the files you want to upload, then right-click on them and select Upload (Figure 2). Figure 2: Step-by-step process of manually uploading files to __EGA_INBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can transfer data from their local storage to the "EGA cloud" by following the depicted steps Please note that regardless of which folder you upload your files in, both folders (to-encrypt, encrypted) will point to the same path (/) (Figure 3). Therefore, you will see your files in both folders. Figure 3: Both folders, to-encrypt and encrypted, point to the same path (/)" If your connection is unstable, please encrypt your files first using Crypt4gh. Then upload them to the ‘encrypted’ folder. The example above shows how to connect to __EGA_INBOX_DOMAIN__ using the private key. However, if you prefer to log in using your credentials, you can do so. Please go to the Frequently Asked Questions (FAQs)  for more information. SFTP command line To upload files securely to your private area of the EGA, you can use SFTP(Secure File Transfer Protocol) with your favorite FTP client. Here's what you need to know to get started: Connect to the target host __EGA_INBOX_DOMAIN__. This is the new hostname for the EGA SFTP service. Log in with your EGA username and key files (or password). Upload files to your private EGA inbox to ensure that only you can access the files. By following these steps, you can securely upload your files to the EGA for safe storage and sharing. Using the SFTP command line client in Linux/Unix Open a terminal and type sftp username@hostnameEnter your EGA passwordTo see a list of available SFTP commands, type helpsftp> put – Upload filesftp> get – Download filesftp> cd path – Change remote directory to ‘path’sftp> pwd – Display remote working directorysftp> lcd path – Change the local directory to ‘path’sftp> lpwd – Display local working directorysftp> ls – Display the contents of the remote working directorysftp> lls – Display the contents of the local working directoryType the "put" command to upload files. For example: put *.bamUse the bye command to close the connection (SFTP session). After uploading- Once you have uploaded files to the inbox, please bear in mind that the checksum needs to be calculated, which can take up to two days. You will only be able to link your files to a run/analysis once the encrypted checksum has been calculated.- When linking your files to the 'Run' or 'Analysis', ensure that the file name matches the file path '/name' in the INBOX folder.- Please delete the files from your SFTP INBOX after all the runs/analyses have been registered and files are ingested (SP > Files > Files ingested). This will clear your inbox space an allow you to upload more files. This will also prevent the files from reappearing in your Submitter Portal inbox. Frequently Asked Questions Specific to the inbox What username should I use to log in to my inbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username.  If you have forgotten your registered username, please contact our Helpdesk team for assistance. How are checksums calculated in your inbox? If you encrypt the file beforehand and upload it to the "encrypted" folder, the unencrypted checksum will not be calculated until the file is ingested (i.e., until it is used in a run/analysis). If the file is uploaded to the "to-encrypt" folder, then both checksums are calculated.Please bear in mind that after files have been uploaded to the inbox, the checksum must be calculated, which can take from a few hours to two days.  Specific to using keys to authenticate Can I access one EGA account from different devices? Yes, you can access your account from different devices by linking several public keys to your EGA account. Each device can generate a unique public-private key pair, and the corresponding public keys can be linked to the same account. This way, you can use different public keys on different devices and still have access to the same account and data. I have several keys and I don't remember which one is which When generating SSH keys, it's a good practice to add a comment using the -C flag. This will allow you to add a descriptive tag to your key, making it easier to identify later on. Here's an example command that generates an SSH key with a comment: ssh-keygen -t ed25519 -C work-pass In this example, we're generating an ed25519 SSH key with the comment work-pass. Once you have multiple keys with different comments, you can use the comments to easily identify each key. To view the comments for your existing SSH keys, you can use the following command: ssh-keygen -l -f /path/to/key This will display the key fingerprint and the associated comment. By checking the comments, you should be able to identify which key is which. What if I can't find my SSH keys for uploading files with a key file, and how can I use new keys? If you can't find your SSH keys, don't worry - you can make new ones. To do this, open your terminal or command prompt and type a command to make a new SSH key. You can pick a name for the key, and choose a password to keep it safe. After making the key, you can add the new key to your account or server where you want to upload files using the key file. This usually involves copying and pasting the key's "public" (e.g. file.pub) part to the right place. If you lose track of the key again, just make a new one and add it again. Keep in mind that SSH keys belong to you and your computer, so if you switch computers or accounts, you'll need to make new keys. I don't want to type the passphrase every time I use the key. What can I do? You can use an ssh-agent to avoid typing the passphrase every time you use the key. An ssh-agent is a program that stores your private keys in memory and provides them to ssh when needed. You can add your key to the ssh-agent using the command ssh-add followed by the path to your key file.Here's an example of the steps to follow: Open a terminal window.Start the ssh-agent by typing the command eval $(ssh-agent).Add your key to the ssh-agent by typing the command ssh-add [key filepath]. For instance, if your key file is located in the home directory with the name mykey, the command will look like this: ssh-add ~/mykey After adding your, key to the ssh-agent, you should be able to use ssh without having to enter your passphrase every time. Can I use my password for authentication (without my private key)? If you prefer to use your username and password for authentication instead of your private key, you can still do so. When using a Graphical User Interface (GUI) such as FileZilla, you can select Ask for password as your Logon Type (Figure 3). This option will prompt you to enter your password when you click Connect, instead of using your private key. Figure 3: This option will prompt you to enter your password when you click "Connect", instead of using your private key. Figure 3: Process of establishing a new connection to __EGA_INBOX_DOMAIN__ using your password as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers. It's worth noting that using a password for authentication can be less secure than using an SSH key, as passwords can be more easily compromised through various means. However, if you choose to use your password for authentication, selecting "Ask for password" as your Logon Type is a good way to do so securely via a GUI. Why is it better to use my key and not my password? SSH keys for authentication is generally considered to be more secure and convenient than using passwords. SSH keys are more difficult to crack than passwords, and they can be restricted to specific users and machines, giving you more control over access. Once you set up your SSH keys, you can use them to authenticate quickly and easily, without having to enter a password every time. This makes automation of tasks, such as uploading encrypted files, much simpler. Additionally, SSH keys provide better logging, allowing you to keep track of who is accessing your systems and when. All in all, using SSH keys is a good practice for improving security and convenience in your authentication process.

