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• (ChIP-seq) Shifted assembly and function of mSWI/SNF family subcomplexes underlie targetable dependencies in endometriod carcinomas

  ChIP-seq data of 18 samples from the VOA1066 undifferentiated endometrial carcinoma cell-line with various pulldowns: BRG1 (abcam, ab110642, GR3255117-11), BRD9 (CST, E4Q3F, Lot 1), ARID1A (CST, D2A8U, Lot 4), SS18 (CST, D6I4Z, Lot 1), PBRM1 (CST, D3F70, Lot 3), GLTSCR1 (CST, E6I3A, Lot 1), H3K27ac (CST, C36B11, Lot 16), or none. Sample were either untreated or received doxycycline-induced ARID1A treatment. Samples were sequenced on Illumina NextSeq 500 using 37 bp single-end sequencing parameters. Raw fastq files, along with processed bigwig files containing normalized genomic coverage, and called narrow peaks, are included for each sample.

  Dataset EGAD50000001473

• 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

• scRNAseq data of human innate lymphoid cells (ILCs) and natural killer (NK) cells from fresh umbilical cord blood

  scRNA-seq was performed on the BD Rhapsody platform. ILCs (ILC1, ILC2, ILC3) and NK cells were bulk sorted from fresh cord bloods of 3 donors. The 4 samples containing ILCs and NK cells from each donor were stained with Sampletag antibodies (12 samples in total) before Abseq staining with the BD Immune Discovery panel and 6 additional antibodies was performed to better classify immune cell subsets. The sorted population were pooled before loading onto the BD Rhapsody cartridge. The manufacturer's protocol was followed for library construction and samples were sequenced on a Illumina NovaSeq 6000.

  Dataset EGAD50000001713

• McGill EMC Community projects Release 7 for cell line "hTERT RPE1"

  Complete reference epigenome (as defined by IHEC) of normal hTERT RPE1 cell line as well as hTERT RPE1 cell lines engineered to express EPC1-PHF1 and JAZF1-SUZ12 fusion proteins, found in Endometrial Stromal Sarcoma.

  Dataset EGAD00001007680

• ESGI-Identification of novel genes and mechanisms leading to Primary Ciliary Dyskinesia

  Approximately 80% of clinically clearly diagnosed patients suffering from primary ciliary dyskinesia (PCD) cannot be assigned to a specific gene defect. Despite extensive research on PCD and despite the increasing number of PCD genes and knowledge about their sites of action as e.g structural component or cytoplasmic pre-assembly factor, the biology of motile cilia and the pathomechanism leading to PCD is largely unknown. The aim of this study is to identify novel PCD related genes and processes relevant for motile cilia function.We will perform exome sequencing, aiming on the analysis of family trios. In these families, the diagnosis of PCD is secured, but the underlying gene defects has so far not been identified.

  Dataset EGAD00001001092

• 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

• 76 cancer and normal whole genomes from eleven SI-NET patients

  This dataset comprises of 76 cancer and normal whole genomes obtained from 11 SI-NET patients, in the form of two fastq files (forward and reverse reads) for each genome containing sequences generated by Illumina NovaSeq 6000 system.

  Dataset EGAD00001006161

• A whole-genome sequencing study for evolutionary history of Tibetans and their genetic adaptations to high altitude

  Due to a unique adaptation to high altitude, the Tibetan Plateau population has been the subject of much research interest. In this study, we conducted whole genome sequencing of 27 Tibetan individuals. Through our analysis, we inferred a detailed history of demography and revealed the natural selection of Tibetan population. We provided evidence of genetic separation between the two subpopulations of Han and Tibetans as early as 44 to 58 thousand years ago, replicated previously reported high altitude adaptation genes, including EPAS1 and EGLN1, and reported three new candidate genes, including PTGIS, VDR, and KCTD12.

  Study phs001338

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the regulation of B cell recptor repertoire in B cell subsets and its contribution to autoimmune diseases, B cell subsets from 36 Systemic Lupus Erythematosus(SLE), 90 Systemic Sclerosis(SSc), 85 Myositis(IIM), 21 Mixed Connective Tissue Disease(MCTD), 18 Sjogren's syndrome(SjS), 27 Rheumatoid Arthritis(RA), 23 Behcet's disease(BD), 18 Adult Onset Still���s Disease(AOSD), 24 ANCA-associated Vasculitis(AAV), 16 Takayasu���s Arteritis(TAK) and 137 healthy controls(HC) were collected (Naive_B, USM_B, SM_B, DN_B, Plasmablast. RNA-seq and BCR-mapping was performed with each B cell subset samples.

