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• Count Me In (CMI): The Metastatic Prostate Cancer (MPC) Project (CMI-MPCproject)

  Count Me In - The Metastatic Prostate Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Prostate Cancer Research The Metastatic Prostate Cancer Project (MPCproject; http://mpcproject.org/) is a research study that empowers men with metastatic and advanced prostate cancer to partner directly with researchers by sharing their samples and clinical information, with the ultimate goal of accelerating scientific discoveries that have clinical impact. The MPCproject enables any man with metastatic or advanced prostate cancer in the US and Canada to participate in cutting-edge genomic and molecular research, regardless of where they live. Metastatic or advanced prostate cancer patients visit the project website and complete an online questionnaire of basic information about themselves and their cancer. Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA, and transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided with updates on the study.

  Study phs001939

• UK_RCC_GWAS

  Renal cell carcinoma (RCC) cases comprised adult patients with histologically proven RCC were collected through two sources within the UK. First, 856 cases from SORCE, a MRC collection of surgically treated RCC cases ascertained through UK clinical oncology centres. Second, 189 RCC cases collected through the ICR and Royal Marsden NHS Hospitals Trust. Cases included 590 clear cell carcinomas (CCCs), 42 papillary carcinomas (PCs), 33 chromophobe carcinomas (CCs) and 19 mixed or other histological subtypes. DNA was extracted from EDTA-venous blood samples using the conventional methods and quantified using PicoGreen (Invitrogen). Cases were genotyped using the Human OmniExpress-12 BeadChip according to the manufacturer's recommendations (Illumina Inc, San Diego, CA, USA). After strict QC, 944 cases were retained. Data provided in plink format. Controls used were data from the Wellcome Trust Case Control Consortium 2 (WTCCC2) 1958 birth cohort and the UK Blood Service Control Group (available as EGAS00000000028). 

  Dataset EGAD00010002310

• Bulk RNA sequencing data of high-grade serous ovarian cancer samples (set 7-17)

  The dataset contains RNA sequencing data of 272 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000, MGISEQ or Hiseq X Ten. The 814 samples are fresh frozen tissue samples that have been collected from different tissues and time points before and during treatment. The files provided are paired fastq files.

  Dataset EGAD50000001370

• Cell types of the human retina and its organoids at single-cell resolution. Cowan et al

  Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers, and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas.

  Dataset EGAD00001006350

• Genetic vulnerability of knockout cancer lines (2019-04-01)

  Genome-wide CRISPR/Cas9 library screen was performed in isogenic cell lines. Three biological replicates were used. Cells were harvested at initiation of screen and at specific time points following cell culture. Using this approach we aim to identify genes specifically important in cell survival in engineered cell lines. Please perform 72, instead of 36, PCR reactions as the screen performed at 200x coverage. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004881

• Single cell transcriptomics of hESC-derived midbrain dopaminergic neurons generated by a new human development-based protocol

  Single cell RNA-seq from D0,D11,D16,D21,D28 of dopamingeric differentiation from hESCs cell lines H9 and HS980 using current protocols. Different time points along the differentiation for each cell line were multiplexed using BD™ Single-Cell Multiplexing Kit for use with the 10x Chromium™ Single Cell 3’ Reagent Kit v2.

  Dataset EGAD00001008834

• miRNA data for aSAH patients with or without subsequent vasospasm

  These files contain the normalized and raw count abundances miRNA for aSAH patients. These abundances were obtained using Next-Generation Sequencing after selection of the miRNA in the RNA biobank. In total, there are 28 VSP- and 28 VSP+ patients for two-time points. Normalized data were obtained by applying size factor and VSN normalizations as described in Pulcrano-Nicolas et al. Stroke 2018. Raw count data corresponding to the raw abundances of miRNA in aSAH patients.

  Dataset EGAD00001004185

• COVID-19 Challenge Project Single Cell Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection.

  Dataset EGAD00001012227

• Whole exome sequencing (WES) of EBV- primary central nervous system lymphoma (PCNSL)

  This dataset contains whole exome sequencing (WES) of 29 HIV- EBV- primary central nervous system lymphoma (PCNSL) tumors and 5 activated B-cell-like PCNSL (ABC-PCNSL) and activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL) cell lines (TK, HKBML, OCI-Ly3, HBL-1, TMD-8). Cases with secondary involvement of the CNS were excluded. DNA was extracted with AllPrep DNA/RNA FFPE kit and libraries were prepared using the Agilent SureSelect Human All Exon v6 + UTR kit. Paired end reads were aligned to GRCh37 using bwa mem v.0.7.17, and reads were sorted and duplicated were marked in the final BAM files. Access to this data is controlled. There are a number of steps that a researcher must take to obtain access to this data, including execution of a Data Access Agreement between the institutions. The process is overseen by the Technology Development Office; please contact our general email address TDOadmin@phsa.ca. Please only click the "request data" button on the EGA website after a Data Access Agreement is fully executed.

  Dataset EGAD50000000451

• Whole Exome and Whole Genome Profiling as well Genome-Wide Methylation Profiling from Early to Advanced Chronic Lymphocytic leukemia (CLL), Genome-Wide Methylation Profiling in Monoclonal B Cell Lymphocytosis (MBL)

  Serial whole exome sequencing of samples collected from 21 patients at multiple time points during progression from early to late chronic lymphocytic leukemia (CLL) and one matching non-tumor tissue sample from each patient. Additional whole genome sequencing of samples from 3 selected patients. Genome-wide B cell methylation compared between 5 healthy donors from the same age group as patients, 20 patients with monoclonal B cell lymphocytosis and in serial CLL samples with matching whole exome sequencing. Moreover, genome-wide single-cell RRBS-profiling of B cells from one healthy donor and from one patient with CLL was performed using a protocol newly developed by the A. Meissner group.

