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• CTCF ChIP-sequencing data for Oncogenic 3D genome conformations identify novel therapeutic targets in ependymoma

  This dataset contains CTCF ChIP-sequencing data from seven samples (six tumor samples and one tumor derived cell line). Following library amplification, DNA fragments were sequenced using Illumina HiSeq 2000 paired-end sequencing resulting in 14 FASTQ files.

  Dataset EGAD00001008806

• 17 scRNAseq samples

  17 samples were processed for single cell RNA sequencing (SORT-seq)

  Dataset EGAD00001007523

• ctDNA dataset

  ctDNA data from IMvigor010: ctDNA data include TMB_status, cfDNA_extracted_ng, Plasma_Volume_Used_ml, Sample_Call, Sample_Number_Positive_Calls, Sample_Mean_VAF_In_Plasma (%), Sample_MTM_per_mL_In_Plasma for 581 patients across IMvigor010.

  Dataset EGAD00001007574

• ChIP-sequencing in human monocyte differentiation

  This dataset consists of ChIP-seq data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. ChIP-sequencing was done for H3K27, RAD21 and CTCF. In total, the data set includes 120 samples.

  Dataset EGAD00001007954

• Platelet RNAseq data for SLFN14 K219N patients

  RNAseq dataset containing 20 control and 2 SLFN14 K219N patient samples, derived from platelets. Sequencing libraries were constructed using an Illumina TruSeq stranded Ribo Zero Gold kit and paired end sequenced at a read depth of 30 million reads on an Illumina NovaSeq 6000 platform.

  Dataset EGAD00001008965

• Pacbio HiFI Whole-Genome Sequecing of Trios with Intellectual Disability

  6 trios and 1 proband were whole genome sequenced with PacBio Sequel II to a depth of 30X, using the HiFi chemistry. For each trio the proband was affected with severe ID, and the parents were unaffected. Samples are grouped by trio.

  Dataset EGAD00001009109

• 10xscRNA sequencing of 2 samples RRMM (multiple myeloma)

  Paired scRNA sequencing using 10xgenomics library preparation and Illumina HiSeq4000 for sequencing of 2 samples RRMM (relapsed refractory multiple myeloma)

  Dataset EGAD00001009681

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Small RNA sequencing data (TruSeq small RNA library preparation kit v2) from serum samples and tumor tissue of orthotopically injected mice (SH-SY5Y cell line) and unengrafted mice, treated with idasanutlin, temsirolimus and vehicle control.

  Dataset EGAD00001009625

• Raw count matrix for 44 baseline + 44 progression samples

  Count matrix from 44 pre-treatment (Ven-Obi or Clb-Obi) and 44 paired, post-treatment relapsed CD19+ B cells.

  Dataset EGAD00001009500

• Tumor Educated Platelets (TEPs) for breast cancer detection

  The TEP dataset consists of 549 Fastq samples which are divided into two experiments: a training data cohort, used to train the classifier, and a validation data cohort, used to assess classifier performance

  Dataset EGAD00001009790

• MutaSeq data for A.10-12

  MutaSeq was applied to CD34+ cells from patient samples A.10, A.11 and A.12 of the study. The protocol followed is described in https://doi.org/10.1038/s41467-021-21650-1 and in the methods of the manuscript

  Dataset EGAD00001010189

• Exome sequencing data

  Libraries were constructed using SureSelect HS XT Target Enrichment System v6 (Agilent). For each patient a library of CD3- cells (myeloid cells, considered tumor cells) and CD3+ cells (T cells, considered healthy) were generated.

  Dataset EGAD00001010190

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• Low-pass whole-genome DNA sequencing of cohesin-mutated and wildtype adult AMLs

  Low-pass whole-genome DNA sequencing of cohesin-mutated (STAG2 or RAD21 mutations) and wildtype (CTRL-AML) adult AMLs generated generated from ultrasound-fragmented genomic DNA. Samples were only sequenced shallow (20-40 Mio reads) Used for digital karyotyping and ChIP-seq background/copy-nuber normalization/correction.

  Dataset EGAD00001011207

• Whole exome sequencing (WES) of CIMP leukemias

  Whole exome sequencing of tumor material derived from 14 mixed myeloid/lymphoid leukemias with a CpG Island Methylator Phenotype (CIMP). For 4 of these patients, normal material was also sequenced and used as control (files with the same identifiers prepended by an “h”).

  Dataset EGAD00001011053

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• Human Spermatogenesis Methylome

  The dataset contains the methylome EM-sequencing raw data (fastq) of different spermatogenic cells from 5 human males (three controls and two crypotzoospermic). The datasets correspond to the following cell types: undifferentiated spermatogonia, differentiating spermatogonia, 4C spermatocytes, and 1C spermatids (this cell type only for the control individuals)

  Dataset EGAD00001011180

• Single cell TotalSeqC protein data of 20 PMBC pools of HCC patients

  Single cell TotalSeqC protein data serial peripheral blood mononuclear cell (PBMC) samples taken from advanced HCC patients. TotalSeqC is available for 41 out of 72 PBMC samples included in the study, and were combined into 20 pools.

  Dataset EGAD00001011346

• Whole-genome sequencing of Himalayan populations

  Whole-genome sequencing of 60 individuals from 15 Himalayan populations using the Illumina-B HiSeq X platform. These data are part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/.

