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• Glial Cell Line-Derived Neurotrophic Factor (GDNF) Polymorphisms and Anxiety, Depression

  GDNF gene variants were studied as possible risk factors of depression or anxiety on a young sample. The association study involved eight (rs1981844, rs3812047, rs3096140, rs2973041, rs2910702, rs1549250, rs2973050 and rs11111) GDNF single nucleotide polymorphisms and anxiety and depression scores measured by the Hospital Anxiety and Depression Scale (HADS) on 708 Caucasian young adults with no psychiatric history. Results provided significant effects of two single nucleotide polymorphisms on anxiety scores following the Bonferroni correction for multiple testing (p=0.00070 and p=0.00138 for rs3812047 and rs3096140, respectively). Haplotype analysis confirmed the role of these SNPs (p=0.00029). A significant sex-gene interaction was also observed since the effect of the rs3812047 A allele as a risk factor of anxiety was more pronounced in males. This is the first demonstration of a significant association between the GDNF gene and mood characteristics demonstrated by the association of two SNPs of the GDNF gene (rs3812047 and rs3096140) and individual variability of anxiety using self-report data from a non-clinical sample. Reprinted from Kotyuk et. al., 2013 (Kotyuk, E., Keszler, G., Nemeth, N., Ronai, Z., Sasvari-Szekely, M., and Szekely, A. (2013). Glial Cell Line-Derived Neurotrophic Factor (GDNF) as a Novel Candidate Gene of Anxiety. PLoS One,8, (12) PMID: 24324616), with permission from Publisher (All content of articles published in PLOS journals is open access. You can read about our open access license here: http://www.plos.org/about/open-access/. To summarize, this license allows you to download, reuse, reprint, modify, distribute, and/or copy articles or images in PLOS journals, so long as the original creators are credited (e.g., including the article's citation and/or the image credit); Laura Perry; Staff EO;PLOS ONE)

  Study phs000713

• A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

  In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

  Study EGAS50000001529

• Molecular Genetics of Heroin Dependence in China

  Our principal goal was to determine the chromosomal locations of genetic variations associated with increased vulnerability to heroin dependence. This goal was attained by identifying specific DNA markers that are genetically linked to heroin dependence. We collected blood and diagnostic information (using a structured diagnostic interview) from 1230 people (sib-pairs) having DSM-IV defined heroin dependence as well as from their parents and other affected and unaffected siblings, when possible. Genotype and clinical data was archived using database software. We conducted a multipoint linkage analysis using the guidelines of Lander and Kruglyak to assert statistical significance, and followed up on regions of interest with a dense set of markers to evaluate candidate genes.

  Study phs001213

• Genetically unique biospecimens derived from individuals with or without Type 1 Diabetes

  In this dataset, samples correspond to pools of genetically unique biospecimens derived from individuals with or without Type 1 Diabetes. Each sample alias contains all the DNA test numbers for that pool. Each experiment corresponds to scmxGEX (multiome RNA gene expression), scmxATAC (multiome ATAC sequencing), scRNA (single cell RNA sequencing), scATAC (single cell ATAC sequencing) for each pool. Runs link the appropriate fastq files to each experiment. Deconvolution using genetic information is required for single sample-based testing.

  Dataset EGAD50000001257

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  The ccRCC-ITH study WES dataset is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. It contains whole exome sequencing data of 18 tumor and 2 adjacent normal samples from 2 UTSW patients, who have consented to depositing their genomic data to public repository. Tumor samples come from different tumor sites, including primary tumor, thrombus and metastases. WES was performed using 75bp paired-end fragments at an average read depth > 50x on a NovaSeq 6000 platform (Illumina, San Diego, CA, USA). The raw data is in fastq format.

  Dataset EGAD50000001550

• Childhood Cancer Data Initiative (CCDI): Identification and Targeting of Treatment Resistant Progenitor Populations in T-cell Acute Lymphoblastic Leukemia

  Our goal with this study was to identify the mechanisms of treatment resistance in T-cell acute lymphoblastic leukemia (ALL) using single-cell genomics. We profiled 40 T-ALL cases from the Children's Oncology Group AALL0434 clinical trial using CITE-seq/snATAC-seq, capturing a breadth of immunophenotypes, including early T-cell precursor (ETP) and near-ETP/non-ETP subtypes. By integrating analyses of T-ALL cells with the normal T-cell developmental trajectory, the study identified a specific subgroup of leukemia cells resembling bone marrow progenitors (BMP-like cells). These BMP-like cells were associated with treatment failure and poor overall survival in T-ALL patients. Overall, this study reveals comprehensive multiomic signatures for rapidly assessing risk and tailoring targeted treatment for high-risk T-ALL patients.

  Study phs003432

• Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

  This study presents a methodology for detecting circulating tumor DNA (ctDNA) using deep whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive alternative to bisulphite sequencing. The method enables simultaneous analysis of genomic and methylomic data for multi-cancer detection and monitoring minimal residual disease. In a diagnostic accuracy study across various cancer types, it achieved 85.3% sensitivity and 88.8% specificity, with validation done using matched tumour biopsies. Additionally, in silico validation showed strong discrimination at low ctDNA levels. The approach also successfully tracks tumour burden and ctDNA shedding from precancerous lesions post-treatment, making it ready for further clinical testing.