  Study phs001431

• NGS-based monitoring of the T cell receptor repertoire in living donor kidney transplant patients undergoing combination cell therapy

  Tolerance induction through mixed chimerism is a promising approach to achieve long term graft patency without or only low dose maintenance immunosuppression. In this phase I/IIa academic trial kidney transplant recipients in the case group were co-transplanted with bone marrow from the same donor and received an autologous cell product. The control group did not receive donor bone marrow or an autologous cell product. Peripheral blood mononuclear cells were collected at multiple timepoints before and after transplantation and the recipients native T-cell receptor (TCR) repertoire at time points 0, 1, 3 and 6 months after transplantation as well as their donor reactive TCR repertoire were analysed using NGS-based TCR sequencing.

  Study EGAS50000000210

• Temporal stability of circulating microRNAs in human serum

  Circulating microRNA biomarkers for disease have been subject to extensive research. However, insufficient consideration of variability in the healthy population has led to few markers achieving the performance necessary in independent follow-up studies to be taken forward to clinical practice. To investigate the natural variation of circulating microRNA over time, we performed small RNA sequencing in a longitudinal study of 66 women with no history of cancer, and determined the distribution and dynamics (via intraclass correlation coefficients, ICCs) of the miRNA profile over 3 time points sampled across 2-5 years. We also investigate abundances in circulation, as well as the impact of normalization, age, BMI, and other sample collection factors on microRNA measurements from small RNA sequencing.

  Study EGAS00001003221

• Spatial heterogeneity of follicular lymphoma

  Follicular lymphoma (FL) is an incurable B cell malignancy characterized by advanced stage disease and a heterogeneous clinical course. Recent genomic studies have focused on profiling “single” FL biopsies over several time-points, however, multi-site sampling in solid cancers has demonstrated profound spatial intra-tumor heterogeneity (ITH) with implications for precision medicine based initiatives. This study examined the extent of spatial heterogeneity in FL by whole exome sequencing 22 synchronously removed spatially separated biopsies from 9 patients. We observed significant differences in the extent of ITH across cases, with two distinct patterns of high and low spatial heterogeneity emerging. Site-specific alterations in genes with biological, prognostic or therapeutic relevance included, TNFRSF14, PIK3CD, TNFAIP3, PTEN, EP300 and XBP1. In depth characterization of these variants using deep-sequencing techniques confirmed their discordant nature, suggesting on-going genetic diversification driving evolution after widespread tumor dissemination. There was evidence of tumors comprising multiple competing subclones, with distinct clusters of mutations demonstrating differential expansions within spatially-separated sites. For cases where spatial tumors were examined at two time-points (FL and transformation to diffuse large B cell lymphoma (DLBCL)), the degree of heterogeneity increased with transformation. Collectively, our results demonstrate that spatial ITH is prevalent in FL. The existence of site-specific aberrations suggests that a single biopsy may not be sufficient in all patients to capture the full genomic complexity present and these spatial variations need to be considered in biomarker-led clinical studies.

  Dataset EGAD00001003553

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• Oncogenic fate conversion by PRDM16s causes acute myeloid leukemia

  Oncogenic mutations confer aberrant replicative capacity to cells with little or no replicative capacity, generating cancer stem cells that perpetuate the tumor through extensive self-replication and differentiation blockade. However, whether oncogenes disrupt the cellular identity ofcancer stem cell by altering the developmental potential is unknown. Fate conversion has been demonstrated by ectopic expression of master transcriptional regulators, such as PU.1 and C/EBP alpha that confers myeloid cell fate to other cell types, and PRDM16 that confers brown adipose fate to white adipocytes or myoblasts. Here we show that a transcriptional regulator overexpressed in human myeloid malignancies, PRDM16s, causes oncogenic fate conversion, by transforming cells fated to form platelets and erythrocytes into myeloid leukemia-initiating cells (LICs). Prdm16s expression in hematopoietic progenitor cells caused a myelodysplastic syndrome (MDS)-like disease that progressed to acute myelogenous leukemia (AML). The myeloid diseases caused by Prdm16s exhibited expansion of megakaryocyte-erythroid progenitors (MEPs) but not granulocyte-macrophage progenitors. MEPs from Prdm16s-induced leukemia possessed LIC potential, and expression of Prdm16s in normal MEPs was sufficient to convert them to myeloid LICs and blocked megakaryocytic/erythroid potential. Prdm16s induced the expression of myeloid master regulators, including PU.1 and C/EBP alpha, by interacting with their super enhancers. Ablation of myeloid master regulators attenuated the myeloid potential and reinstalled the megakaryocytic/erythroid potential of leukemic-MEPs in mouse models and in human AML with PRDM16 rearrangement. Our study demonstrates that oncogenic Prdm16 expression converts the fate of MEPs to a malignant myeloid fate by activating myeloid master transcription factors.