  Study JGAS000485

• RNA-Seq of Whole Blood from Patients with Intracranial Aneurysms

  Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size. However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imaging on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. We hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. We propose to use whole blood transcriptomes to develop a "one-stop" diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to develop and validate biomarkers to predict risk, as calculated by the currently-used metric of aneurysm size, the clinical PHASES score, and the RRS. Here, we collected blood samples from consented individuals who were receiving cerebral imaging at the Gates Vascular Institute (Buffalo, NY) for intracranial aneurysm. RNA extracted from blood samples (n=43) was subjected to RNA-sequencing and added to our existing database (n=44). When combined with our previous data, we had transcriptome data from 68 aneurysms (after additional sample filtering). This dataset was stratified into low- and high-risk according to IA size, PHASES score, and RRS score. Differentially expressed genes were identified and used to construct predictive models. Fastq files and basic demographic information for the 43 newly-sequenced intracranial aneurysm samples on this project will be available through dbGaP.

  Study phs003072

• ALS Compute

  Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of brain and spinal cord motor neurons. Half of ALS patients display cognitive symptoms of frontotemporal dementia (FTD); reciprocally, about 40% of FTD patients show motor neuron deficits, and approximately 15% develop overt ALS. The clinical overlap between ALS and FTD means that the two conditions are thought to represent a disease spectrum (ALS/FTD). In recent years, the identification of several genetic causes of ALS/FTD has contributed significantly to our understanding of disease pathogenesis. Unfortunately, one-third of the underlying genetic causes of familial cases and ~90% of sporadic cases of ALS/FTD remain unexplained. As such, there is a dire need to identify additional genetic factors contributing to ALS/FTD. Such studies require huge cohorts of harmonized whole genome sequencing (WGS) data sets from cases and controls. Currently, there are several major ongoing sequencing efforts for ALS patients. Numerous centers lead to inefficiency, especially in terms of overall costs. At a minimum, this includes the cost of high-performance computing, the storage of large data files, and the duplication of effort between groups. This lack of data harmonization between groups precludes sharing of genetic information and weakens collaborative efforts. The cost and logistics are also a barrier to attracting talented investigators to the ALS/FTD field. To overcome this unmet need, we have founded the ALS Compute project. We are centralizing the storage of ALS/FTD WGS data from every significant sequencing effort in the United States and beyond within a single Cloud environment. This approach will facilitate data harmonization and improve accessibility to the data. To accomplish this, we have made the data and the computational infrastructure available via the Terra platform hosted by NHGRI's Genomic Data Science Analysis, Visualization, and Informatics Lab-Space (AnVIL). This will allow researchers worldwide to access this wealth of data, develop new theories of the disease, and yield breakthroughs in our understanding of ALS/FTD.

  Study phs003184

• The Microbial Ecology of Bacterial Vaginosis: A Fine Scale Resolution Metagenomic Analysis

  Archived self-collected vaginal swabs were utilized from a pilot study of vaginal douching cessation (NIH/NIAID R03-AI061131). Thirty-nine non-pregnant, reproductive-age women who reported the use of vaginal douche products in the two months prior to screening were enrolled. Thirty-three of these successfully completed the 16-week longitudinal study. Participants self-collected vaginal swabs and smears twice weekly. We report sequences based on the analysis of 16S rRNA gene sequences amplified from whole genomic DNA isolated from the swabs. Bacterial vaginosis (BV) is defined by Gram's stain of vaginal fluid (Nugent's score =7). The large body of information generated will facilitate understanding of vaginal microbial community dynamics, the etiology of BV, and drive the development of better diagnostic tools for BV. Furthermore, it is hoped that the information will enable a more personalized treatment of BV and ultimately, prevent adverse sequelae associated with BV.

  Study phs000261

• Multi-Ethnic Study of Atherosclerosis (BioLINCC)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics).

  Study phs003288

• Integrative Molecular Characterization of Breast Cancer

  Version 1: We have performed integrative analyses of breast cancer tumors, including whole exome sequencing (WES) of tumor and normal pairs, whole transcriptome sequencing, and single-cell RNA sequencing (scRNA-seq) or single-nucleus RNA sequencing (snRNA-seq), to determine molecular correlates of response to novel and immune therapies. We have focused on dissecting the role of anticancer immunity in response to these therapies and understanding biological mechanisms underlying therapeutic resistance. The goal of this work is to advance a precision medicine approach to breast cancer treatment by identifying molecular biomarkers to improve therapy selection and novel therapeutic targets to overcome resistance. Version 2: We performed bulk whole exome sequencing (WES) of fresh frozen tissue from primary hormone receptor-positive breast cancer. Additionally, where available, we performed bulk whole transcriptome sequencing for the same individuals (tumor only). Additionally, we performed single cell sequencing on fresh frozen tissue from primary hormone receptor-positive breast cancer.

