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• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  ChIP-Seq data for 154 CD4-positive, alpha-beta T cell sample(s). 355 run(s), 265 experiment(s), 250 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002673

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002697

• Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

  We used 200 ccRCC samples from 51 tumors to simultaneously isolate DNA, RNA, and protein according to established protocol. RNA quality was assessed using an Agilent Bioanalyzer, and total RNA with RIN>7 was used for further RNA sequencing. 184 ccRCC samples from 49 tumors passing initial quality control underwent RNA sequencing at Admera Health Inc. (Genohub Inc., Austin, TX). RNA sequencing libraries were prepared using the Illumina TruSeq Stranded mRNA high throughput (HT) sample preparation kit following the manufacturers’ protocol. Pair-end RNA Seq data was deposited in this cohort.

  Dataset EGAD00001005356

• Targeted Germline Sequencing of the Leeds Melanoma Cohort

  In this project we performed targeted sequencing of known and suspected melanoma susceptibility genes in a cohort of melanoma patients and matched controls. Our aim was to identify variants that predispose to melanoma development. The melanoma cases used in this study were population ascertained.

  Dataset EGAD00001007520

• Whole Exome Sequencing data of glioma from the Chinese Glioma Genome Atlas (CGGA) project

  Glioma is the most common and aggressive brain cancer in adults. While primary glioma has been widely studied, molecular characterization of recurrent glioma is still rare. The high-quality sequencing data that we generated provides a useful resource for the community. The CGGA project contains over 2,000 samples from Chinese cohorts. It totally includes the whole-exome sequencing (286), DNA methylation (159), mRNA sequencing (1,018), mRNA microarray (301) and microRNA microarray (198) and matched clinical data. CGGA removes the barriers to researchers, providing rapid and convenient access to high-quality functional genomic data resources for biological research and clinical applications.

  Dataset EGAD00001006445

• mRNA and T cell receptor sequencing of patients with Pandemrix-associated narcolepsy type 1

  PBMCs isolated from 27 individuals (11 narcolepsy type 1 patients, 16 healthy controls) were stimulated with the peptide Neuroaminidase 175-189 or Protein-O-mannosyl transferase 1 (POMT1) 675-689 or media as control. FACS sorted CD4+ and CD8+ lymphocytes from one patient were subjected to the same stimulation. Transcriptome profiling was done with a 3' tagging protocol. T cell receptor repertoires were profiled with amplicon sequencing (Rep-seq). The dataset contains FASTQ files with sequencing reads, transcript count matrices and TCR clonotypes.

  Dataset EGAD00001006797

• mRNA and T cell receptor sequencing of patients with Pandemrix-associated narcolepsy type 1

  PBMCs isolated from 27 individuals (11 narcolepsy type 1 patients, 16 healthy controls) were stimulated with the peptide Neuroaminidase 175-189 or Protein-O-mannosyl transferase 1 (POMT1) 675-689 or media as control. FACS sorted CD4+ and CD8+ lymphocytes from one patient were subjected to the same stimulation. Transcriptome profiling was done with a 3' tagging protocol. T cell receptor repertoires were profiled with amplicon sequencing (Rep-seq). The dataset contains FASTQ files with sequencing reads, transcript count matrices and TCR clonotypes.

  Dataset EGAD00001006796

• BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression

  This dataset contains all available targeted exon sequencing bam files from our study, "BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which sample is referenced. These include serial cfDNA samples ("-1", "-2", "-3", etc.), paired white blood cell or benign tissue control samples ("-Control"), or primary archival tissue samples derived from a diagnostic biopsy, prostatectomy, or transurethral resection of the prostate ("-Tissue"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006733

• VCF file from 16 patients affected by acute intermittent porphyria

  VCF file from 16 patients affected by acute intermittent porphyria. Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). BAM files were processed at the CNAG (Barcelona) with their pipeline, including GATK v3.6 for genotyping and other tools such as snpEff for annotating variants, to produce this VCF file with a total of 10,630,259 variants, out of which 8,731,523 are SNVs.

  Dataset EGAD00001006952

• scRNA-seq dataset of patient and healthy donors

  scRNA-seq dataset on a patient (P) presenting with defects of immunity and four healthy donors (C1, C2, C3, C4). This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are 15 paired-end fastq files (3 per patient/donor - I1, R1, R2) and 15 processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (3 per patient/donor - barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz).

  Dataset EGAD00001008372

• Cell-free DNA and bone marrow samples from myelodysplastic syndromes

  We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA.

  Dataset EGAD00001008567

• Genetic regulation of RNA splicing in human pancreatic islets

  Here we provide access to newly generated RNA-seq data for 101 human islet samples used to map genetic effects on gene expression and alternative splicing (eQTLs and sQTLs) in a total of 399 human islets. We also make publicly available genotyping array data for 128 human islets, including the fraction of 101 human islet samples with existing RNA-seq data.

  Dataset EGAD00001009102

• WGS of tissues from members of family with germline POLD1 L474P variant

  The study includes WGS data for DNA extracted from blood, fibroblasts or buccal swabs from sixteen family members, who represent four sub-families, each including two parents and one to three children, comprising a total of eight offspring. In two sub-families POLD1 L474P was carried by the father; in one sub-family, by the mother; and in the other sub-family, both parents had wild-type POLD1.