  Documentation submission/data/uploading-files/inbox

• GeneSTAR (Genetic Study of Atherosclerosis Risk) NextGen Consortium: Functional Genomics of Platelet Aggregation Using iPS and Derived Megakaryocytes

  The causal mechanisms of common diseases and their therapies have been only marginally illuminated by genetic variants identified in genome wide association studies (GWAS) utilizing single nucleotide polymorphism (SNPs). Platelet activation pathways reflecting hemostasis and thrombosis are the underlying substrate for many cardiovascular diseases and related acute events. To overcome GWAS limitations, genomic studies are needed that integrate molecular surrogates for platelet-related phenotypes assayed in cell-based models derived from individuals of known genotypes and phenotypes. In our GWAS study of native platelet aggregation phenotypes and aggregation in response to low dose aspirin in 2200 subjects (GeneSTAR, Genetic Study of Aspirin Responsiveness), important genome wide "signals" (p&lt;5x10-8) associated with native platelet aggregation and important "signals" associated with platelet responsiveness to aspirin were identified and replicated. Although we are currently performing functional genomics studies to elucidate our most promising findings in known genes (PEAR1, MET, PIKC3G), most "signals" occurred in intergenic regions or in introns. Mechanistic interpretation is limited by uncertainty as to which gene(s) are up- or down-regulated in the presence of most SNP modifications. In this 3 phase proposal, we will (1) create pluripotent stem cells (iPS) from peripheral blood mononuclear cells, and then differentiate these stem cells into megakaryocytes (2) develop an efficient strategy to produce iPS and megakaryocytes using a novel pooling method, and (3) produce iPS and megakaryocytes from 250 subjects in GeneSTAR (European Americans and African Americans), selected based on specific hypotheses derived from GWAS signals in native and post aspirin platelet function; characterize genetic mRNA transcripts using a comprehensive Affymetrix array; measure protein expression for transcripts of interest using mass spectrometry; examine mRNA and protein expression patterns for each GWAS signal to determine the functional pathway(s) involved in native platelet phenotypes; and examine the functional genomics of variations in responsiveness to aspirin using our prior genotyped and phenotyped population. Precise information about the exact functional processes in megakaryocytes and platelets may lead to innovative and tailored approaches to risk assessment and novel therapeutic targets to prevent first and recurrent cardiovascular and related thrombotic events.

  Study phs001074

• A New Reference Panel to Boost African American Genotype Imputation

  Modern genetic studies have been conducted predominantly in cohorts of individuals of European ancestry. By 2010, there were approximately ten times as many published genome wide association studies (GWAS) in people of European ancestry than studies in people of all other ancestries combined. This research disparity has led to an uneven understanding of the genetic basis underlying disease in Europeans and non-Europeans. 23andMe's web-based, large scale research model is ideal for scaling genetics research within non-European populations and thereby bringing more parity to genetics research. Our database is composed of genotypes and phenotypes of over 1,000,000 consenting customers, including over 200,000 individuals with non-European ancestry. The data derived from non-European individuals represent a particularly valuable resource for genetic discovery of novel variants that may not be found in the European population. However, research studies in non-European populations are weakened by the lack of availability of large-scale reference datasets and, in particular, genotype imputation panels. Genotype imputation is a statistical methodology that uses observations of genotypes in a large reference panel to infer unobserved genotypes in a target dataset. This methodology is widely used within GWAS, and allows novel genetic associations to be identified and refined. Due to this utility, very large reference panels have been constructed, containing thousands or tens of thousands of whole genome sequences. Unfortunately, the largest imputation panels are composed of predominantly European genomes, reflecting the modern bias towards European studies in GWAS. This proposal aims to address this imbalance by constructing an imputation panel specifically for the African American population. In doing so, we will expand 23andMe's ability to perform genetic discovery in non-European populations, and improve the understanding of global genetic variation underlying diseases and traits. Key commercial outcomes of the research include the identification of novel genetic targets for internal and external therapeutic development. The long-term aim is to improve understanding of disease in minority populations, which we hope may eventually lead to improved treatments of disease in these historically medically understudied groups.