  Study phs002419

• A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

  Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

  Study EGAS50000001457

• STimage: Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data

  Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. Deep learning models are used to predict gene expression or classify cell types directly from images, offering significant clinical potential but still requiring improvements in interpretability and robustness. We present STimage as a comprehensive suite of models to predict spatial gene expression and classify cell types directly from standard H\&E images. STimage enhances robustness by estimating gene expression distributions and quantifying both data-driven (aleatoric) and model-based (epistemic) uncertainty using ensemble approach with foundation models. Interpretability is achieved through attribution analysis at single-cell resolution integrated with histopathological annotations, functional genes, and latent representations. We validated STimage across diverse datasets, demonstrating its performance across various platforms. STimage-predicted gene expression can stratify patient survival and predict drug response. By enabling molecular and cellular prediction from routine histology, STimage offers a powerful tool to advance digital pathology.

  Study EGAS50000001503

• Whole_genome_sequencing_in_a_multiplex_Crohn_s_disease_family

  In 2009 we identified a four-generation family with over 700 members and 41 affected with Crohn's disease (CD). At the time we sequenced the exome of 6 affected individuals but did not identify any coding variants which appear to explain the high prevalence of disease. Since then we have collected DNA from a large number of additional family members, genotyped linkage arrays on the entire family to refine genomic regions shared by identity by descent and genotyped affected and unaffected members at known CD risk loci identified by Genome Wide Association Studies (GWAS). These analyses have confirmed that a significant unexplained excess of disease remains after accounting for all known genetic factors, and that several regions of the genome are shared by a large fraction of affected individuals. We therefore perform whole genomes sequencing from 8 individuals which will allow us to impute the complete sequence of nearly all the members of the two largest and most severely affected branches of the family.

  Study EGAS00001000060

• Tracking the genomic evolution of esophageal adenocarcinoma through neoadjuvant chemotherapy

  Esophageal adenocarcinomas (EACs) are associated with dismal prognosis. Deciphering the evolutionary histories of this disease may shed light on therapeutically tractable targets and reveal changing mutational processes during the disease course and following neoadjuvant chemotherapy (NAC). We exome sequenced 40 tumor regions from 8 patients with operable EACs both before and after platinum-containing NAC. This revealed the evolutionary genomic landscape of EACs with the presence of heterogeneous driver mutations, parallel evolution, early genome doubling events and an association between high intratumor heterogeneity and poor response to NAC. Multi-region sequencing demonstrated a significant reduction in T>G mutations within a CTT context when comparing early and late mutational processes and the presence of a platinum signature with enrichment of C>A mutations within a CpC context following NAC. EACs are characterized by the presence of amplifications containing targetable oncogenes present before and after chemotherapy that may provide a rationale for future therapeutic approaches.

  Study EGAS00001001254

• The genomic landscape of cutaneous squamous cell carcinoma from immunosuppressed and immunocompetent patients reveals common drivers and a novel mutational signature associated with chronic azathioprine exposure

  Cutaneous squamous cell carcinoma (cSCC) has a high tumour mutational burden (50 mutations per megabase DNA pair). Combining whole exome analyses from 40 primary cSCC tumours, comprising 20 well differentiated and 20 moderately/poorly differentiated tumours, with accompanying clinical data from a longitudinal study of immunosuppressed and immunocompetent patients, coupled with integration of independent gene expression studies has allowed the identification of commonly mutated genes and altered pathways and processes. Mutational signature analysis revealed the presence of a novel signature (signature 32), which was found exclusively in the tumours from immunosuppressed patients who had been exposed to azathioprine. Characterisation of a panel of 15 keratinocyte cancer cell lines derived from tumours from immunocompetent and immunosuppressed patients reveals that they accurately reflect the mutational signatures and genomic alterations of primary tumours and provide a resource for the validation of tumour drivers and therapeutic targets.

  Study EGAS00001002612

• 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

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• Colorectal adenomas, NKI-AvL TGO series Stool-Proteomics

  Colorectal cancer (CRC) develops from normal epithelium, through a benign precursor lesion called adenoma, by accumulation of genetic alterations affecting oncogenes and tumour suppressor genes. About 5% of colorectal adenomas are estimated to progress to CRC. However, it is important to identify which adenomas actually are at high-risk of progression, because these should serve as intermediate endpoints for e.g. CRC screening programs. In clinical practice, adenomas with a size of ≥10 mm, villous component and/or high-grade dysplasia, called advanced adenomas, are considered high-risk, although this classification lacks solid evidence. Specific DNA copy number changes are associated with adenoma-to-carcinoma progression.For this tissue dataset, we applied low-pass whole genome sequencing to 98 non-advanced and advanced adenomas. These adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Study EGAS00001002953

• Cross-species Comparison Reveals Therapeutic Vulnerabilities Halting Glioblastoma Progression

  The growth of a tumor is tightly linked to the distribution of its cells along a continuum of activation states. Here, we systematically decode the activation state architecture (ASA) in a glioblastoma (GBM) patient cohort through comparison to adult murine neural stem cells. Modelling of these data forecast how tumor cells organize to sustain growth and identifies rate of activation as the main predictor of growth. Accordingly, patients with a higher quiescence fraction exhibit improved outcomes. Further, DNA methylation arrays enable ASA- related patient stratification. Comparison of healthy and malignant gene expression dynamics reveals dysregulation of the Wnt- antagonist SFRP1 at the quiescence to activation transition. SFRP1 overexpression renders GBM quiescent and increases overall survival of tumor-bearing mice. Surprisingly, it does so through reprogramming the tumor’s stem-like methylome into an astrocyte- like one. Our findings offer a framework for patient stratification with prognostic value, biomarker identification, and therapeutic avenues to halt GBM progression.