  Dataset EGAD00001009282

• T cell transcriptional gradient

  There are two datasets: 1. scRNA-seq of human cutaneous immune cells from psoriasis patients. These include pre- and post-Tildrakizumab treated patients and come in a BAM file format. 19006FL-25-01 19006FL-38-01 19006FL-32-01-03 19006FL-33-01 19006FL-28-01-05 19006FL-35-01-01 2. RNA-seq of ZFP36L2 CRISPIR deleted Human T cells are FASTQ files. 19006XR-30-05 19006XR-30-04 19006XR-30-02 19006XR-30-01 19006XR-26-05 19006XR-26-04 19006XR-26-02 19006XR-26-01 19006R-22-04 19006R-22-08 19006R-22-05 19006R-22-01

  Dataset EGAD00001009677

• Test dataset with ligh-weight files

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 3 pairs of light-weight (sliced) files: BAM + BAI, CRAM + CRAI and VCF + TBI. These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client). For any further questions, please contact the DAC (Helpdesk - email: helpdesk [at] ega-archive [dot] org).

  Dataset EGAD00001009826

• H3K27ac/H3K27me3 landscape of medulloblastoma

  We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

  Dataset EGAD00001009709

• WGS data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - UMCU/NKI

  The dataset includes cram files from WGS of 6 NEN tumors or metastases and matched PDTOs. For all tumors, cram files from WGS of either matched normal tissue or matched blood from the corresponding patients are included. Analysis VCF files are also included in the dataset. The sequencing was done with a NovaSeq 6000 instrument.

  Dataset EGAD00001009989

• Long-read sequencing identifies a common transposition haplotype predisposing for CLCNKB deletions

  This dataset contains CLCNKA/CLCNKB locus alignment data from 27 patients with Bartter syndrome and structural variants encompassing the CLCNKB gene. Due to data protection regulations and in accordance with the patient consent, only relevant alignments from the following regions are shared: hg19: chr1:16,300,000-16,400,000 hg38 (linked read dataset only): chr1:16,000,000-16,100,000 Methods to generate libaries were: long-range amplicon PCR (24 samples), targeted long-fragment enrichment (Samplix/Xdrop technology, 4 samples), long-read whole genome (PacBio Sequel II HiFi reads, 3 samples), 10X linked read short read whole genome (1 sample).

  Dataset EGAD00001011064

• TXT_Cytof_15B

  Matrix of normal values from 39 marker CyTOF assay performed on longitudinal BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011143

• SNF_CyTOFF_20

  Matrix of normal values from 39 marker CyTOF assay performed on baseline BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011146

• Blood plasma and FFPE derived total RNA seq dataset from DLBCL and PMBCL patients

  Blood plasma samples (n=168) and matched diagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples (n=69) of DLBCL patients, PMBCL patients and healthy controls were collected between 2016-2021. Plasma samples were collected at diagnosis, at interim evaluation, after treatment, and in case of refractory or relapsed disease. RNA was extracted from 200 µl plasma using the miRNeasy serum/plasma kit and from FFPE tissue using the miRNeasy FFPE kit. RNA was subsequently sequenced on a NovaSeq 6000 instrument using the SMARTer Stranded Total RNA-seq pico v3 library preparation kit.

  Dataset EGAD00001011679

• A Retrospective and Cross-Sectional Analysis of Patients Treated for SCID Since January 1, 1968

  Individuals with a past diagnosis of severe combined immune deficiency (including many cases of "leaky SCID", Omenn syndrome, and reticular dysgenesis) who have undergone blood and marrow transplant, gene therapy, or enzyme replacement in the past may be eligible for 6902. The purpose of 6902 is very similar to 6901, except 6902 is looking backwards at what has already been done in the past (compared to 6901 which is looking into the future). Over 800 patients with SCID are expected to be enrolled on 6902. This makes 6902 the largest study ever to describe outcomes for patients with SCID treated at many different hospitals around North America. One of the most important components of the 6902 study is the "cross sectional" study. Patients who have received their treatments (BMT, gene therapy, enzyme replacement) many years ago are asked to come back to the hospital where they were treated. During this visit, additional research blood work is drawn and information is gathered regarding long-term transplant outcomes such as infections, graft-versus-host disease, autoimmune diseases, and quality of life. This will allow PIDTC researchers to better understand long-term outcomes from procedures that occurred many years ago (sometimes over 30 years ago) - something that is not possible at the present time with 6901. This will help researchers to best design new treatments and clinical trials in the future for children with SCID.

  Study phs001326

• Enhanced Adjuvanticity of a Personal Neoantigen Vaccine Generates Potent Neoantigen-Specific Immunity

  Personalized neoantigen-targeting vaccines can induce durable and diverse T cell responses and have been associated with improved outcomes. To augment immunogenicity, we tested a synthetic long peptide vaccine formulated with the adjuvants Montanide and poly-ICLC in 10 patients with melanoma. The vaccines, co-administered locally with ipilimumab and systemically with nivolumab, generated de novo ex vivo T cell responses against the majority of immunizing neoepitopes in all 9 fully vaccinated patients, and ex vivo CD8+ T cell responses in 6 of 9. Hundreds of circulating and intratumoral T cell receptor (TCR) clonotypes emerged following vaccination that were distinct from those arising after PD-1 inhibition. By linking vaccine-specificity and cellular phenotype of TCRs in post-treatment tumors at single cell resolution, we demonstrate remodeling of the intratumoral T cell repertoire following vaccination. These observations demonstrate the impact of multi-pronged immune adjuvanticity on the T cell repertoire in the context of neoantigen-targeting vaccines. We are submitting WES data from whole blood samples and tumor FFPE samples, and RNA-seq data from tumor FFPE samples. We are also submitting RNA-seq data from purified tumor samples. scRNA-seq data will also be submitted for skin samples (pre and post neoantigen vaccine dose #3), and tumor samples before starting treatment, before starting neoantigen vaccine Dose #1, and before neoantigen vaccine dose #4. Bulk TCR-seq data will be submitted for blood samples.

  Study phs003919