  Study EGAS00001003235

• The evolutionary steps from primary to metastatic prostate cancer are largely uncharted, and the ability to use DNA present in body fluids as correlates of aggregate metastatic status is under-examined. We reconstructed phylogenies in ten prostate cancer patients with fatal disease using deep targeted sequencing of the prostate, adjacent and distant organs, as well as plasma, serum, and cerebrospinal fluid at various time points. A total of 163 samples are studied.

  The evolutionary steps from primary tumor to metastasis in prostate cancer are largely uncharted, and the ability to use serum, plasma, and cerebrospinal fluid as a correlate of aggregate metastatic tumor genomic status has not been tested. We used deep targeted sequencing to reconstruct tumor evolution in ten prostate cancer patients with fatal disease encompassing examination of the prostate and adjacent and distant organs, as well as plasma, serum, and cerebrospinal fluid at various time points. We show that there is substantial evolution from a common ancestor within the prostate that results in branching to multiple lineages which form an intermixed multi-clonal primary tumor mass. After the occurrence of key driver aberrations, one of these lineages will metastasize to multiple sites in a sequential fashion. These metastatic sites are then susceptible to being populated by cells from other intra-prostatic lineages or from other metastases. Genomic representation of metastases in body fluids is not uniform. Cerebrospinal fluid analysis can detect lineages not detected in circulating DNA, suggesting possible clinical utility.

  Study EGAS00001003848

• Impact of allogeneic umbilical-cord derived mesenchymal stromal cells on B-cell scRNAseq in patients with systemic lupus erythematosus

  The impact of MSC(UC) on peripheral B cells from Systemic Lupus Erythematosus (SLE) patients was studied by 10X scRNAseq. This scRNAseq study encompassed 3 SLE patients at 3 time points: before or after (1 month, and 3 months) MSC injection in order to analyze B cell subsets and their DEG. The aim of this study was to observe the potential changes of B cell subsets after MSC(UC) injection in SLE patients.

  Dataset EGAD50000000471

• Targeted gene panel sequencing of matched diagnosis-remission-relapse B cell precursor acute lymphoblastic leukemia samples

  Bone marrow mononuclear cells from patients diagnosed with B cell precursor acute lymphoblastic leukemia were obtained at three sequential time points: first diagnosis, remission after chemotherapy and relapse. Genomic DNA was isolated and targeted gene panel sequencing was performed using a customized biotinylated RNA oligo pool (SureSelect, Agilent, Santa Clara, California) to hybridize the target regions comprising 362 kbp on a HiSeq2000. Target regions were selected to validate mutations previously identified in these samples using whole exome sequencing.

  Dataset EGAD00001004977

• FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

  28 patients. Cell-free DNA and leukocyte DNA, both from before any neoadjuvant treatment. Tumor FFPE tissue (plus metastasic tissue for some patients) from after any neoadjuvant treatment. Some cfDNA from follow-up time points (e.g. after neodj. treatment or in the clinical course). IDT xgen Pan-Cancer panel for hybridisation capture. Illumina TruSeq library prep for cfDNA and leukocyte DNA, Illumina DNA Prep for FFPE DNA. n=150 libraries in total.

  Dataset EGAD00001010081

• Whole genome sequencing of tumor samples from advanced pre-treated NSCLC patients recruited in a phase I/II single-arm trial utilising CVA21, an oncolytic coxsackie virus, in combination with pembrolizumab.

  This dataset contains paired tumor and matched normal whole-genome sequencing (WGS) data from longitudinally collected samples of patients enrolled in an Australian clinical study involving multiple cancer types. For each patient, one or more tumor biopsies were obtained at different treatment time points (Scr, Day 0, Day 15, Day 22, Day 33), and matched normal samples were collected either from blood or non-tumor tissue.

  Dataset EGAD00001015682

• GEnetics of Nephropathy - an International Effort (GENIE) GWAS of Diabetic Nephropathy in the UK GoKinD and All-Ireland Cohorts

  Diabetic kidney disease, or diabetic nephropathy (DN), is one of the leading causes of end-stage renal disease in the United States and worldwide. DN is a common complication of long-standing type 1 and type 2 diabetes. The clinical course is characterized by development of proteinuria and gradual loss of kidney function. Although existing treatments that decrease proteinuria have been shown to moderately abate progression of diabetic kidney disease, many affected patients, who do not die from cardiovascular disease, go on to develop terminal renal failure, necessitating costly renal replacement therapies, such as dialysis and renal transplantation. Type 1 diabetes (T1D) can have its onset in childhood and affected individuals often develop end-stage renal disease in early adulthood, leading to further loss of quality of life. The genetic basis of the disease is not well understood. The GENIE (GEnetics of Nephropathy an International Effort) consortium was initiated to perform the most comprehensive and well powered DN susceptibility genome wide association study (GWAS) analysis to date, using the largest collection of type 1 diabetics with and without kidney disease across four study cohorts. The UK-ROI samples were genotyped as part of this project. UK-ROI Sample Description The UK-ROI collection consists of samples derived from the Republic of Ireland (Dr. Catherine Godson, PI, at University College, Dublin, Ireland) and the United Kingdom (Warren 3 and Genetics of Kidneys in Diabetes UK, UK GoKinD, Dr. Alexander P. Maxwell, PI, at Queen's University of Belfast, UK). All study subjects met the inclusion criteria: white individuals with T1D, diagnosed before 31 years of age, whose parents and grandparents were born in the British Isles.