  Study phs001798

• A Single Cell Atlas of Gene Regulatory Elements in the Human Heart

  Background: Cis-regulatory elements such as enhancers and promoters are crucial for directing gene expression in the human heart. Dysregulation of these elements can result in many cardiovascular diseases that are major leading causes of morbidity and mortality worldwide. In addition, genetic variants associated with cardiovascular disease risk are enriched within cis-regulatory elements. However, the location and activity of these cis-regulatory elements in individual cardiac cell types remains to be fully defined. Methods: We performed single nucleus ATAC-seq and single nucleus RNA-seq to define a comprehensive catalogue of candidate cis-regulatory elements (cCREs) and gene expression patterns for the distinct cell types comprising each chamber of four non-failing human hearts. We used this catalogue to computationally deconvolute dynamic enhancers in failing hearts and to assign cardiovascular disease risk variants to cCREs in individual cardiac cell types. Finally, we applied reporter assays, genome editing, and electrophysiogical measurements in in vitro differentiated human cardiomyocytes to validate the molecular mechanisms of cardiovascular disease risk variants. Results: We defined &gt;287,000 candidate cis-regulatory elements (cCREs) in human hearts at single-cell resolution, which notably revealed gene regulatory programs controlling specific cell types in a cardiac region/structure-dependent manner and during heart failure. We further report enrichment of cardiovascular disease risk variants in cCREs of distinct cardiac cell types, including a strong enrichment of atrial fibrillation variants in cardiomyocyte cCREs, and reveal 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Two such risk variants residing within a cardiomyocyte-specific cCRE at the KCNH2/HERG locus resulted in reduced enhancer activity compared to the non-risk allele. Finally, we found that deletion of the cCRE containing these variants decreased KCNH2 expression and prolonged action potential repolarization in an enhancer dosage-dependent manner. Conclusion: This comprehensive atlas of human cardiac cCREs provides the foundation for not only illuminating cell type-specific gene regulatory programs controlling human hearts during health and disease, but also interpreting genetic risk loci for a wide spectrum of cardiovascular diseases.

  Study phs002204

• NHLBI and NIDDK Sponsored GWAS in Benign Ethnic Neutropenia/Leukopenia (BEN) in African-Americans (age >45 yrs old) from the REGARDS

  Benign ethnic neutropenia (BEN) is a clinical condition more commonly observed in African-Americans. It is characterized by a relative reduction in neutrophil count by about 1000 cells per microliter, leading to a decrease in total leukocyte count by similar decrement. Previous reports of this condition showed that there was neither higher frequency nor increased severity of infections in affected individuals. Bone marrow examinations showed normal white cell maturation; and ex vivo culture of marrow cells showed low normal or slightly reduced number of myeloid colonies. Under physiologic stress, the increases in neutrophil and leukocyte counts of BEN individuals are slightly lower, compared to normal African-Americans or Caucasians. These clinical observations suggest that BEN results from a lower &#39;set point&#39; for cell number in the marrow. Additionally, case reports of familial BEN, the persistence of BEN over many decades in the US, UK, and Africa, and the recent report of Duffy antigen and chemokine receptor (DARC) being associated with neutropenia, all suggest a strong genetic association to neutropenia/leukopenia. Our initial look into microarray analyses in a pilot trial of subjects showed that there were no significant differences in mRNA signals between BEN and normal subjects. Therefore, we are now proposing a larger study, utilizing Illumina Omni Express chips, to look for genetic associations. We have partnered with the Reasons for Geographic and Racial Differences in Stroke study (REGARDS), where nearly half of the cohort are African-Americans. This will be one of the few GWAS being performed in only African-Americans, and will provide valuable genetic information to link with neutropenia and possibly other conditions/diseases. Genotyping was performed by the Johns Hopkins University Center for Inherited Disease Research (CIDR). Quality control of the genotypic and phenotypic data was performed through a collaboration between CIDR and the Genetics Coordinating Center, Department of Biostatistics at the University of Washington, which is funded by a federal contract supported by 14 NIH Institutes (HHSN268200782096C).