  Study EGAS00001008155

• Comparison of sequencing assays for sensitive detection of circulating tumour DNA in stage IA-IV breast cancer

  This study compared different assays for the detection of circulating tumour DNA (ctDNA) in serial plasma from stage IA-IV breast cancer patients, targeting structural variants (SVs), single nucleotide variants (SNVs) and/or somatic copy-number aberrations (SCNAs). SV-multiplex PCR, SNV-/SV-hybrid capture, and different depths of whole-genome sequencing (WGS) were used to evaluate ctDNA levels, demonstrating concordant results. SNV-hybrid capture targeting 1,347-7,491 mutations was the most sensitive assay, detecting 67% (36/54) of samples down to an allele fraction (AF) of 0.00024%. SV-multiplex PCR, targeting 21-47 mutations, detected 63% (34/54) of samples down to 0.00047% AF and has potential as a clinical assay.

  Dataset EGAD00001008589

• Region-Specific Neural Stem Cell Lineages Revealed by Single-Cell RNA-Sequences from Human Embryonic Stem Cells

  During development of the human brain, multiple cell types with diverse regional identities are generated. Here we report a system to generate early human brain forebrain and mid/hindbrain cell types from human embryonic stem cells (hESCs), and infer and experimentally confirm a lineage tree for the generation of these types based on single-cell RNA-Seq analysis. We engineered SOX2Cit/+ and DCXCit/Y hESC lines to target progenitors and neurons throughout neural differentiation for single-cell transcriptomic profiling, then identified discrete cell types consisting of both rostral (cortical) and caudal (mid/hindbrain) identities. Direct comparison of the cell types were made to primary tissues using gene expression atlases and fetal human brain single-cell gene expression data, and this established that the cell types resembled early human brain cell types, including preplate cells. From the single-cell transcriptomic data a Bayesian algorithm generated a unified lineage tree, and predicted novel regulatory transcription factors. The lineage tree highlighted a prominent bifurcation between cortical and mid/hindbrain cell types, confirmed by clonal analysis experiments. We demonstrated that cell types from either branch could preferentially be generated by manipulation of the canonical Wnt/beta-catenin pathway. In summary, we present an experimentally validated lineage tree that encompasses multiple brain regions, and our work sheds light on the molecular regulation of region-specific neural lineages during human brain development.

  Study phs001205

• Multi-omics bulk and single-cell profiling of epithelioid sarcoma

  Epithelioid sarcoma (EpS) is an aggressive sarcoma, characterized by the loss of SMARCB1 expression. EpS is traditionally classified as distal or proximal according to clinicopathological features, but its molecular characteristics remain largely unknown. To establish an EpS molecular classification and uncover determinants of inter- and intra-patient heterogeneity in EpS, we used multi-omics profiling and integrated the genomic, transcriptional and methylome landscapes with single-cell RNA sequencing on fresh samples as well as spatial transcriptomics. We identified two molecular subtypes of EpS: “distal-like” and “proximal-like”, which were distinct from the histological subtypes. Distal-like tumors include all morphological distal subtypes and a subset of proximal and hybrid EpS. They express a specific molecular single-cell derived epithelial-to-mesenchymal transition signature, which associates with improved patient survival and includes Desmoglein 2 (DSG2), which we identify as a potential routine immunohistochemical biomarker to improve diagnosis. Distal-like EpS also display increased peri-tumoral CD8+ T cell infiltrates and specific tumor-immune cell interactions. Conversely, proximal-like EpS harbor a higher inter-tumoral molecular heterogeneity with some cases resembling other SMARCB1-deficient tumors by DNA methylation profiling, and increased intra-tumoral pro-tumoral macrophage infiltrates. Our study introduces a novel molecular classification of EpS with prognostic value, associated diagnostic biomarkers and distinct tumor immune microenvironments, which extends beyond traditional clinicopathological classification. This paves the way for precision medicine-based therapeutic strategies for patients with EpS.