  Study EGAS50000000715

• Single-cell RNA sequencing of SI-NET

  Small intestinal neuroendocrine tumors (SI-NETs) arise from hormone-producing cells in the gut, yet the molecular changes driving malignant transformation remain poorly understood. Bulk tissue-based analyses make it challenging to distinguish signals derived from normal cells from those of normal hormone-producing cells. In this study, we analyzed SI-NETs at single-cell resolution and directly compared tumor cells with their corresponding normal hormone-producing counterparts using single-cell RNA sequencing. Tissue samples were obtained from two patients undergoing tumor resection surgery. Cells from corresponding normal intestinal mucosa and SI-NET tumors were isolated using specific markers and analyzed for direct comparison.

  Study EGAS50000001584

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• Targeted next-generation sequencing detects novel gene-phenotype associations and expands the mutational spectrum in cardiomyopathie

  Cardiomyopathies are a heterogeneous group of primary diseases of the myocardium,including hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), andarrhythmogenic right ventricular cardiomyopathy (ARVC), with higher morbidity andmortality. These diseases are genetically diverse and associated with rare mutations ina large number of genes, many of which overlap among the phenotypes. To betterinvestigate the genetic overlap between these three phenotypes and to identify newgenotype-phenotype correlations, we designed a custom gene panel consisting of 115genes known to be associated with cardiomyopathic phenotypes and channelopathies.A cohort of 38 unrelated patients, 16 affected by DCM, 14 by HCM and 8 by ARVC,was recruited for the study on the basis of more severe phenotypes and family historyof cardiomyopathy and/or sudden death.

  Study EGAS00001002506

• Comprehensive miRNA Sequence Analysis Reveals Survival Differences in Diffuse Large B-cell Lymphoma Patients

  Diffuse large B-cell lymphoma (DLBCL) is an aggressive disease, with 30-40% of patients failing to achieve complete responses to standard therapy. miRNAs are RNA molecules that attenuate expression of their mRNA targets. To characterize the DLBCL miRNome, we sequenced miRNAs from 92 DLBCL and 15 benign centroblast fresh frozen samples and from 140 DLBCL formalin-fixed, paraffin-embedded tissue (FFPET) samples for validation.

  Study EGAS00001001025

• Methylation_changes_in_OA_patients_with_chronic_exposure_to_cobalt_and_chromium

  We have whole blood from a population of 70 patients, half exposed chronically to an excessof metals cobalt and chromium. The 2 groups are age, sex, and OA diagnosis matched. The2 groups have systemic differences in bone mass and turnover, and other systemicdifferences.We will type the cohort of 70 individuals on the Illumina 450k methylation array and willcompare between the two groups.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 EGAS00001001180

• Bulk RNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015508

• Human liver NPCs single cell project

  Independent of their inflammatory phenotype, macrophages are key orchestrators of hepatic metabolism. Non-alcoholic fatty liver disease (NAFLD) often occurs in obese individuals and is among the most common causes of cirrhosis, the terminal chronic liver disease that may necessitate liver transplantation. While multiple populations of macrophages have been described in the human liver, their function and turnover in obese patients at high risk of developing NAFLD and cirrhosis is currently unknown. Herein we identified a specific human population of resident liver myeloid cells that protects against the metabolic impairment associated with obesity. By studying the turnover of liver myeloid cells in individuals undergoing liver transplantation using markers of donor-recipient mismatch, we made the novel discovery that liver myeloid cell turnover differs between humans and mice. Using single cell techniques and flow cytometry we determined that the proportion of the protective resident liver myeloid cells, denoted liver myeloid cells 2 (LM2), decreases during obesity. Functional validation approaches using human 2D and 3D cultures revealed that the presence of LM2 ameliorates the oxidative stress associated with obese conditions. Our study indicates that resident myeloid cells could be a therapeutic target to decrease the oxidative stress associated with NAFLD.

  Study EGAS00001007194

• Nurminen et al ("GP2Men") Study Primary and Metastatic Prostate Cancer Whole Genome Sequence Data

  We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

  Study EGAS50000000005

• Molecular counting enables accurate and precise quantification of methylated ctDNA for tumor-naive cancer therapy response monitoring

  Personalized cancer treatment can significantly extend survival and improve quality of life for many patients, but accurate and real-time therapy response monitoring remains challenging. To overcome logistical and technical challenges associated with therapy response monitoring via imaging scans or assays that track the variant allele fraction (VAF) of somatic mutations in circulating tumor DNA (ctDNA), we developed a tumor-naive liquid biopsy assay that leverages Quantitative Counting Template (QCT) technology to accurately and precisely quantify methylated ctDNA (Northstar ResponseTM).