  Study phs000389

• Everything you need to know about Federated EGA Affiliates: Q&A

  Addressing common questions about Federated EGA (FEGA) Affiliates and providing answers. FEGA Affiliates have recently been defined as the third tier within the newly approved “Federated EGA Structure and Organisation” document, alongside Central EGA (CEGA) and the FEGA Nodes. In this blog post, we aim to answer the questions that may arise on this topic. For more general information about FEGA Affiliates, you can refer to this blog post. Let's now start with the questions and answers! What is the difference between a FEGA Affiliate and a FEGA Node? FEGA Nodes A FEGA Node is a national-level service that accepts submissions and provides archiving and access services within a single country's jurisdiction. Nodes provide end-to-end services for submitters in that jurisdiction, including submission support, processing, permissions management, and distribution. FEGA Affiliates A FEGA Affiliate is not a national submission service. Instead, it archives data from its own legal entity and/or selected partner institutions (for example, consortium partners). Affiliates are designed for organisations and consortia that need to keep data stewardship and access decisions within their own governance model, while still enabling discovery through the broader FEGA ecosystem. What do Affiliates commit to? Here is a practical checklist of the core expectations for a FEGA Affiliate. FEGA Affiliate checklist Discovery and metadata Submit non-personal metadata to CEGA to obtain EGA accessions and enable discovery (with metadata validation handled by the CEGA Helpdesk). Operations and resilience Maintain a data storage system and a defined backup/recovery approach. Ensure operational capacity (personnel and infrastructure) to deliver Affiliate services. Maintain systems and practices that support local data security and align with EGA best-practices. Access and user support Provide data distribution or access (e.g in a trusted research environment) to authorised users to datasets hosted at the Affiliate. Provide permissions management for datasets archived by the Affiliate (the CEGA DAC (Data Access Committee) Portal is always at your disposal to use). Provide a minimal helpdesk with sufficient capacity to support relevant DACs and approved users. Membership term Commit to a minimum membership term of four years. Governance and participation (lightweight by design) Affiliates integrate into the FEGA network operationally, but without the committee obligations associated with Nodes. When is becoming an Affiliate the right fit? Consider the Affiliate tier if: You host (or plan to host) controlled-access datasets that must be managed under your organisation’s or consortium’s governance, you want studies to be discoverable through EGA, but need access control and/or distribution to remain local, and you are not aiming to operate a national submission service tier.. What if a FEGA Node already exists in my jurisdiction? We encourage any potential Affiliate to reach out to their national FEGA Node to explore collaboration at the national level. Why? Federated models within a country already exist in FEGA, where a national Node operates like a Central EGA for their country. FEGA Nodes can also represent the interests of any Affiliates within their jurisdiction at the FEGA Committees. FEGA Nodes have experience and can support you on your FEGA journey. Ready to join as a FEGA Affiliate? We’re excited to open this formally defined pathway for organisations and consortia to participate in the federation. If you think the FEGA Affiliate tier fits your needs, start by assessing: Your scope (organisation/consortium-held data rather than public external submissions), Your ability to provide the core services (permissions, distribution/access, helpdesk, monitoring), and Your readiness to submit non-personal metadata to CEGA for accessioning and discovery. To express interest, please contact us here, and we'll help you understand the onboarding steps and how Affiliates integrate into the FEGA network.

  Blog fega-affiliates-q&a

• Targeted bisulfite sequencing

  Raw reads from targeted bisulfite sequencing. The SureSelect Methyl-Seq target enrichment system (Agilent Technologies, Inc., CA, USA) was used to prepare bisulfite sequencing libraries from blood DNA samples of lymphoma patients (Ly1, Ly2), healthy family members (Ly8, Ly9, Ly10, Ly11, Ly12, Ly13 and Ly14), baseline controls (Control1-5), DNMT3A mutation carriers (Id5, Id7, Id9, Id11) and their age-matched controls (Id6, Id8, Id10, Id12). In addition, blood DNA sample of a patient (HLRCC_N7) with germline fumarate hydratase (FH) mutation is included. Illumina paired-end sequencing for targeted libraries from Ly1, Ly2, Ly8, Ly9, Ly10 and Ly11 was done at Karolinska Institutet using 100 base-pair read length and the HiSeq2000 platform. Illumina paired-end sequencing for targeted libraries from Ly12, Ly13, Ly14, and DNMT3A mutation carriers and their age-matched controls was done as a service at BGI (BGI Tech Solutions Co., Ltd., China) using 126 base-pair read length and the HiSeq2500 platform.

  Dataset EGAD00001004785

• Deep exome sequencing

  Bam files from deep exome sequencing of blood DNA samples from five TET2 mutation carriers (Ly1, Ly2, Ly9, Ly11, Ly14) and three wild-type family members (Ly8, Ly10, Ly13) extracted at multiple time points. Library preparations were performed with SeqCap EZ Exome v3 (Roche, Switzerland) using six different index primers per sample for which paired-end Illumina sequencing was done with 75bp read length and HiSeq4000 sequencer. After alignment (bwa version 0.7.12), base recalibration (GATK 3.5), realignment around indels (GATK 3.5) and duplicate removal (MarkDuplicates; Picard Tools version 1.79), data from libraries with six different indexes were merged.

  Dataset EGAD00001004780

• Mannheim Liquid Biopsy Unit, Heidelberg University & DKFZ

  The dataset consists of sequenced cell free DNA (cfDNA) samples from colorectal cancer patients. The samples were sequenced on an Illumina MiSeq machine using a custom amplicon sequencing approach. These amplicons were designed to cover the most common mutation hotspots in colorectal cancer. The data include 138 cfDNA samples from 34 different patients. For each patient several samples are available derived from blood drawn at different time points during treatment. In addition the data include samples from 22 histology slides and 30 samples derived from HT29/HCT116 cell lines that were used as controls.