  Study phs000507

• Longitudinal Studies of Patients with Familial Platelet Disorder with Associated Myeloid Malignancy (FPDMM)

  FPDMM (OMIM #601399) is a rare autosomal dominant disease characterized by defective megakaryocytic development, thrombocytopenia, platelet functional defects, and a life-long risk of developing hematological malignancies. FPDMM is caused by germline mutations in the RUNX1 gene, which encodes a master regulator of hematopoiesis. The overall lifetime risk of hematological malignancies in FPDMM patients is 35 - 45%. It is hypothesized that mutations in other genes cooperate with the germline RUNX1 mutations for leukemia development. However, it is not clear which genes need to be mutated for leukemia to develop and which biomarkers or clinical tests can be used to predict which patients will progress to leukemia. Likewise, there are no treatments and/or preventative measures that can reduce or stop disease progression except for stem cell transplantation, which is not available for all patients and may be associated with significant complications. To address these questions, we launched a longitudinal natural history study of patients associated with RUNX1 germline mutations at the NIH Clinical Center in early 2019 (Trial Registration ID: NCT03854318). The goals of this study are to: (1) perform comprehensive longitudinal phenotyping of FPDMM patients to document the full spectrum of both hematopoietic and non-hematopoietic manifestations of the disease; and (2) perform extensive genomic analyses of FPDMM patient samples to identify cooperating genomic variants, which may confer growth advantage that leads to clonal expansion of affected hematopoietic cells that may serve as the precursor to malignancies. The data available through dbGaP include exome sequencing and RNA-seq data from these patients. Diverse germline mutation types were identified in the RUNX1 gene, including splice site mutations and large deletions, in addition to nucleotide substitutions and small indels. Somatic mutations, especially in genes associated with clonal hematopoiesis of indeterminate potential (CHIP), were found in a substantial proportion of FPDMM patients who were leukemia-free. The findings suggest that the genomes in these patients are prone to somatic mutations and monitoring the dynamic changes of these somatic mutations prospectively may provide a way to predict progression to malignancies.

  Study phs003075

• National Institute of Mental Health (NIMH) Duke Cognition Cohort

  The overall goal is to identify genetic variants influencing normal variation between humans, with a focus on cognitive and neurosensory traits. Because of the focus of funding agencies on disease, very few studies of the genetics of non-disease traits have been performed. The genetic variation underlying the vast majority of differences between humans therefore remains not only undiscovered, but also unexplored. We have assessed &#62;1,200 healthy volunteers for &#62;70 diverse, non-disease phenotypes, with a focus on cognitive and neurosensory traits that are understudied and seem to have a strong biological basis. Our study includes measurements of face recognition, night vision, cognitive performance, auditory pitch discrimination, contagious yawn susceptibility, time perception, sense of direction, taste preferences, personality, sexual behaviors, sleep habits, acne, headache locations, synesthesia, and teeth sensitivity. This method is very different from the focus of most studies on collecting cohorts of patients with disease and controls with minimal phenotypic information. Because we phenotype the same healthy volunteers for multiple highly variable yet heritable traits, we can perform genetic analyses on a large number of phenotypes by just investing once in sequencing the DNA of these participants. An additional &#62;2,000 participants in our cohort have been measured just for cognitive performance instead of for the more extensive phenotyping. Most of the genetic studies in this cohort have been about cognitive perfromance. The number of participants with genetic data generated who have undergone the more extensive phenotyping is limited. Our studies of the more novel traits like contagious yawning have therefore focused more on correlations between different phenotypes until we have a sufficient sample size to truly attempt to make genetic discoveries. . The dataset also includes two small challenge studies. In one study, the cognitive performance of 150 healthy volunteers was measured before and after an acute dose of the antiepileptic drug topiramate. In the other study, the cognitive performance of 13 healthy volunteers was measured before and after 24 hours of sleep deprivation.

  Study phs001406

• Exceptional Responders Initiative

  The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is &#60; 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

  Study phs001145

• Bacterial Vaginosis, Cervical Immune Cells and HIV Susceptibility

  This was a cross-sectional study to characterize cervical immune cell composition and activation status in the presence versus absence of bacterial vaginosis (BV) using bulk messenger RNA sequencing (mRNA-Seq). Women enrolled in a longitudinal, open cohort study and engaged in a sex work in Mombasa, Kenya, were eligible. On the day of enrollment, participants self-collected vaginal swabs for generation of Gram-stained slide. The slides were scored from 0-10 using the method of Nugent and Hillier; in this system, women with scores of 0-3 are considered to have normal vaginal flora, those with scores of 4-6 are considered to have intermediate flora, and those with scores of 7-10 are considered to have BV. For this study, only women with normal flora (Nugent scores 0-3) or BV (Nugent scores 7-10) were eligible. Participants underwent speculum-assisted pelvic examination and collection of cervical biopsy specimens using Tischler forceps. Biopsies were placed immediately in ice cold medium and transferred to the laboratory where they were weighed and transferred to freezing medium (10% DMSO + fetal bovine serum) and cooled slowly overnight. Samples were shipped from Kenya to the United States in liquid nitrogen dry shippers, collagenase digested into single cell suspensions, and sorted on a FACS aria to enrich for a population of live, CD45+ cells. Sorted samples (N=17 with BV and N=13 without BV) were immediately lysed and processed using the Takara SMART-Seq v4 Ultra Low Input RNA Kit for sequencing. Library generation was completed using the manufacturer's instructions and sequencing performed on an Illumina NextSeq500 platform using Illumina NextSeq 500/550 High Output v2.5 (150 Cycles). The FASTQ files generated and BV status (N=9 with BV and N=12 without BV that passed quality control) of the donor sample will be available on dbGaP. We identified over 1000 differentially expressed genes between women with versus without BV at an adjusted p-value of <0.05 (listed under "gene names" below).

