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• ctDNA mutation analysis using the SiMSen-seq approach

  Mutation analysis in plasma samples with low ctDNA levels using a molecular barcoding technology, i.e. the single target approach SiMSen-seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing).

  Dataset EGAD00001006104

• In Utero MPN Twin WGS Data

  The dataset contains sequencing data generated for the publication 'In utero origin of myelofibrosis presenting in adult monozygotic twins after a prolonged disease latency.

  Dataset EGAD00001008319

• Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud university medical center

  Dac EGAC00001003193

• Cyr61-MAC DAC

  DAC for access to dataset on Cyr61-MAC and HUVEC

  Dac EGAC50000000355

• Citeseq of human bone marrow

  CITE-seq dataset of human bone marrow from four healthy donors. Single-cell RNA sequencing was performed using the 10x Genomics 3’ v3 platform. Approximately 7,000–10,000 cells were loaded in each 10x channel, after which the single-cell libraries were prepared according to manufacturer’s instructions, except for the added CITE-seq steps. Demultiplexed FASTQ files are provided.

  Dataset EGAD50000001211

• Bulk RNA sequencing validating an in vitro model mimicking the taNK phenotype.

  In order to obtain a sufficient amount of taNK cells for functional assays, we established an in vitro model to mimic the phenotype of taNK cells. BulkRNA sequencing was performed in order to validate the obtained phenotype comparing in vitro-generated CD103+CD49a+ (ta)NK cells with CD103-CD49a- non-taNK cells.

  Dataset EGAD50000002387

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___visium

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth.

  Study EGAS00001006045

• Tumor gene expression profiles for the study "TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells"

  RNA was extracted from formalin-fixed and paraffin embedded tumors of a large cohort of bladder cancer patients before treatment with anti-PD-L1. RNA was sequenced using a capture based approach (exome capture, RNA access).

  Dataset EGAD00001003977

• Small RNA sequencing dataset from human prefrontal cortex tissue - ALS vs CTR

  For mature miRNAs and hairpins, BAM and FASTq files

  Dataset EGAD50000000468

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010114

• Cell line data (RNAseq, ATACseq, ChIPseq)

  Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

  Dataset EGAD00001005493

• Temporal and Clonal Progression in Pediatric Ependymoma

  Whole genome and exome-based DNA sequencing of germline and tumor specimens from serial samples of a single patient's ependymoma. The findings reveal the extent to which treatment with radiation and chemotherapies resulted in the diversification of the tumor subclonal architecture and shaped the neo-antigen landscape, and provide new insights into possible molecular mechanisms of oncogenesis, treatment response and recurrence.

  Study phs001461

• Characterization of Neoantigen-reactive T cells by Single-Cell Analysis

  Through CITE-seq and TCR-seq analysis of non-small cell lung cancer (NSCLC) tumor-infiltrating lymphocytes (TIL), we developed a neoantigen-reactive T-cell signature based on clonotype frequency and CD39 protein and CXCL13 mRNA expression. There are four datasets from four NSCLC cases. Each dataset includes (1) Transcriptome of tumor infiltrating lymphocytes (TIL), (2) Cell surface protein expression on TIL by Feature barcoding, (3) T-cell receptor analysis of TIL, and (4) Reference file for feature-barcoding antibodies.

  Study phs002792

• Analysis of genomic alterations in dedifferentiated liposarcoma

  Multiomics analysis of rare cancers to identify genetic alterations related with pathogenesis and prognosis. To identification of genetics alterations of Dedifferentiated liposarcoma, DNAs and RNAs were extracted from dedifferentiated liposarcoma and paired non-cancer (normal) tissues. NGS libaraies were prepared by using Agilent SureSelect XT Human All Exon V5 + IncRNA kit for whole exome sequencing (WES) and TruSeq Stranded mRNA Prep kit or TruSeq RNA Access Library Prep kit (RNA seq). Sequencing was perfomred by Illumina HiSeq 2500.