  Dataset EGAD00001004574

• Longitudinal profiling of circulating tumour DNA for tracking tumour dynamics in pancreatic cancer

  Whole genome sequencing from two resectable patients with pancreatic cancer for both normal and tumour tissue samples; whole exome sequencing from the two resectable patients and five unresectable patients of peripheral blood mononuclear cells and blood plasma (1-5 time points per patient), and whole exome sequencing of plasma samples from three chronic pancreatitis patients.

  Dataset EGAD00001008593

• single cell RNA sequencing of resting and IAV-stimulated mononuclear phagocytes of Africans and Europeans

  CD14+ monocytes from 4 African and 4 Europeans individuals with varying degree of ex-vivo susceptibility to Influenza, were either stimulated with Influenza A virus, or left resting. Cells from all 16 samples were collected at 4 time points (0, 2, 4, 6h post infection), and pooled across 13 libraries. Samples were processed on the 10x chromium with 3' reagents kits, V3 chemistry and sequenced with Hiseq X ten.

  Dataset EGAD00001006938

• Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

  Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

  Study EGAS50000000470

• Mutational patterns and regulatory networks in epigenetic subgroups of meningioma (H033)

  DNA methylation patterns delineate clinically relevant subgroups of meningioma. We previously established the six meningioma methylation classes (MC) benign-1, 2, 3, intermediate-A, B and malignant. Here, we set out to identify subgroup-specific mutational patterns and pathway regulation. Whole-genome-sequencing was performed on 62 samples across all MCs and WHO grades from 62 patients with matched blood control, including 40 sporadic and 22 radiation-induced (Mrad) meningiomas. RNA sequencing was added for 18 cases and chromatin-immunoprecipitation for the enhancer mark H3K27ac followed by sequencing (ChIP-seq) for 16 samples. Besides the known mutations in meningioma, structural alterations were found to contribute to the spectrum of mechanisms inactivating NF2 in sporadic meningioma similar to previous reports for Mrad. Aberrations of DMD were found to be enriched in MCs with NF2 mutations and DMD was among the most differentially upregulated genes in NF2 mutant compared to NF2 wild-type cases. The mutational signature AC3 was detected in both sporadic meningioma and Mrad, but distributed across the genome in sporadic cases and enriched near genomic breakpoints in Mrad. In general, the malignant MC presented a significantly higher exposure to AC3 and higher genomic instability beyond the mutational load than the other MCs. Pathway analysis of the ChIP-seq clusters revealed that the FOXM1 is most differentially activated in high-grade cases, along with super enhancer recruitment near HOX genes and respective upregulation of expression. This data further elucidate the biological mechanisms differentiating meningiomas of different WHO grade and epigenetic subgroups and suggest leveraging the genomic instability as novel therapeutic targets.

  Study EGAS00001003481

• Emory University African American Vaginal, Oral, and Gut Microbiome in Pregnancy Cohort Study

  The Emory University African American Microbiome in Pregnancy Cohort Study prospectively enrolls African American women between 18-40 years of age without chronic medical conditions into a longitudinal follow-up study that involves completing microbiome sampling and data collection at two time points in pregnancy (8-14 weeks gestation and 24-30 weeks gestation). The study is investigating the role of the oral, vaginal, and gut microbiome on preterm birth and other pregnancy outcomes as well as biobehavioral factors that shape the microbiome among this socio-demographically diverse group of women. Microbiome sampling involves the oral, vaginal, and gut sites. Biobehavioral factors that are being explored for their association with microbiome composition at the three body sites include measures of sociodemographic status as well as diet and nutrition, infectious and stress exposures.

  Study phs001865

• Epigenomics of Neurocognitive Function in Breast Cancer

  This study harnessed the data and biospecimens from the Exercise Program in Cancer and Cognition (EPICC) study (parent study) that collected data on cognitive function, demographics, other symptoms and biospecimens at two time points (T1: enrollment, T2: six months later) within the context of a six-month randomized controlled trial of a moderate intensity aerobic exercise intervention. This study collected genome wide DNA methylation data from T1 and T2 and conducted epigenome-wide association-based analyses to find genes and biological pathways explaining variability in cognitive function and explaining how exercise mitigates cognitive decline. Our initial findings identified cg10331779 near CTNND2 (p-value=9.65×10-9) associated with processing speed and cg25906741 in MLIP (p-value=2.01×10-8) associated with subjectively measured cognitive function. Additionally, differentially methylated regions were identified near SLC6A11, PRKG1/CSTF2T, and FAM3B for processing speed and near PI4KB and SGCE/PEG10 for mental flexibility.

  Study phs003959

• Whole Genome Sequencing to track subclonal heterogeneity in 18 samples from 3 Chronic Lymphocytic Leukemia patients subjected to repeated cycles of therapy.

  This study took 18 samples from three patients with Chronic Lymphocytic Leukemia. The 3 CLL patients received multiple different treatments sequentially for a period of up to 7 years. Peripheral blood samples were taken at 5 specific time points during disease progression together with 1 matched buccal swab per patient. All the selected patients had unmutated IgVH status reflecting poor prognosis. However, none of the patients had complex genomic aberrations associated with aggressive disease. Peripheral blood samples and buccal smears were obtained from patients, who had given informed consent for sequential sample collection and analysis. Tumour samples were obtained before treatment, after treatment and at relapse and subjected to Ficoll separation. Lymphocyte cell purity was assessed by full blood count enumeration. Buccal smears were obtained and processed using Isohelix.