  Study phs002329

• Neoadjuvant atezolizumab plus chemotherapy in gastric and gastroesophageal junction adenocarcinoma: the phase 2 PANDA trial

  Gastric and gastroesophageal junction (G/GEJ) cancers carry a poor prognosis, and despite recent advancements most patients die of their disease. While immune checkpoint blockade has become part of the standard of care for patients with metastatic G/GEJ cancers, its efficacy and impact on the tumor microenvironment in the early disease setting remain largely unknown. We hypothesized a higher efficacy of neoadjuvant immunotherapy plus chemotherapy in patients with non-metastatic G/GEJ cancer. In the phase 2 PANDA trial, patients with previously untreated resectable G/GEJ tumors (n=21) received neoadjuvant treatment with one cycle of atezolizumab monotherapy followed by 4 cycles of atezolizumab plus docetaxel, oxaliplatin and capecitabine. Treatment was well-tolerated, and all patients underwent resection without treatment-related delays, meeting the primary endpoint of safety and feasibility. Tissue was obtained at multiple time points, allowing analysis of the effects of single-agent PD-L1 blockade and the subsequent combination with chemotherapy on the tumor microenvironment. A total of 21 patients were included, of whom 20 patients underwent surgery and were evaluable for the secondary pathologic response and survival endpoints, while 19 were evaluable for exploratory translational analyses. A major pathologic response (MPR, ≤10% residual viable tumor) was observed in 14/20 (70%; 95% CI 46-88%) patients, including 9 (45%; 95% CI 23-68%) pathologic complete responses. At a median follow-up of 47 months, 13/14 responders were alive and disease-free, while 5/6 nonresponders had died due to disease recurrence. Notably, baseline PD-1+CD8+ T cell infiltration was significantly higher in responders than in nonresponders, and comparison of the tumor microenvironment alterations following anti-PD-L1 monotherapy versus the subsequent combination with chemotherapy revealed that increased immune activity was achieved upon single-agent PD-1/L1 axis blockade. Based on these data, anti-PD-L1 plus chemotherapy warrants further exploration in patients with non-metastatic G/GEJ cancer, and these results call for validation in a larger cohort.

  Study EGAS50000000168

• Kids First: Whole Genome Sequencing in Recessive Structural Brain Defects

  Almost 5% of all live births in the US (1:20 births) display an inborn defect, including both structural and functional/metabolic abnormalities. These are among the most common causes of Infant mortality in the developed world and underlie nearly half of hospitalizations in the first 3 years of life. Of the 35 major defects observable at birth from the International Clearinghouse for Birth Defects Surveillance Program (www.icbdsr.org, external link), about half involve the nervous system. Many of these result in lifelong neurodevelopmental disorders. Structural Brain Defects (SBDs) result from errors in development of the central nervous system, including defects in the forebrain, midbrain and hindbrain. Many SBDs arise as the consequence of a single gene bi-allelic mutation, and for this reason, occur more commonly in populations or communities with elevated consanguinity.Our lab has identified dozens of novel SBD genes using WES/WGS in consanguineous SBD families. Importantly, the genes that we and others have identified in these unique families are then used to advance diagnosis in pediatric SBDs around the world. We have built an enormous cohort of SBD families, including newly recruited families not yet studied genetically, and previous families that were negative for cause following WES analysis. Here we propose to collaborate with the Gabriella Miller Kids First Pediatric Research Program (X01) to have sequencing performed in individuals from a total of 200 families with genetically undiagnosed SBDs. The Gleeson Lab team of researchers is dedicated to the field of SBDs, with an outstanding track record of high-impact science, and a collaborative approach to discovery. We have 150 newly recruited families that we propose to study by WES by sequencing blood-derived DNA from two affected patients, or the parents and one affected patient. We also have 50 families in which WES was negative, which we propose to study in a multi-omics approach combining WGS from blood-derived DNA. We anticipate that this study will lead to the identification of many new molecular causes of SBDs, as well as uncover new genotype-phenotype correlations and new disease mechanisms, paving the way for future breakthroughs in detection, treatment and prevention.