  Study JGAS000182

• Papua New Guinean Genome Diversity Project (PGDP)

  The PGDP dataset includes 58 whole genome sequences for Papua New Guinean individuals from different locations. DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer. The PGDP dataset provides Fastq and BAM files.

  Dataset EGAD00001007783

• Data for Paper: Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  mRNA, total RNA, small noncoding RNA, NOMe-Seq and DNase-Seq data from following samples (not every Sequencing Type for every sample): 01_HepG2_LiHG_Ct1 41_Hf01_LiHe_Ct 41_Hf02_LiHe_Ct 41_Hf03_LiHe_Ct 51_Hf03_BlCM_Ct 51_Hf04_BlCM_Ct 51_Hf03_BlEM_Ct 51_Hf04_BlEM_Ct 51_Hf03_BlTN_Ct 51_Hf04_BlTN_Ct Metadata available at deep.dkfz.de

  Dataset EGAD00001002735

• scRNA-seq data set for 13 AML patients

  This dataset includes single cell (sc)RNA-seq of N=13 AML patients. The dataset includes bam files that have been purged of reads mapping to cells where a majority of the reads from that cell mapped to the human genome. All scRNA-seq data were generated using the Chromium Next GEM Single Cell 5' Reagent Kits v2 (Dual Index) from 10X Genomics.

  Dataset EGAD50000001346

• RNA-seq data from the MESOMICS project (French project of molecular characterization of malignant pleural mesothelioma)

  The dataset includes fastq files from 109 tumor samples as well as RNA-seq gene expression R data, RNA-seq transcript expression R data, RNA-seq gene counts matrix, RNA-seq transcript counts matrix, RNA-seq gene FPKM matrix RNA-seq transcript FPKM matrix for the 109 samples. The sequencing was done with HiSeq 2000 instrument.

  Dataset EGAD00001007024

• Illumina BeadArray SNP arrays

  SNP measurement. Illumina BeadArray SNP arrays for the study "Molecular characteristics in Burkitt lymphoma over age groups"

  Dataset EGAD00010002137

• Premalignant SOX2 in ovarian cancer patients

  Whole Genome Sequencing data set for the study "Premalignant SOX2 in ovarian cancer patients"

  Dataset EGAD00001002734

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - TGS

  Targeted gene sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015468

• Walter and Eliza Hall Institute - University of Melbourne

  Data Access Committee for Gocuk, Lancaster et al. 2024: nanopore sequencing data of patients with choroideremia and X-linked retinitis pigmentosa, to determine X inactivation skew.

  Dac EGAC50000000301

• HIV exome pilot, exome data hs37d5

  exome sequence data for 57 HIV elite long term non-progressors and rapid progressors. Complete dataset of improved BAMs mapped to hs37d5 and including phenotype information.

  Dataset EGAD00001003345

• Illumina HiSeq X Ten

  Three files of patients 10, 11 and 13 with WGS done on Illumina HiSeq X Ten. For research purpose and authorised user only.

  Dataset EGAD00001003439

• ATAC-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole genome sequence data for ATAC-seq (42 samples) of human stimulated and cultured CD4+ Treg cells.

  Dataset EGAD00001004829

• DAC for Whole Genome Sequencing Expands Diagnostic Utility and Improves Clinical Management in Pediatric Medicine

  Dac EGAC00001000419

• DAC for Genetic and Microenvironmental Analysis of PTCL at Department of Hematology, University of Tsukuba

  Dac EGAC50000000600

• DAC for "H3K27me3-mediated epigenetic repression regulates neuroblastoma development and contributes to biological heterogeneity"

  Dac EGAC00001003620

• Circulating tumor cells for comprehensive and multiregional non-invasive genetic characterization of multiple myeloma

  Study EGAS00001004288

• The biology of cell-free DNA fragmentation and the roles ofDNASE1, DNASE1L3 and DFFB

  The biology of cell-free DNA fragmentation and the roles of DNASE1, DNASE1L3 and DFFB

  Study EGAS00001003514

• Analysis of somatic mutations in normal blood, AML and MDS samples

  Targeted pulldown of genes known to be recurrently mutated in AML & MDS from patient and normal samples using Agilent Sureselect and for some cases also using Illumina Truseq technology.