  Study EGAS00001000885

• SUM-seq data for spontaneous differentiation of iPSCs upon perturbation of GATA2, NR4A2 or SOX17

  We combined SUM-seq with arrayed CRISPR screening, modulating the expression of key lineage transcription factors (TFs) (GATA2 - mesoderm, SOX17 - endoderm, and NR4A2 - neuroectoderm) in hiPSCs via CRISPR interference (CRISPRi) or activation (CRISPRa) over a time course of spontaneous differentiation (days cultured in vitro: 0, 4, 12, and 18). This totalled to 54 samples (4 day/time points x 3 target TFs x 2-3 gRNAs per target x CRISPRi/a). Single-cell chromatin accessibility and gene expression data is provided as demultiplexed fastq files.

  Dataset EGAD50000001205

• SUM-seq data for Macrophage polarisation to M1 and M2 phenotypes experiment

  We stimulated iPSC-derived M0 macrophages with LPS and IFN-γ to induce M1 polarization or IL-4 to induce M2 polarization. To discern early and sustained responses at chromatin accessibility and gene expression levels, we collected samples at five time points along the two polarization trajectories; prior to stimulation (M0) and at 1-hour, 6-hour, 10-hour, and 24-hour intervals, each sampled in duplicates totaling 18 samples, and subjected them to SUM-seq library preparation. Sequenced files for both data modalities are provided as demultiplexed fastq files.

  Dataset EGAD50000001206

• SCANDARE HNSCC DNA targeted panel sequencing

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 232 FFPE samples at baseline from 83 HNSCC patients using DNA targeted panel sequencing, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001654

• Cell-free DNA sequencing data of healthy control, atrophic gastritis, and gastric cancer patients’ blood

  Sample cohort (n=48) is consisted of healthy, atrophic gastritis and gastric cancer patients. Some of the gastric cancer patients samples are collected at the separate time points: -1 before the operation; -2 after the operation; -3 during the control visit. For the hybridisation capture of the genes unique 15 gastric cancer-related gene panel was developed and very deep sequencing using TruSight Oncology Unique Molecular Identifier (UMI) Reagents (Illumina) was used.

  Dataset EGAD00001011153

• High-resolution testing of ctDNA dynamics predicts survival in metastatic NSCLC

  One of the great challenges of therapeutic oncology is determining who might achieve survival benefit from a particular therapy. Circulating tumor DNA (ctDNA) provides real-time assessments of patient prognosis and response to treatment using a simple blood draw. While ctDNA positivity is established as a poor prognostic factor, studies on longitudinal ctDNA dynamics have been small and non-randomized, with ctDNA assessments done at disparate time points. To address this, we performed high-sensitivity longitudinal ctDNA testing in 466 patients across 5 time points (1,954 samples total) in a randomized phase III study comparing different chemotherapy-immunotherapy combinations. We leverage machine learning to jointly model multiple ctDNA metrics to predict overall survival in a training/testing framework. _ . Treatment initiation correlated with reductions in ctDNA levels, and training of our machine learning model suggests that assessment of ctDNA dynamics at C3D1 (cycle 3 day 1) of chemo-IO treatment may be optimal to predict OS. The model performs well in the hold-back test data, enabling stratification of patients with Stable Disease (SD) into high-risk vs low-intermediate-risk (HR = 3.2 [2.0-5.3], p <0.001; median 7.1 versus 22.3 months respectively); similarly, the model stratifies patients with a Partial Response (PR) (HR =3.3 [1.7-6.4], p <0.001; median 8.8 versus 28.6 months). Importantly, the model validates well in an external cohort of patients in a different treatment setting and assayed with a different ctDNA technology, in which model predictions similarly identified high-risk patients (OS HR=3.73 [1.83-7.60], logrank p=0.00012). Simulations of clinical trial scenarios employing our ctDNA model further suggest that early ctDNA testing outperforms early radiographic imaging for predicting trial outcomes (increasing the rate of ‘True Go’ decisions by 5.2 - 22.8% depending on the drug combination). Overall, we show that measuring ctDNA dynamics during the course of therapy dramatically improves patient risk stratification, and may provide a means to differentiate between competing therapies at an early time point during clinical trials.

  Study EGAS00001006703

• Drug screening of patient-derived organoids from colorectal peritoneal metastases

  Colorectal cancer (CRC) patients with peritoneal metastases (CRPM) have limited treatment options and the lowest CRC survival rates. We trialed the possibility of organoid directed precision treatment for CRPM patients. CRPM organoids (peritonoids) isolated from patients underwent next-generation sequencing and medium-throughput drug panel testing ex vivo to identify specific drug sensitivities for each patient. We measured the utility of such a service including: success of peritonoid generation, time to cultivate peritonoids, reproducibility of the medium-throughput drug testing, and documented changes to clinical therapy as a result of the testing. Peritonoids were successfully generated and validated from 68% (19/28) of patients undergoing standard care. Genomic and drug profiling was completed within 8 weeks and a formal report ranking drug sensitivities was provided to the medical oncology team upon failure of standard care treatment. This resulted in a treatment change for 2 patients, one of whom had a partial response despite previously progressing on multiple rounds of standard care chemotherapy. The barrier to implementing this technology in Australia is the need for drug access and funding for off-label indications. In conclusion, our approach is feasible, reproducible and can guide novel therapeutic choices in this poor prognosis cohort, where new treatment options are urgently needed. This platform is relevant to many solid organ malignancies.