  Study phs002590

• Gabriella Miller Kids First Pediatric Research Program in Pediatric T-Cell Acute Lymphoblastic Leukemia

  The outcome for patients with relapsed T-ALL is dismal with 3-year event free survival of AALL0434 was a Children's Oncology Group-initiated phase 3 randomized clinical trial comparing Capizzi-style escalating methotrexate plus pegaspargase (CMTX) vs. high dose methotrexate (HDMTX), with/without six 5-day courses of nelarabine. Survival on this study was superior to any prior trial for de novo T-ALL, changing the standard of care. Yet, a substantial minority (~15%) of patients had relapsed or refractory (r/r) disease. Through the TARGET initiative, RNA sequencing (RNA-Seq), DNA copy number analysis, and whole-exome sequencing (WES) were performed on 264 T-ALL patients treated on AALL0434, demonstrating recurrent alterations could be grouped into 10 different potentially targetable functional pathways. This analysis was not powered to examine associations between genetic lesions with outcome, because too few patients with r/r disease were included. This project is dedicated to testing the hypothesis that comprehensive genomic profiling of the entire AALL0434 cohort will identify recurrent genetic alterations that can be segregated into biologically relevant deregulated pathways that can be combined with MRD to identify patients at risk for poor outcomes before they relapse and provide rationale for treatment with alternative therapies. In addition, a number of small recent studies demonstrated that many of the biologically relevant alterations in T-ALL occur in non-coding regions of the genome, but no large studies have performed whole genome sequencing (WGS) in T-ALL. This project also tests the hypothesis that WGS of a large cohort of patients with T-ALL will identify novel lesions in coding and non-coding regions that will be highly impactful in the understanding of T-ALL pathogenesis.These hypotheses are tested by performing comprehensive genomic profiling (WGS, WES, RNA-Seq, and copy number analysis) of the entire AALL0434 cohort with available samples with the following specific aims: (1) identify recurrent genetic alterations that predict poor outcome in T-ALL; (2) identify novel alterations, including non-coding alterations in T-ALL; and (3) identify germline genetic variants that predispose to T-ALL and to increased toxicity to chemotherapy.

  Study phs002276

• Psychophysiological Investigation of Myocardial Ischemia (PIMI-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To investigate psychophysiological factors related to both symptomatic and asymptomatic cardiac ischemia.Background: An important hypothesis has been generated from current research in this area: manifestations and expressions of cardiac ischemia are influenced by specified psychophysiological mechanisms.Participants: The study population consisted of 196 participants recruited from four clinical units, all of which were clinical units for the Asymptomatic Cardiac Ischemia Pilot (ACIP). Participants eligible for PIMI were identified throughout the screening process established for the enrollment of participants in ACIP.Design: The primary goal of PIMI was to test the hypothesis, "Manifestations and expressions of cardiac ischemia are influenced by specific psychophysiological mechanisms." The specific relationships investigated were:Patients who are susceptible to mental stress ischemia (indexed by new left ventricular wall motion abnormalities) would display more ischemia during daily activities and would have ambulatory ischemia at lower heart rate and activity level thresholds than patients who are not susceptible. Cardiovascular and catecholamine reactivity to mental stress would be a predictive of severity of mental stress ischemia and of ambulatory ischemia. &#914;-edorphin responses to mental stress and to exercise would be predictive of asymptomatic ischemia. Patients with systematic ischemia and those with asymptomatic ischemia would show differences in each of the following at rest and after response to stresses (exercise and/or mental tests). Mental stress would produce different hormonal and perceptual responses than exercise. Asymptomatic ischemia would be associated with a lesser severity of ischemia than symptomatic ischemia. The location of the ischemic myocardium would be inferior in a higher proportion of patients with asymptomatic ischemia than of patients with symptomatic ischemia. The latency internal that would be the onset of ST segment depression and the onset of ischemic pain would be related to somatic sensory perception, autonomic nervous system reflux control of the heart, &#914;-endorphin responses, and psychosocial characteristics.

  Study phs004183

• UK10K NEURO IOP COLLIER

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Genetics and Psychosis (GAP) set consists of samples from subjects with schizophrenia, ascertained as a new-onset sample. This set is of UK origin, with data on cognition, brain imaging and other endophenotypes. The Maudsley twin series consists of probands ascertained from the Maudsley Twin Register, defined as patients of multiple birth who had suffered psychotic symptoms. This set is of UK origin, with data on cognition, brain imaging and other endophenotypes, with DNA available from an MZ or DZ affected or unaffected co-twin. The Maudsley family study (MFS) consists of over 250 families who have a history of schizophrenia or bipolar disorder Within the Maudsley Family Study, biological markers of psychosis include neuropsychological tests, Evoked Response Potentials Tests (ERPs), MRI scans, dermatoglyphics and eye tracking. Early risk factors for psychosis and clinical symptoms are also investigated. This set is of UK origin, with DNA available from both affected and unaffected relatives in many of the probands. For further information on this study please contact David Collier (david.collier@kcl.ac.uk).