  Study EGAS50000000734

• Analysis of Cell-Free DNA to Predict Outcome to Bevacizumab Combination Therapy in Metastatic Colorectal Cancer Patients

  This dataset includes FASTQ files of low coverage whole genome sequencing of normal tissue (n = 8), tumor tissue (n = 55) and cell free DNA from plasma samples (n=101) from patients with metastatic colorectal cancer treated with bevacizumab. A total of 164 samples are present from two different cohorts. The first batch of samples (n = 139, sample names sAPD302T until sAPD502_P0) were collected from the AC-Angiopredict Phase 2 trial (NCT01822444), the second batch of samples (n = 25m, sample names sAPD503_P0 until sAPD527_P0) were collected from the UMM cohort.

  Dataset EGAD50000000176

• Diverse transcriptomic and mutational patterns but limited functional pathway alterations in patient-derived SS cells

  We profile the whole-transcriptome of 7 patient-derived Sézary Syndrome (SS) cells to identify expression patterns, functional programs and expressed gene mutations that may provide clues on new therapeutic options for SS patients. The libraries were sequenced on NextSeq500 (Illumina) with a paired-end read length of 2x75bp.

  Study EGAS50000001151

• RNA-sequence analysis in patients with inclusion body myositis

  This study aimed to elucidate the molecular features of inclusion body myositis (IBM). We performed RNA sequencing analysis of muscle biopsy samples from myositis patients with the pathological finding of CD8-positive T cells invading non-necrotic muscle fibers expressing major histocompatibility complex class I (IBM, polymyositis, and unclassifiable myositis), and controls.

  Study JGAS000068

• Somatic mutations in endometriosis and normal uterine endometrium

  To characterize the genomic features of endometriosis, we performed whole-exome sequencing for ovarian endometriotic epithelium samples obtained from subjects without concurrent gynecological cancers. Additionally, we analyzed histologically normal uterine endometrial epithelium samples obtained from subjects with benign gynecologic diseases. All the epithelium samples were isolated by laser microdissection from frozen sections.

  Study EGAS00001003095

• RNA-seq Revision

  The dataset comprises bulk RNA‑seq libraries generated on the Illumina NextSeq 500 platform, including primary human hepatocytes (four donors), colon tissue (four masked replicates), and a comprehensive set of iPSC‑derived samples from the JHU106, ChiPSC18, ChiPSC22, and H9 lines. The collection covers multiple differentiation stages from iPSC to DE to HLC and cultivation protocols (CEL, HAY, SPH) with at least three replicates per condition. All sequencing data are provided as raw FASTQ files, with colon samples delivered as masked FASTQ in accordance with patient consent requirements.

  Dataset EGAD00001008951

• Genomic gain of EBV's LMP-1 in NKTCL

  The study found a high recurrence of genomic gain of LMP1 locus within EBV-associated NKTCL. The pilot data set and extended dataset of 77 WGS NKTCLs found 18/77 tumoral genomes to harbour genomic gain of LMP-1 locus within the EBV viral genomes within NKTCL tumoral sequencing data. The study also found 1/10 NKTCL cell lines to be positive for LMP-1 locus gain within EBV genomes too. This dataset includes solely the confirmatory WGS data of LMP-1 gain from NKYS cell lines using Oxford Nanopore long-read sequencing technology.

  Study EGAS50000000260

• CSER: Evaluating Utility and Improving Implementation of Genomic Sequencing for Pediatric Cancer Patients in the Diverse Population and Healthcare Settings of Texas: The KidsCanSeq Study

  Through this Clinical Sequencing Evidence-Generating Research (CSER) with Enhanced Diversity project we are completing a clinical study (The Texas KidsCanSeq Study) comparing the results of targeted cancer panel sequencing versus genome-scale testing in pediatric cancer patients across diverse clinical settings. We will compare the targeted pediatric cancer panel to germline whole exome sequencing (WES) of unselected childhood cancer patients. We will also compare an RNA/DNA targeted pediatric cancer panel versus WES, transcriptome sequencing and copy number array of FFPE tumor samples for the subset of patients with high-risk tumors. Exome sequencing is performed from a blood or saliva sample of the pediatric age (0-18) patient. We are building on our success completing the CSER program BASIC3 exome sequencing trial (which included 60% Hispanic and African-American patients from a single large academic center) in this large multi-institutional study of an even more diverse patient population from six pediatric oncology healthcare settings across Texas. Data from the Texas KidsCanSeq study will be submitted through the CSER Data Coordinating Center for access in NIH-supported databases.

  Study phs002378

• Whole Exome sequencing of Gingivo-buccal Cancer : ICGC-India Project_Batch04

  Whole Exome Sequencing of Gingivo-buccal Cancer: ICGC-India ProjectAs a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Exome of paired DNA samples – isolated from the tumor tissue and from the blood of 47 patients – have been performed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Whole exome sequencing is being performed at the National Institute of Biomedical Genomics, Kalyani.

  Study EGAS00001002852

• Epigenetic analysis of clear cell renal cell carcinoma using ChIP-seq

  To investigate the epigenetic landscape of clear cell renal cell carcinoma (ccRCC), we performed ChIP-seq data for the CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3, and HIF1A marks in the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as the HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and narrowPeak formats. Data were processed using the nf-core chipseq pipeline.

  Dataset EGAD50000001886