  Dataset EGAD00001002180

• B15PON dataset

  Organoid cultures derived from normal colon and/or colorectal adenomas and/or colorectal carcinomas. RNA and DNA was isolated from these cultures for genome wide profiling.

  Dataset EGAD00001008411

• Whole exome sequencing of Finnish hereditary breast cancer families

  A remarkable proportion of factors causing genetic predisposition to breast cancer (BC) are unknown in non-BRCA1/2 families. Exome sequencing was performed for 13 high-risk Finnish hereditary breast and/or ovarian cancer (HBOC) families to detect variants contributing to BC susceptibility

  Study EGAS00001001835

• RRBS data for solid tumors and adjacent normal tissues

  RRBS data for solid tumors and adjacent normal tissues

  Dataset EGAD00001009001

• WES data for genomic determinants of response and resistance to inotuzumab in B-ALL

  Whole exome sequencing data for 69 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000097

• Exome sequencing for paired tumor/normal samples from patients with corticotropin-independnet Cushing's syndrome

  Exome sequencing was performed for paired tumor/normal samples from patients with corticotropin-independnet Cushing's syndrome. Tumor DNA was extracted from adrenocortical adenomas and normal DNA was extracted from adjacent adrenal tissues or periphral blood.

  Dataset EGAD00001000715

• WGS files for Klco-NUP98 data

  WGS files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015443

• WXS files for Klco-NUP98 data

  WXS files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015444

• RNASeq files for Klco-NUP98 data

  RNASeq files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015445

• scRNASeq files for Klco-NUP98 data

  scRNASeq files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia" PMID: 39974131, PMCID: PMC11838931, DOI: 10.1101/2025.01.21.25320683

  Dataset EGAD00001015479

• ChIPseq data for Glioblastoma (EGAS00001003953, H016)

  ChIPseq data for human glioblastoma patients, EGAS00001003953. Mix of input, H3K27ac, H3K27me1, H3K27me3, H3K36me3, H3K4me1, H3K4me3, H3K9me3 and BRD, 20 human samples, 2 cell lines (LN229, ZH487).

  Dataset EGAD00001006548

• High-throughput sequencing data for study of molecular drivers of resistance to castration in localised prostate cancer

  Aligned whole-genome sequencing and RNA-seq of localised prostate cancer for study 'Loss of SNAI2 in prostate cancer correlates with clinical response to androgen deprivation therapy'.

  Dataset EGAD00001006640

• CBD-RAW-REPERTOIRE-T: T cell bulk repertoire sequence files

  fastq and filtered fasta files for T-cell receptor sequencing. For further information regarding this dataset, please contact Rachael Bashford-Rogers at contact@combat.ox.ac.uk.

  Dataset EGAD00001007961

• Genetic Variants Influence on the Placenta Regulatory Landscape

  This study of the regulatory landscape of the placenta relies on the identification of associations between genetic variant and gene expression changes (eQTLs); genetic variant and DNA methylation changes (mQTLs); and, gene expression change and DNA methylation change (eQTMs). It involves the analysis of DNA sequence variation (n=303), DNA methylation (n=303) and mRNA expression data (n=80) from placentas from healthy women. Such studies are crucial to fully apprehend the complexity of the regulatory landscape and to support further analysis focusing and disease driven phenotype.