  Study EGAS00001000121

• HIV exome pilot, exome data part 2 GRCh37_53

  exome sequence data for 25 HIV elite long term non-progressors and rapid progressors. Partial dataset (overlap with EGAD00001000047) of raw BAMs mapped to GRCh37_53.

  Dataset EGAD00001000087

• Oncotrack_450K_metastatic

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

  Dataset EGAD00010001161

• iPSC Samples for EBiSC

  EBiSC Whole Genome Sequencing raw FASTQ

  Dataset EGAD00001003882

• iPSC alignment file (CRAM) for EBiSC

  EBiSC Whole Genome Sequencing processed CRAM

  Dataset EGAD00001003942

• WTCCC2 bacteraemia susceptibility replication samples

  A WTCCC2 project - replication study for bacteraemia susceptibility in 2518 individuals from Kenya, genotyped on the Illumina Immunochip chip.

  Dataset EGAD00010001509

• GCAT| SNParray coreSpain V1

  4988 samples issued from GCAT cohort, genotyped with MEGAex-Infinium Array, with data for Cr1-22. Plink files with QC but not imputed.

  Dataset EGAD00010001665

• GCAT| SNParray coreSpain V2

  4988 samples issued from GCAT cohort, genotyped with MEGAex-Infinium Array, with data for Cr1-22. Plink files with QC and imputed (SHAPEIT+IMPUTE).

  Dataset EGAD00010001664

• Richter Syndrome Methylation dataset

  Raw idat files for 90 RS + DLBCL + CLL samples.

  Dataset EGAD00010002194

• P50_P76_P763_DAC_DMSO_24h_48h_72h_Illumina_HT12v4_Gene_Expression.xlsx

  Expression dataset for DAC treated CD34 sorted primary CML bone marrow samples

  Dataset EGAD00010002211

• DNA-Methylation data for atypical teratoid/rhabdoid tumoroids study

  We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles

  Dataset EGAD00010002400

• Hostage_2_genotype

  Cohort: Raw genotype files for Hostage2 cohort. Genotype Chip: Illumina’s (Illumina Inc., San Diego, U.S.) Global Screening Array-24 Multi Disease (GSA) Version 2.0 B1 genomic build: b37

  Dataset EGAD00010002171

• Hostage_3_genotype

  Cohort: Raw genotype files for Hostage3 cohort. Genotype Chip: Illumina’s (Illumina Inc., San Diego, U.S.) Global Screening Array-24 Multi Disease (GSA) Version 2.0 B1 genomic build: b37

  Dataset EGAD00010002173

• Hostage_4_genotype

  Cohort: Raw genotype files for Hostage4 cohort. Genotype Chip: Illumina’s (Illumina Inc., San Diego, U.S.) Global Screening Array-24 Multi Disease (GSA) Version 2.0 B1 genomic build: b37

  Dataset EGAD00010002178

• Hostage_1_genotype

  Cohort: Raw genotype files for Hostage1 cohort. Genotype Chip: Illumina’s (Illumina Inc., San Diego, U.S.) Global Screening Array-24 Multi Disease (GSA) Version 2.0 B1 genomic build: b37

  Dataset EGAD00010002180

• OncoScan SNP data set for systemic follicular lymphoma (sFL)

  122 unpaired initial tumor samples (122 FFPE samples) of sFL patients measured with OncoScan SNP microarrays, Affymetrix CEL intensity data file types (Thermo Fisher Scientific, Waltham, Massachusetts, USA)

  Dataset EGAD00010002592

• T and NK cell PBMC metadata

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

  Dataset EGAD50000000140

• WGS and WXS for mismatch repair-deficient human colon organoids

  Whole genome/exome sequencing to detect spontaneous acquired mutations in mismatch repair-deficient human colon organoids.

  Dataset EGAD50000000159

• Genotyping data of 81 patients with multiple sclerosis and other neurological diseases

  This dataset consists of raw unimputed genotype data for 81 individuals with multiple sclerosis (n=33) and other neurological disease (n=48).

  Dataset EGAD50000000183

• GSA reference

  reference whole exome sequence serving as a reference of individuals. Includes the raw GSa files and the called variants in vcf format merge for all individuals (S1-S5).

  Dataset EGAD50000000481

• bfast CohortD OAPL

  ctDNA mutation calls (one mutation per sample per line) for BFAST Cohort D including mutation-level data like coding change, allele frequency, etc.

  Dataset EGAD50000000148

• Dataset for NSCLC samples

  This dataset contains 10x scRNA sequencing data of 16 NSCLC samples. Sequencing was performed on Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD50000000185

• Reconstruction oral cavity tumor evolution through brush biopsy

  A dataset of samples analyzed for the publication "Reconstructing oral cavity tumor evolution through brush biopsy", Springer Nature, DOI: 10.1038/s41598-024-72946-3

  Dataset EGAD50000000856

• RNAseq data

  Bulk RNAseq data for IMbrave151 (N = 96), including raw counts, transcript per million (TPM), and voom transformed values.