  Study EGAS50000000973

• 1M-scBloodNL

  Here we present the 1M-scBloodNL study, in which we performed single-cell RNA-seq on 120 individuals of the Northern Netherlands population cohort Lifelines. For each individual peripheral blood mononuclear cells (PBMCs) were sequenced in an unstimulated condition, and after 3 and 24 hour in vitro stimulation with C. albicans (CA), M. tuberculosis (MTB) and P. aeruginosa (PA), totalling approximately 1.3 million cells. scRNA-seq was conducted with the 10X Genomics 3'-end v2 (72 libraries) and v3 (33 libraries) technology. In general, each library contains PBMCs from 8 donors and 2 different stimulation-timepoint combinations. Donors were demultiplexed using a combination of SoupOrCell (https://www.nature.com/articles/s41592-020-0820-1) and genotype information to assign the correct donor to a donor-specific cell cluster.

  Dataset EGAD00001007764

• Nala TAS-LRS PGx Study

  Sequencing was performed on the PromethION Flow Cell R10 (M version) using the P2 Solo Sequencer (MinION release 24.02.16). The library was divided into three portions and loaded in a tapered manner across three time points. At the first time point, the initial portion of the library was loaded, and sequencing began in whole-genome mode (without adaptive sampling), to monitor QC (N50 within the expected range). After one hour, adaptive sampling was activated. A custom BED file was used to define the target regions (N=326). Each region was extended by 20 kb upstream and downstream, and overlapping regions were merged into non-redundant intervals using bedtools43, covering a total of 1.3% of the human genome. At the second time point (20–24 hours after sequencing began, or when fewer than 2000 pores remained active), the flow cell was washed following ONT’s Flow Cell Wash Kit protocol, and the second portion of the library was loaded. At the third time point (40–48 hours), the second portion of the library was retrieved, and merged with the third portion. The flow cell was washed and reloaded with the mixed library. POD5 files were basecalled using Dorado v0.8.1 in super-accuracy (SUP) mode with the dna_r10.4.1_e8.2_400bps_SUP@v5.0.0. Reads from the initial 1 h Whole Genome Sequencing (WGS) and subsequent 72 h adaptive sampling were filtered for Q-scores >10. Passing reads were demultiplexed using Dorado’s demux function, then combined per sample and mapped to the GRCh38 reference genome using Minimap2 v2.22. Files were converted to CRAM using samtools.

  Dataset EGAD50000001609

• High Density SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation

  This research builds upon an extensive resource of melanoma cases and hospital based controls collected over several years at the U.T. M.D. Anderson Cancer Center. The goal of this research is to identify novel susceptibility and outcome-related genes for melanoma using a systematic genome-wide association-based approach. Our goal is to conduct high-density SNP association and outcome studies. This dbGaP study contains samples from 2000 European ancestry cases and 1000 European ancestry controls using the Illumina OMNI1-Quad SNP chip. As a part of an ongoing R01 project, we have epidemiological data together with candidate gene results for 1000 of the melanoma cases and the controls. With regard to the outcome aspect of our design, as part of our melanoma Specialized Program of Research Excellence (SPORE) grant, our MelCore database contains comprehensive, prospectively maintained clinical information from all melanoma patients included in the study cohort, including primary tumor histopathology and staging information, standard and investigational blood tumor markers, details of surgical and systemic therapies, and extensive follow-up information, including time to relapse or recurrence, pattern of recurrence and survival duration. Finally, we intend to collaborate with the GenoMEL collaboration so we can jointly evaluate each other's findings. The goal of our analysis will be to identify novel genetic factors predisposing the development of melanoma, as well as genetic factors controlling melanoma stage at presentation, recurrence and progression. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to melanoma through large-scale genome-wide association studies of 2000 European ancestry cases and 1000 European ancestry controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000187

• MILK-Omics: Systems Biology of Human Milk and Its Links to Maternal and Infant Health

  The primary objective of the project is to generate a systems-level view of human milk in the context of healthy mothers and their term infants. The study uses biospecimens and clinical data from the Mothers and Infants LinKed for Healthy Growth Study (MILk Study), a prospective observational cohort of approximately 500 exclusively breastfeeding women and their infants who are followed to 6 months of age. The project focuses on mature milk samples collected at 1 month postpartum and infant gut microbiome samples collected at 1 and 6 months of age. Specific Aim 1 is to identify maternal genetic and clinical factors that shape human milk gene expression. Using bulk and single-cell RNA sequencing of the milk cell pellet and genotypes from maternal DNA, we will identify novel genetic determinants of the milk transcriptome and assess potential modification of these genetic associations by gestational weight gain, diet, and other clinical factors. Specific Aim 2 is to describe key features of the normative human milk biosystem and their interactions with one another. Specifically, machine learning techniques will be used to characterize interaction networks and correlational structures among the following features of human milk: transcriptomics, microbiomes, oligosaccharides, metabolomics, lipidomics, and milk macronutrient composition. Specific Aim 3 is to establish how the milk biosystem is related to variation in infant gut microbiomes and health. dbGaP will house the maternal genotype and milk transcriptomics data.The infant microbiome sequence data are associated with BioProject PRJNA1019702.