  Study phs002023

• Immune Responses in Checkpoint Myocarditis Across Heart, Blood, and Tumor

  Immune checkpoint inhibitors (ICIs) are widely used in anti-cancer therapies, but they can cause morbid and potentially fatal immune-related adverse events (irAEs), such as ICI-related myocarditis (irMyocarditis). The pathogenesis of irMyocarditis and its relationship to anti-tumor immunity remain poorly understood. We sought to define immune responses in heart, tumor, and blood in irMyocarditis patients and controls by leveraging single‐cell RNA sequencing (scRNA‐seq) coupled with T-cell Receptor Sequencing (TCR-Seq). Our analysis demonstrated increased frequencies of cytotoxic T cells, inflammatory mononuclear phagocytes (MNPs), conventional dendritic cells (cDCs), and inflammatory fibroblasts in irMyocarditis heart tissue. Additionally, we revealed decreased frequencies of plasmacytoid dendritic cells, cDCs, and B lineage cells but an increased frequency of MNPs in the blood of irMyocarditis patients. Raw data for heart and blood can be found in dbGaP. All processed data and raw TCRseq data from heart tissue and tumor samples for this study can be found in GEO (Accession number GSE228597).Subject IDs with the prefix "SIC" were collected by the Severe Immunotherapy Complications (SIC) service at MGH due to suspicion of immune-related adverse events. Subject IDs with the prefix "donor" were collected by the MGH Melanoma Biobank at scheduled timepoints; this biobank systematically collects samples from patients at MGH at clinically relevant timepoints.

  Study phs003413

• National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

  NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

  Study phs004180

• Nala TAS-LRS PGx Study

  Pharmacogenomics (PGx) testing improves medication safety and efficacy by identifying genetic variants that affect drug response. However, current technologies often fail to resolve complex loci, detect structural variants, or phase alleles accurately. Here, we present an end-to-end PGx workflow based on Targeted Adaptive Sampling-Long Read Sequencing (TAS-LRS), integrating a streamlined laboratory protocol with a bioinformatics pipeline that includes a novel CYP2D6 caller. Using 1,000 ng of DNA and three-sample multiplexing on a single PromethION flow cell, the assay achieves consistent on-target (25x) and off-target (3x) coverage, enabling accurate, haplotype-resolved testing of 35 pharmacogenes alongside genome-wide genotyping from off-target reads. We further developed the workflow into a clinically ready service and validated its performance across 17 reference and clinical samples. The assay demonstrated high concordance for small variants (99.9%) and structural variants (>95%), with phased diplotypes and metabolizer phenotypes reaching 97.7% and 98.0% concordance, respectively. Improved calls were observed in 12 genes due to enhanced genotyping, phasing, or novel allele detection. In addition, off-target reads supported accurate genome-wide imputation, comparable to short-read sequencing and superior to microarrays. These results establish the feasibility of long-read sequencing for clinical PGx testing and position TAS-LRS as a scalable solution combining both targeted and genome-wide utility.

  Study EGAS50000001116

• Complete Genomics Deep Whole-Genome Sequencing of Circulating Tumor Cells from a Patient with Metastatic Breast Cancer

  Circulating tumor cells (CTCs) are considered to be informative non-invasive biopsy for the early detection, diagnosis or therapy guidance of cancer. CTCs also contain most of the heterogeneity found across multiple metastatic sites. In this study, we combine recently improved CTC isolation methods, resulting in almost pure CTCs, with advanced whole genome sequencing (WGS) based on Long Fragment Read (LFR) technology to demonstrate, for the first time, the research and clinical utility of an accurate, comprehensive, phased, and quantitative genomic analysis of CTCs. In particular, genomes of 34 CTCs, collected at two different time points from a patient whose metastatic breast cancer ultimately became resistant to standard treatments, were analyzed as 3072 barcoded sub-genomic compartments of long DNA. An average read coverage of 23X per cell enabled the high-resolution detection of somatic variants, cancer copy number variations (CNVs) and structural variants, including 133 CNVs shorter than 1Mb and an early chromothripsis-like event.

  Study phs001028

• Novel Strategies to Eliminate Resistance to B-cell Receptor Inhibitor Therapy in Lymphoid Malignancies

  Ibrutinib and acalabrutinib are BTK inhibitors (BTKi) used as frontline therapies for chronic lymphocytic leukemia (CLL). Clonal evolution during ibrutinib treatment has previously been studied, but limited study of clonal evolution in patients receiving acalabrutinib has been done. Our group analyzed 216 blood samples from 38 CLL patients at multiple time points during their BTKi treatment. Samples were prepared by standard protocols and sequenced using 200x Illumina sequencing. Using the longitudinal data, we reconstructed the clonal evolution of each patient using somatic mutations found within the B-cell populations. Three patterns of clonal evolution were identified: 1) new clone emergence, 2) clonal selection, and 3) clonal replacement. As previously seen in ibrutinib treatment, the evolution of subclones containing CLL-driver mutations was associated with worse clinical outcomes for patients treated with acalabrutinib (Log-rank p=0.04). Understanding clonal evolution during treatment with acalabrutinib can help determine and modify the clinical course of patients with CLL.

