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• 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

• Dataset-linking-WGS-samples-in-ega-box-81-via-README-for-study-EGAS00001002923

  This dataset contains 318 Tumor and Control WGS files submitted in another EGA box for samples for Gerhauser et al.,Cancer Cell, 2018, 34:996-1011. WGS and sequencing protocol was earlier described in Weischenfeldt et al, Cancer Cell, 2013.

  Dataset EGAD00001007861

• Utlizing the RA signature to predict response to TNFi

  This study involves bulk RNA-seq analyses of blood cells from patients with rheumatoid arthritis who have had an inadequate response to methotrexate, collected before and 12 weeks after effective treatment with either etanercept or adalimumab. Peripheral blood mononuclear cells were stimulated with anti-CD3 for 24 hours and sorted into CD4+, CD19+, and CD4-CD19- (DN) populations for bulk RNA-seq.

  Study phs002562

• The landscape of somatic mutations in epigenetic regulators across 1000 pediatric cancer genomes

  To define the frequency and pattern of somatic mutations in epigenetic regulators in pediatric cancer, we sequenced 633 genes, encoding the majority of proteins involved in patterning the epigenome, in 1000 pediatric tumors spanning 21 different cancer subtypes. This analysis establishes an epigenetic landscape of pediatric cancer, which expands the knowledge for potential therapeutic targets and for developing personalized therapy.

  Study EGAS00001000449

• Subclonal evolution of four ER+ breast cancers determined by WGS and scRNA-Seq

  We analyzed the subclonal evolution of four ER+ breast cancers over 2-15 years using whole-genome sequencing (WGS) and single-cell RNA-Seq (scRNA-Seq). For each patient we analyzed 2-6 cancer samples, generally metastatic pleural effusions or ascites, by WGS, along with germline DNA. Two of the samples per patient were selected for single-cell RNA-Seq.

  Study EGAS00001002436

• Ancient nuclear genomes enable repatriation of Indigenous human remains

  For many decades Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return of their ancient people. By sequencing ten ancient nuclear genomes of Aboriginal Australians and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1,540 yr BP) of known provenance we demonstrate the feasibility of successfully identifying the geographic origins of unprovenanced ancestral remains using genomic methods.

  Study EGAS00001003359

• Chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from immune cells for healthy young and healthy old subjects

  Dataset consisting of: (1) N=234 genome-wide chromatin accessibility (ATAC-seq) profiles for distinct N=21 healthy old and N=28 healthy young subjects. ATAC-seq biological samples provided for the following tissues: PBMC (N=24), CD14+ monocytes (N=18), CD8+ memory T cells (N=7), CD8+ naive T cells (N=7), CD4+ memory T cells (N=7), CD4+ naive T cells (N=7), and naive B cells (N=7). (2) N=39 genome-wide transcription (RNA-seq) data for distinct N=15 healthy old and N=24 healthy young subjects' PBMCs.

  Dataset EGAD00001003602

• March 2018 cumulative data release for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2018 cumulative data release (bams,fastqs) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium

  Dataset EGAD00001003963

• November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001007529

• cfDNA Methylomes for HCC Detection and Postoperative Monitoring

  To overcome the limitations of current ctDNA-based HCC detection, specifically mutational profiling, we propose quantifying cfDNA methylation levels using cfMeDIP-seq and evaluating its capacity for HCC detection and post-surgery recurrence monitoring. This approach aims to reveal the clonal dynamics of HCC during surgery and upon relapse. Our preliminary data and analyzed results demonstrate that tumor-agnostic cfDNA methylomes can accurately detect HCC and predict recurrence after liver resection or transplantation. This method could have significant implications for the diagnosis, treatment, and monitoring of HCC.

  Study EGAS50000000450

• Development and Validation of Patient-Derived Xenografts from Fibrolamellar Carcinoma Human Tissue

  We developed and validated Patient-Derived Xenografts (PDX) of Fibrolamellar Carcinoma human tissue from surgical resections. Human tissues from primary liver tumor, recurrent liver, and liver metastases were implanted into NOD-SCID-Gamma (NSG) mice (Jackson laboratories) and monitored for tumor growth. Some of the original tissues were frozen for further analysis including RNA sequencing. Tumors that grew were then harvested and passaged into additional mice. Some tumor tissues from the PDX samples were frozen for RNA-Seq analysis. The PDX was validated by histologic, transcriptomic and proteomic analysis. The RNA-Seq analysis was performed on original tissue samples including primary liver tumor, recurrent liver, liver metastases, normal liver, and the derived PDX.

  Study phs002435

• SJCRH pediatric HGG sequencing data

  A DAC to manage access to sequencing data derived from primary patient tumors and associated models, e.g. xenografts and cell lines.

  Dac EGAC50000000101

• Immunopeptidomics of colorectal cancer organoids reveals a sparse HLA class I neoantigen landscape and no increase in neoantigens with interferon or MEK-inhibitor treatment

  Study EGAS00001003886

• bulk RNA-seq data

  a total number of 99 bulk RNA-seq lymphoma samples

  Dataset EGAD50000000631

• methylomics

  Methylomics analysis results formatted as a beta matrix

  Dataset EGAD00010001660

• TRACERx RRBS

  TRACERx 100: RRBS data from a subset of the first 100 TRACERx tumours

  Dataset EGAD00001004798

• HeLa S3 (CCL-2.2) HiC Sequencing

  HiC chromatin conformation sequencing was performed for the purpose of chromosome fusion and structural rearrangement identification.

  Study phs000665

• Liver Regulatory Genomics Data Access Committee

  Data access committee for genomic datasets generated for human liver tissue and human primary liver cells by the Regulatory Genomics of Metabolic Disease group (Imperial College London, Section of Genetics and Genomics).

  Dac EGAC50000000715

• single cell transcriptomic analysis of tumor samples collected from 5 patients with EMM

  Contains the raw single cell RNAseq data used for the study

  Study EGAS50000000034

• Whole exome sequencing of prDLBCL

  To investigate the mutational landscape of prDLBCL, 34 cases were selected for whole exome sequencing.

  Study EGAS50000000403

• sc-DECISION

  Data derived from PBMC and blood samples for the single cell and bulk RNAseq analysis for the sc-DECISION paper. https://doi.org/10.1101/2025.02.04.25321370

  Dataset EGAD50000001622

• RNAseq for CIAO Clinical Trial

  RNAseq (QuantSeq) from FFPE tissues for the CIAO clinical trial

  Dataset EGAD50000001676

• Single-cell RNA-seq of Bone marrow samples

  For two donors, we collected CD34 plus and CD34 minus hematopoietic cells for the single-cell RNA-seq analysis.

  Dataset EGAD50000000514

• cfDNA methylation dataset for colon cancer

  Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

  Dataset EGAD50000000075

• HCC.GNE RNA-Seq

  RNA-Sequencing data (raw read sequences) for 23 samples, from 12 patients, for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma"

  Dataset EGAD00001000886