  Study phs003408

• Tumor-reactive heterotypic CD8 T cell clusters from clinical samples

  Emerging evidence suggests a correlation between CD8+ T cell-tumor cell proximity and anti-tumor immune response. However, it remains unknown whether these cells exist as functional clusters that can be isolated from clinical samples. By conventional and imaging flow cytometry, we show here that from 21/21 human melanoma metastases, we could isolate heterotypic clusters, comprising CD8+ T cells interacting with one or more tumor cells and/or antigen-presenting cells (APCs). Single-cell RNA-sequencing revealed that T cells from clusters were enriched for gene signatures associated with tumor reactivity and exhaustion. Clustered T cells exhibited increased TCR clonality indicative of expansion, while TCR-matched T cells showed more exhaustion and co-modulation when conjugated to APCs than to tumor cells. T cells that were expanded from clusters ex vivo exerted on average 9-fold increased killing activity towards autologous melanomas, which was accompanied by enhanced cytokine production. Upon adoptive cell transfer into mice, T cells from clusters showed improved patient-derived melanoma control, which was associated with increased T cell infiltration and activation. Together, these results demonstrate that tumor-reactive CD8+ T cells are enriched in functional clusters with tumor cells and/or APCs and that they can be isolated and expanded from clinical samples. Typically excluded by single cell gating in flow cytometry, these distinct heterotypic T cell clusters serve as a valuable source to decipher functional tumor-immune cell interactions, while they may also be therapeutically explored.

  Study EGAS50000000785

• RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.

  Background: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called `epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. Results: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder. Conclusions: Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity.

  Study EGAS00001002484

• The long term effects of chemotherapy on normal blood - WGS dataset

  In developed countries, ~10% of individuals are exposed to systemic chemotherapy for cancer and other diseases. Many chemotherapeutic agents act by increasing DNA damage in cancer cells, hence triggering cell death. However, there is limited understanding of the extent and consequences of collateral DNA damage to normal tissues. To investigate the impact of chemotherapy on mutation burdens and cell population structure of a normal tissue we sequenced blood cell genomes from 23 individuals, aged 3-80 years, treated with a range of chemotherapy regimens. Substantial additional mutation loads with characteristic mutational signatures were imposed by some chemotherapeutic agents, but there were differences in burden between different classes of agent, different agents of the same class and different blood cell types. Chemotherapy also induced premature changes in the cell population structure of normal blood, similar to those of normal ageing. The results constitute an initial survey of the long-term biological consequences of cytotoxic agents to which a substantial fraction of the population is exposed during the course of their disease management, raising mechanistic questions and highlighting opportunities for mitigation of adverse effects.

  Dataset EGAD00001015339

• Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

  Background: Glioblastoma (GBM) harbors a highly immunosuppressive tumor microenvironment (TME) which influences glioma growth. Major efforts have been undertaken to describe the TME on a single-cell level. However, human data on regional differences within the TME remain scarce. Goals: we performed single-cell RNA sequencing (scRNAseq) on paired biopsies from the tumor center, peripheral infiltration zone and blood of five patients with primary GBM Details: This EGA study includes raw data sequencing files for the scRNA-seq samples. The processed data (output from Alevin, UMI count matrix and cell metadata) are available from GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE197543

  Study EGAS50000000302

• The Genomic Landscape of Mongolian Hepatocellular Carcinoma

  Background and Hypotheses: Mongolia has the highest reported incidence of - and mortality from - hepatocellular carcinoma (HCC) in the world, which is between three and seven times higher than that observed in other high-incidence populations, such as South Korea, Thailand, and China. Although its causative factors and underlying tumor biology remain unknown, risk factors such as chronic hepatitis B virus and/or hepatitis C virus infection are highly prevalent. Moreover, Mongolia has an extraordinarily high prevalence of hepatitis delta virus (HDV), more than ten times above the global estimate, which we hypothesize as a major driver of Mongolian hepatocarcinogenesis. By performing a comprehensive and integrative genomic characterization, we aimed to identify robust molecular subclasses and driver features informative of the etiology and progression of the disease. This study, the first one of this nature ever to be conducted on a Mongolian cohort, identifies similarities to previous studies performed on other populations (which reflect general characteristics of liver carcinogenesis) as well as unique features of Mongolian HCC. Study Design and Methods: Clinical information and paired tumor/non-tumor liver tissue samples were obtained from 76 HCC patients undergoing surgery at the National Cancer Center of Mongolia. Transcriptome sequencing and whole exome sequencing were performed on all tumor and non-tumor samples, followed by bioinformatics processing and quality control. Consensus clustering and regularized Cox regression analyses were performed on transcriptome data. Driver mutations and mutational signatures were assessed. These results were compared to those from 373 HCC patients of different races and ethnicities and diverse etiologies. Furthermore, molecular subclass gene signatures from multiple previous studies were assessed for validation. Results and Conclusions: Using a transcriptomics-based unsupervised approach, we identified four molecular subclasses among Mongolian HCC cases, which were associated with different patient survival outcomes. These molecular subclasses were mapped to signatures reported in other HCC cohorts, showing significant associations consistent with survival outcomes. A supervised analysis determined risk scores strongly associated with survival, consistent with the four molecular subclasses. Mutational signature analysis using recently published COSMIC and Environmental Agents Compendia identified signatures with distinct prevalence among HDV+ and HVD- groups. Signatures differentially associated with HDV+ include mutational patterns linked to alkylating agents (such as temozolomide), tobacco chewing and exposures to 1,8-Dinitropyrene and furan, whereas HDV- appeared differentially associated with aristolochic acid II. In addition to common driver mutations (TP53, CTNNB1) frequently found in pan-cancer analysis, Mongolian HCC exhibits several unique drivers (most notably GTF2IRD2B, PNRC2, and SPTA1), the latter of which may be linked to HDV infection. These results suggest the existence of new molecular mechanisms at play in Mongolian hepatocarcinogenesis.