  Dataset EGAD50000000568

• Altered Blood and Keratinocyte microRNA/transfer RNA Fragment Profiles Related to Fibromyalgia Syndrome and its Severity

  We show dysregulated microRNA and tRNA fragment profiles related to FMS pathopyhsiology and opening new perspectives for FMS diagnostics and symptom monitoring.

  Dac EGAC50000000247

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_003 for Diffuse large B-cell lymphoma patient sample TFRIPAIR10

  Dataset EGAD50000001372

• ctDNA sample level analysis

  This table summarizes Guardant 360 ctDNA variant summary statistics including frequency of variant types for each sample included in this analysis.

  Dataset EGAD50000001341

• Raw RNA sequencing of hepatoblastoma PDX cell line HB-303-LEF

  This dataset contains raw RNA sequencing data for hepatoblastoma PDX cell line HB-303-LEF

  Dataset EGAD50000001358

• Sequencing data for oesophageal and related samples - cell-lines (WGS)

  Dataset EGAD00001015467

• Policy to access RNAseq Patient Derived Sézary syndrome cells

  This is the policy for accessing the RNAseq raw data associated to the project 'Diverse transcriptomic and mutational patterns but limited functional pathway alterations in patient-derived SS cells'

  Dac EGAC50000000693

• McGill Reproductive Genetics Data Access Committee

  Committee at RI-MUHC (Slim Lab) that reviews requests for controlled human genetic/phenotypic data generated in reproductive genetics/infertility studies. Ensures requests comply with participant consent, ethics approvals, and institutional policies.

  Dac EGAC50000000775

• CRC and UC WES samples

  This is the dataset used to produce results for the report "NOUS-209 off-the-shelf immunotherapy has the potential to hit primary and metachronous colorectal and urothelial cancer in Lynch syndrome"

  Dac EGAC50000000782

• NICOLA Epigenetic Data Wave 1 - Beta values

  Beta values generated from Illumina EPIC methylation array data for a subset of NICOLA Wave 1 samples.

  Dataset EGAD50000001965

• Transcriptomics for UPST-SCCHN3 cohort

  Transcriptomics of Tumor samples on UPST-SCCHN3 cohort

  Dataset EGAD50000002179

• ATAC_TALL_t_14_16_translocation

  ATAC-sequence for patients with t(14;16) translocated T-ALL and control T-ALL patients

  Dataset EGAD50000001784

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_001 for Follicular lymphoma patient sample TFRIPAIR4_FL

  Dataset EGAD00001010217

• NICHE - DNA-seq of MMR proficient and MMR deficient early stage colon cancers

  The dataset includes 174 FASTQ files from paired-end WXS sequencing on Illumina HiSeq2500 for 39 patients.

  Dataset EGAD00001006041

• HV31 - MGI standard short-read sequencing

  MGI standard short-read sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~57×.

  Dataset EGAD00001007044

• Identifying new diagnostic and treatment pathways for patients with unclassifiable sarcomas

  Whole genome sequencing of tumour normal pairs of human undifferentiated sarcomas.

  Dataset EGAD00001003216

• Colon cancer ctDNA

  Samples prepared using Safe-SeqS technology. All samples ran on an Illumina MiSeq instrument. Fastq files for read 1 and the index read present (R and I respectively).

  Dataset EGAD00001003579

• CBD-RAW-CLINVAR: Clinical metadata

  Anonymised patient metadata and associated data dictionary. For further information regarding this dataset, please contact Alexander Mentzer at contact@combat.ox.ac.uk.

  Dataset EGAD00001007931

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_001A for Follicular lymphoma patient sample TFRIPAIR8_FL

  Dataset EGAD00001010220

• TGS - Comprehensive Molecular Characterization of Colorectal Cancer Metastases [MOSAIC] (2017-05-04)

  This dataset contains all the data available for this study on 2017-05-04.

  Dataset EGAD00001003321

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_003 for Follicular lymphoma patient sample TFRI_Cont_3

  Dataset EGAD00001010205

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0172_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0172_001 for Triple negative breast cancer sample SA609X6XB03447

  Dataset EGAD00001011217

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0163_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0163_002 for Triple negative breast cancer sample SA609X7XB03510

  Dataset EGAD00001011218

• 10x Single Cell Gene Expression Library TENX048

  10x Single Cell Gene Expression library TENX048 for Triple negative breast cancer sample SA535X5XB02895

  Dataset EGAD00001011222

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0184_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0184_001 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011227

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_004 for Triple negative breast cancer sample SA535X7XB03305

  Dataset EGAD00001011228

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0206_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0206_001 for Triple negative breast cancer sample SA535X10XB03693

  Dataset EGAD00001011236

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0076_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0076_000 for Triple negative breast cancer sample SA1035X5XB03021

  Dataset EGAD00001011240