  Dataset EGAD00001011358

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Paediatric RNA (2026-01-15)

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease. . This dataset contains all the data available for this study on 2026-01-15.

  Dataset EGAD00001015797

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Paediatric Spatial (2025-07-31)

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015665

• Fixed single-cell transcriptomic characterization of human radial glial diversity

  The human neocortex is created from diverse intermixed progenitors in the prenatal germinal zones. These progenitors have been difficult to characterize since progenitors - particularly radial glia (RG) - are rare, and are defined by a combination of intracellular markers, position and morphology. To circumvent these problems we developed a method called FRISCR (Fixed and Recovered Intact Single Cell RNA) for transcriptome profiling of individual fixed, stained and sorted cells. We developed and validated FRISCR on human embryonic stem cells. We then profiled primary human RG (96 - 132 days post conception) that constitute only 1% of the mid-gestation cortex. These RG could be classified into ventricular zone-enriched RG (vRG) that express ANXA1 and CRYAB, and outer subventricular zone-localized RG (oRG) that express HOPX. Our study identifies the first markers and molecular profiles of vRG and oRG cells, and provides an essential step for understanding molecular networks driving the lineage of human neocortical progenitors. Reprinted from Thomsen et. al. Nature Methods (2015), with permission from Nature Publishing. Human embryonic stem cell data may be obtained through NCBI's GEO database, using accession number GSE71858. Raw data from one human sample that was not consented to be released to dbGaP may be obtained directly from the authors of Thomsen et. al., 2015.

  Study phs001016

• Identification of Rare Germline Variants in Familial Patients with Non-medullary Thyroid Cancer

  As the most common malignancy of the endocrine system, thyroid cancer is classified into two major categories, non-medullary thyroid cancer (NMTC) and medullary thyroid cancer (MTC) according to the origins and clinical features. NMTC includes papillary thyroid cancer (PTC), follicular thyroid cancer (FTC), and anaplastic thyroid cancer (ATC). Sporadic non-medullary thyroid cancer (SNMTC) accounts for ~90% of all thyroid cancers. Compared to SNMTC, familial non-medullary thyroid cancer (FNMTC) is rare, constituting only 3 - 9%. FNMTC is a complex genetic disease that often shows an autosomal dominant mode of inheritance. Characterization of the germline variants causing the disease is still challenging given the heterogeneity of affected families. In recent years, some mutations in known cancer susceptive coding genes have been reported using targeted DNA sequencing method in FNMTC cases. Still, little is known for the novel mutations in other thyroid cancer predisposition genes. With the decreasing cost and rapid development of next generation sequencing technology, more rare germline mutations underlying different types of cancer susceptibility in families had been discovered by whole genome sequencing (WGS). In this study, we performed WGS in familial NMTC patients in the U.S. Our aim is to identify rare germline variants with high penetrance that may contribute to thyroid cancer predisposition in NMTC families.

  Study phs001758

• NIMH Human Middle Temporal Gyrus (MTG) Cell Types

  Elucidating the cellular architecture of the human neocortex is central to understanding our cognitive abilities and susceptibility to disease. In this study, we applied single nucleus RNA sequencing to perform a comprehensive analysis of cell types in the middle temporal gyrus of human cerebral cortex. We identify a highly diverse set of excitatory and inhibitory neuronal types, many of which are relatively sparse. Additionally, we found that excitatory types are less layer-restricted than expected based prior knowledge from cell morphologies and from mouse studies. Comparison to a similar mouse cortex single cell RNA-sequencing dataset revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of human cell type properties. Despite this general conservation, we also find extensive differences between homologous cell types in human and mouse, including dramatic alterations in proportions, laminar distributions, gene expression, and morphology. These species-specific features emphasize the importance of directly studying human brain. This study conducted by the Allen Institute for Brain Science was supported by the Allen Institute for Brain Science and by US National Institutes of Health grant U01 MH114812-02 to E.S.L. Collaborators request that publications resulting from these data cite their original publication: Hodge RD, Bakken TE, et al. Conserved cell types with divergent features between human and mouse cortex. bioRxiv. 2018 doi: 10.1101/384826.

  Study phs001790

• Genetic Determinants of Viral Clearance in HCV-Infected Populations

  The World Health Organization estimates there are 170 million persons with HCV infection worldwide, and an estimated 4 million persons are infected in the United States. Persistent HCV infection can cause cirrhosis and hepatocellular cancer. Long term disease consequences do not occur in persons who spontaneously recover. It is not known why 10-40% recover from hepatitis C (and are not at increased risk of cirrhosis and cancer), but that knowledge would contribute to efforts to treat and/or prevent HCV infection. The overall purpose of this study is to investigate the host genetic basis for recovery from hepatitis C virus (HCV) infection. There is strong evidence that host genetic differences determine HCV recovery. After accidental exposure to the same HCV inoculum, some persons recover while others develop persistent infection. Recovery from HCV infection is an outstanding phenotype for genetic studies since both viral exposure and viral recovery can be ascertained with high sensitivity and specificity and since there are no known viral or environmental determinants. The study group is comprised of an ethnically and geographically diverse international population. All cohorts comprising this study group of 3350 individuals are well characterized. This case-control study is comprised of approximately 40% clearance individuals who are matched by age and HIV status within their respective cohorts at a ratio of 1:1 or 1:2 with HCV chronically infected individuals.

  Study phs000248