  Study phs002000

• Targeted sequencing data for various human bulk tissues

  To estimate the contribution of early embryogenic cell lineages in adult tissues, we performed deep targeted sequencing on 379 bulk tissues from various organs of the five individuals (DB3, DB6, DB8, DB9, DB10). Of the 441 early embryonic mutations targeted, 411 mutations could have high-quality baits designed for them. DNA libraries were prepared by SureSelectXT Library Prep Kit (Agilent), hybridized to the appropriate capture panel, multiplexed on flow cells, and subjected to paired-end sequencing (150-bp reads) on the NovaSeq 6000 platform (Illumina) with a mean ~2,900x depth of coverage for the early mutations. Sequence reads were trimmed and mapped to the human reference genome (GRCh37) using the BWA-MEM algorithm.

  Dataset EGAD00001007704

• WGS and WTS data of patients diagnosed with MEITL.

  WGS from 4 patients, WTS from only 3 patients (insufficient tissue from 4th patient for WTS). Whole-genome sequencing (WGS) was performed for 60 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000. Whole-transcriptome sequencing (WTS): Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on Illumina HiSeq 2500 with 2x101 bp read length. Description of prefix used in filenames: T: Tumor samples N: Normal samples (Blood) P: PDX samples

  Dataset EGAD00001005341

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• RNA-Seq of human longitudinal whole blood samples from PCR-positive and PCR-negative adults following controlled inoculation with Influenza A H3N2 virus.

  Understanding of the transcriptomic profile of individuals in early influenza infection is limited. To investigate this, longitudinal whole-blood samples (n=178) were taken from adult participants following controlled inoculation with Influenza A H3N2 virus (sampling at baseline (0) and days 1, 2, 3, 7, 10 and 14 post-challenge). Most participants became influenza PCR-positive; a minority remained PCR-negative. Total RNA was extracted from PAXgene tubes before undergoing globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced using Illumina NovaSeq 6000.

  Dataset EGAD50000000956

• Ribosomal profiling on Epstein-Barr virus transformed B-lymphoblastoid cell lines.

  This dataset contains Ribo-seq BAM files of Epstein-Barr virus-transformed B-lymphoblastoid cell lines from six individuals (HG00114, HG00282, NA12005, NA12044, NA12717 and NA12751) of the GEUVADIS Project. For each EBV-LCL, 20 million cells were treated with 2 μg/ml harringtonine and 100 μg/ml cycloheximide. After lysing cells in lysis buffer supplemented with 100 μg/ml cycloheximide, ribosome complexes were purified by density purification. Small RNA molecules were isolated using the NucleoSpin miRNA Kit (Bioke, Leiden, Netherlands), followed by RNA PAGE gel separation. Universal linkers were added after dephosphorylation. After reverse transcription, the cDNA was circularized and, after ribosomal RNA depletion, barcoded and sequenced on Illumina NextSeq 500.

  Dataset EGAD50000000465

• Transcriptomic profiling of T cells following ABHD11 inhibition

  This dataset contains paired-end RNA sequencing data from human T cells treated with ML226, a selective ABHD11 inhibitor, and matched vehicle controls. The experiment was designed to investigate the role of ABHD11 in sterol metabolism and its impact on T cell effector function and autoimmunity. Samples were collected across biological replicates following 24-hour treatment, and RNA was extracted for high-throughput sequencing. Sequencing was performed using an Illumina platform. The dataset supports analysis of differentially expressed genes, alternative transcript usage, and pathway-level effects of ABHD11 inhibition. This dataset is part of the study titled "ABHD11 inhibition drives sterol metabolism to modulate T cell effector function and alleviate autoimmunity".