  Study phs001717

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___DNA_sequencing

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

  Study EGAS00001003517

• Understanding_the_multicellular_dynamics_of_clear_cell_renal_cell_carcinoma___single_cell_RNA_sequencing

  This study will reconstruct the single cellular phylogeny of tumour and immune cells in relation to both genomic, functional, and spatial location. 20 tumours in total will be studied, including non-progressing small renal masses, progressing small renal masses, relatively indolent larger tumours, and high risk tumour with metastatic sampling. We aim to: Generate a focused, comprehensive phylogenetic characterisation of tumour cells Understand the dependencies of the cancer genome, transcriptome, tissue architecture and the single cellular micro-environment Quantify the single cellular composition and functional intra- and inter- tumoural heterogeneity Determine the phylogeny of tumour associated lymphocytes and their relationship to neo-epitopes and the immune microenvironment Investigate the mechanisms by which the tumour-normal interface constrains tumoural growth

  Study EGAS00001003519

• Lindsey E. Jones et al. Patient-derived cells from recurrent tumors that model the evolution of IDH-mutant glioma. Neuro-Oncology Advances, 2020. We established robust, versatile, and well-characterized Patient Derived Cells (PDC) of an IDH1-mutant astrocytoma and an IDH1-mutant oligodendroglioma that represents defined evolutionary stages of chemotherapy-induced hypermutation. The PDCs retain tumor subtype defining features over time as well as classic hallmarks of cancer, including anchorage independent growth and cell immortality. The integrated phylogenies composed of PDCs,single-cell-derived PDCs, patient-derived xenografts, and corresponding spatiotemporal tumor tissue samples also provide new insight into the clonality, evolutionary pattern, and immense mutational load of hypermutated IDH mutant gliomas.

  IDH-mutant lower-grade gliomas can undergo malignant progression via temozolomide-driven hypermutation. Patient-derived cells (PDC) that model the genetically distinct hypermutated (HM) tumor subgroup are generally lacking, and few if any human brain tumor cell models are from defined evolutionary time points. Here, we characterize multiple PDC derived from independent surgical specimens of IDH1-mutant recurrences, including an ATRX and TP53-mutant astrocytoma and a 1p/19q co-deleted and TERT promoter-mutant oligodendroglioma. We determined the evolutionary time points represented by each PDC using exome sequencing and phylogenetic reconstruction, comparing the PDC and single cell clones of the PDC (scPDC) to multiple spatiotemporal tumor tissue samples, PDC-derived xenografts (PDX) and patient-matched blood. The tumor samples exhibited TMZ-induced mutagenesis and a branching pattern of evolution. We found clear evidence of two fully independent founder HM clones in the tumor tissue that are faithfully represented by independent PDC. The PDC, scPDC and PDX also shared the mutagenesis signature and represent the mid and later evolutionary time points of their corresponding tumors. The PDC maintained the tumor subtype-defining features over many passages, including heterozygosity of the IDH1 R132H mutation, production of 2-hydroxyglutarate (2-HG), and subtype-specific telomere maintenance mechanisms. The PDC from both tumors exhibited anchorage-independent growth in soft agar. The oligodendroglioma PDC formed infiltrative intracranial tumors with characteristic oligodendroglioma histology, initially with a long period to tumor formation. We conclude that the PDC, scPDC and PDX faithfully model the heterogeneous clonal origins of the corresponding tumor tissue. The multilevel analysis also provides new insight into the intratumoral heterogeneity and vast mutational load of HM glioma. The PDC from multiple evolutionary time points presented in the context of full clinical timelines may be useful to model evolution and intratumoral heterogeneity, important sources of therapeutic failure.

  Study EGAS00001003992

• The genomic landscape of follicular and diffuse large B-cell lymphoma

  As part of the ICGC, the ICGC MMML-Seq project performed whole genome sequencing and RNA sequencing of follicular and diffuse large B-cell lymphoma. Follicular and diffuse large B-cell lymphomas are the most common B-cell lymphomas in adulthood. Analyses were performed in concordance with the guidelines of the ICGC. The results define the genomic landscape of structural variants, somatic single nucleotide variants and mutational signatures in these lymphomas

  Study EGAS00001002199

• DAC for "Multimodal plasma and urinary cell-free DNA profiling improves risk stratification in newly diagnosed prostate cancer" with Dr. Anja Lisa Riediger(a.riediger@dkfz-heidelberg.de) and PD Dr. Magdalena Görtz(magdalena.goertz@dkfz-heidelberg.de)

  Dac EGAC00001003576