  Study phs003042

• Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

  The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

  Study phs003322

• A Comprehensive Platform for Analyzing Longitudinal Multi-Omics Data

  PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for analyzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type or user defined groups. It allows to infer stable and variable features in a given donor and each cell type or a user defined group. The outlier analysis can be performed to identify technical/biological perturbed samples in a donor or a participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type. The data that is available in the dbGaP is the demo longitudinal samples used in the study, which includes hashed raw fastq files for single-cell RNA-sequencing (scRNA-seq) and non-hashed fastq files for single-cell ATAC-sequencing (scATAC) experiment.

  Study phs003203

• Starting Treatment with Agonist Replacement Therapies (START): A Randomized Trial of Methadone vs Buprenorphine/Naloxone for the Treatment of Opioid Dependence

  The Starting Treatment with Agonist Replacement Therapy (START) study was a 24-week, open-label, randomized trial of methadone versus Suboxone (buprenorphine/naloxone) for the treatment of opioid dependence. Patients were over the age of 18 and met DSM-IV qualifications for opioid dependence. The primary goal of the study was to determine if either medicine was associated with liver toxicity issues in this vulnerable patient population. Liver enzymes were measured at four time points. Urinalysis for opioids, cocaine, cannabis, benzodiazepines, and methamphetamine were performed on a weekly basis. A flexible dosing scheme was used during which physicians could alter medication dose based on withdrawal symptoms and urinalysis results. Neither medication was found to be associated with liver enzyme levels. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001135

• Genomics and Methylation of Neuroendocrine Prostate Cancer from cfDNA (Cornell/Trento 2019)

  A subset of castration resistant prostate cancers develop small cell neuroendocrine prostate cancer (NEPC) as a mechanism of treatment resistance. Metastatic tissue biopsies to evaluate for NEPC transformation are invasive and challenging to perform serially. We performed whole exome and whole genome bisulfite sequencing of plasma cfDNA and matched tumor biopsy samples from 62 patients with metastatic prostate cancer along the disease spectrum to evaluate for NEPC associated genomic and epigenomic features. Multiple tissue biopsies and/or plasma time points were included for a subset of patients to characterize disease heterogeneity and dynamic changes. Computational analysis of clonality and allele specific quantification allowed for detailed comparison of matched tumor tissue and cfDNA data (CLONET v2). Methylation profiles detected from tissue and plasma data were compared and NEPC specific alterations were evaluated in cfDNA. The study supports the feasibility of a plasma based assay for the detection of NEPC.

  Study phs001752

• Evolving epigenomics of immune cells in type 1 diabetes at single nuclei resolution

  The appearance of diabetes-associated autoantibodies is the first detectable sign of the disease process leading to type 1 diabetes (T1D). Evidence suggests that T1D is a heterogenous disease, where the type of antibodies first formed imply subtypes. Here, we followed 49 children, who subsequently presented with T1D and 49 matched controls, profiling single-cell epigenomics at different time points of disease development. Quantitation of cell and nuclei populations as well as transcriptome and open-chromatin states indicated robust, early, replicable monocyte lineage differences between cases and controls, suggesting heightened pro-inflammatory cytokine secretion early among cases. The order of autoantibody emergence in cases showed variation across lymphoid and myeloid cells, potentially indicating cellular immune response divergence. The strong monocytic lineage representation in peripheral blood immune cells before seroconversion and the weaker differential coordination of these gene networks close to clinical diagnosis emphasizes the importance of early life as a critical phase in T1D development.

  Study EGAS50000000863

• Single_cell_analysis_T_cell_activation

  We isolated naïve and memory T cells from healthy donors and cultured them in resting and stimulated conditions. We performed scRNA sequencing to assess T cell actiavtaion and perform sceQTL analysis. Major challenges for translating GWAS variants to function include identification of the disease relevant cell types in which the associated variants function. We have shown that immune-disease variants are functional in CD4+ T cell activation, and understanding how GWAS variants affect the activation efficiency is critical for development of new therapies. To perform sceQTL analysis of naïve and memory T cell activation, here we stimulated T cells and profiled single cell transcriptome at different time points following stimulation. We mapped sceQTLs affecting cell activation. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003479

• Transcriptomic classes of BCR-ABL1 lymphoblastic leukemia

  In BCR-ABL1 lymphoblastic leukemia, treatment heterogeneity to tyrosine kinase inhibitors (TKIs), especially in the absence of kinase domain mutations in BCR-ABL1, is poorly understood. Through deep molecular profiling, we uncovered three transcriptomic subtypes of BCR-ABL1 lymphoblastic leukemia, each representing a maturation arrest at a stage of B-cell progenitor differentiation. An earlier arrest was associated with lineage promiscuity, treatment refractoriness, and poor patient outcomes. A later arrest was associated with lineage fidelity, deep and durable leukemia remissions, and improved patient outcomes. Each maturation arrest was marked by specific genomic events that control different transition points in B-cell development. Interestingly, these events were absent in BCR-ABL1+ pre-leukemic stem cells isolated from patients regardless of subtype, which supports that transcriptomic phenotypes are determined downstream of the leukemia-initialing event. Overall, our data indicate that treatment response and TKI-efficacy is an unexpected outcome of the differentiation stage at which this leukemia transforms.

  Study EGAS00001007167