  Dataset EGAD50000001845

• Dataset for upper_gastrointestinal_tumor-RNA

  Rare cancer sequencing data of 44 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008853

• CD19 CAR-T cells from non-Hodgkin's lymphoma patients

  The samples across 17 NHL patient samples with the CD19 CAR-T treatments are sequenced in 10x genomics. Refer to the manuscript supplementary tables and "https://github.com/hwanglab/hwanglab_2021_tigitCarT" for the sequencing sample sheets, the patient clinical information, processed data, and source codes.

  Dataset EGAD00001007741

• RNA-seq and Hi-C data of a chromothripsis patient's iPS cells

  This dataset contains RNA-seq and Hi-C data files of induced pluripotent stem (iPS) cells and iPS cell-derived neural progenitors (NPCs) derived from a germline chromothripsis patient and both parents. iPS cells of the patient (cell lines 14 and 15), the father (lines 23 (with two replicates) and 32) and mother (line 30) were differentiated to NPCs and RNA was collected on day 0, day 7 and day 10 of differentiation. In addition, Hi-C data for two iPS cell-derived NPC lines from the patient (14 and 15) and two lines from the father (23 and 32) was generated.

  Dataset EGAD00001002242

• Whole genome sequencing of multiple myeloma patient samples.

  Tumor (CD138+ plasma cells) and non-tumor (peripheral blood white cells or stem cell harvest) DNA from patients with a plasma cell dyscrasias were sequenced. Whole genome sequencing using high molecular weight DNA was performed using the 10X Genomics Chromium platform on either a HiSeq4000 or NovaSeq (Illumina) using 100 to 150 bp paired-end reads. The dataset consists of 111 patients, and 223 samples in total (matched tumor and control per patient; one patient had 2 tumor samples sequenced). Diseases consisted of 2 MGUS patients, 8 SMM patients, 91 newly diagnosed myeloma patients, 1 previously treated patient, 4 relapsed MM patients, and 5 PCL patients. Paired RNA-seq data are available for 81 of the samples under study EGAS00001003411.

  Dataset EGAD00001004452

• Investigating low frequency variants in CAD/MI cases, controls and pedigrees using whole exome sequencing and custom pulldowns

  The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

  Dataset EGAD00001000400

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

  RNA sequencing data from cancer patient-derived organoids. 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 EGAD00001015470

• Cellular Profiling Identifies Targetable T Cell Phenotypes in Lymphocytic Variant Hypereosinophilic Syndrome

  Lymphocytic variant hypereosinophilic syndrome (LHES) is driven by aberrant Th2‑skewed lymphocyte clones that promote tissue eosinophilia. We performed multimodal single‑cell RNA‑sequencing (scRNA‑seq), cell‑surface protein (ADT) profiling, and paired αβ‑TCR sequencing on peripheral‑blood mononuclear cells (PBMCs) from two clinically characterized LHES patients and one idiopathic HES control. One LHES patient was sequenced at two timepoints, pre-JAK inhibitor treatment and post-JAK inhibitor treatment. Single‑cell regulatory‑network inference (SCENIC), CellChat ligand–receptor modelling, and scRNA variant calling were integrated with flow‑cytometric validation and 5,000× amplicon sequencing. Two clonally expanded CD3‑CD4⁺ central‑/effector‑memory T‑cell clusters were observed exclusively in LHES. These cells showed Th2‑associated regulons (GATA3, BATF, MAF), high expression of CCR4, CD52, PTGDR2 and IL13, and down‑regulation of CD247 (CD3ζ), a mechanism experimentally confirmed to abolish surface CD3/TCR. Autocrine IL‑7 signaling, predicted by CellChat, provides an antigen‑independent proliferative cue. Therapeutically actionable targets (CCR4, CD52, IL‑5, IL‑7, TNF) were prioritized; one refractory patient achieved complete clinical and cytologic remission after mogamulizumab (anti‑CCR4) therapy. Longitudinal sequencing revealed clonal evolution with acquisition of a STAT3 p.G618R mutation under JAK‑inhibition, highlighting a resistance mechanism. Raw scRNA‑seq (5′ cDNA, VDJ, ADT) data, and sample‑level metadata will be distributed through dbGaP. These resources provide the first high‑resolution immune atlas of LHES and a framework for rational, precision immunotherapy in eosinophilic disorders.

  Study phs004041

• Genetic-epigenetic tissue mapping for plasma DNA: applications in prenatal testing, transplantation and oncology

  We developed Genetic-Epigenetic Tissue Mapping (GETMap) to determine the tissue composition of plasma DNA carrying genetic variants not present in the constitutional genome through comparing their methylation profiles with relevant tissues.

  Dataset EGAD00001007041

• Genomic analysis for intrahepatic cholangiocarcinoma

  Intrahepatic cholangiocarcinomas (iCCs) are characterized by their rarity, difficulty in diagnosis, and overall poor prognosis. We performed comprehensive genomic characterization of treatment-naive iCC. This study reports a large-scale genomic analysis of iCC. The findings could assist in patient stratification with iCCs and in developing rational therapeutic strategies.

  Dataset EGAD00001008557