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• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Dataset EGAD00001015535

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

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

  Dataset EGAD00001003602

• National Eye Institute (NEI) Age-Related Eye Disease Study (AREDS)

  The Age-Related Eye Disease Study (AREDS) was initially designed as a long-term multi-center, prospective study of the clinical course of age-related macular degeneration (AMD) and age-related cataract. In addition to collecting natural history data, AREDS included a clinical trial of high-dose vitamin and mineral supplements for AMD and a clinical trial of high-dose vitamin supplements for cataract. AREDS participants were 55 to 80 years of age at enrollment and had to be free of any illness or condition that would make long-term follow-up or compliance with study medications unlikely or difficult. On the basis of fundus photographs graded by a central reading center, best-corrected visual acuity and ophthalmologic evaluations, 4,757 participants were enrolled in one of several AMD categories, including persons with no AMD. The clinical trials for AMD and cataract were conducted concurrently. AREDS participants were followed on the clinical trials for a median time of 6.5 years. Subsequent to the conclusion of the clinical trials, participants were followed for an additional 5 years and natural history data were collected. The AREDS research design is detailed in AREDS Report 1. AREDS Report 8 contains the mainline results from the AMD trial; AREDS Report 9 contains the results of the cataract trial. Blood samples were also collected from 3,700+ AREDS participants for genetic research. Genetic samples from 600 AREDS participants (200 controls, 200 Neovascular AMD cases, and 200 Geographic Atrophy cases) were selected using data available in March 2005 and then were evaluated with a genome-wide scan. These data, as well as selected phenotypic data, were made available in the dbGaP. DNA from AREDS participants, which is currently being stored in the AREDS Genetic Repository, is available for research purposes. However, not all of the 3,700+ AREDS participants who submitted a blood sample currently have DNA available. In addition to including the data from the genome-wide scan on the 600 original samples, this second version of the AREDS dbGaP database provides a comprehensive set of data tables with extensive clinical information collected for the 4,757 participants who participated in AREDS. The tables include information collected at enrollment/baseline, during study follow-up, fundus and lens pathology, nutritional estimates, quality of life measures and measures of morbidity and mortality. In November 2010, over 72,000 high quality fundus and lens photographs of 595 AREDS participants (of the original 600 selected for the genome-wide scan) were made available in the AREDS dbGaP. In addition to the genome-wide scan data, the fundus and lens grading data for these participants are also available through the AREDS dbGaP. Details about the ocular photographs that are available may be found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs". In January 2012, a measure of daily sunlight exposure was added in a separate "sunlight" table. Furthermore, the "followup" table has been revised. The visual acuity for the right eye was inadvertently missing at odd-numbered visits (01, 03, 05, etc.). This data is now part of the table. In February 2014 over 134,500 high-quality fundus photographs (macular field F2) of 4613 AREDS participants were added to the existing AREDS dbGaP resource. The AREDS dbGaP image archive already contains over 72,000 high quality fundus and lens photographs of 595 AREDS participants for whom dbGaP-accessible genotype data exist. Information about the available ocular photographs found in the document "Age-Related Eye Disease Study (AREDS) Ocular Photographs" has been updated with an addendum. It is hoped that this resource will better help researchers understand two important diseases that affect an aging population. These data may be applied to examination and inference on genetic and genetic-environmental bases for age-related diseases of public health significance and may also help elucidate the clinical course of both conditions, generate hypotheses, and aid in the design of clinical trials of preventive interventions. Definitions of Final AMD Phenotype Categories Please see phd001138.1 for a detailed description of how AREDS participants' final AMD phenotype was categorized. User's Guide for AREDS Phenotype Data A detailed User's Guide for the AREDS phenotype data is available. This User's Guide is meant to be a comprehensive document which explains the complexities of the AREDS data. It is recommended that all researchers using AREDS phenotype data make use of this User's Guide.

  Study phs000001

• Assessment of Health-related Quality of Life in Rare Kidney Stones

  The purpose of this study is to learn about Health-related Quality Of Life (HRQoL) in patients enrolled in the Rare Kidney Stone Consortium (RKSC) registries. Quality of life studies look at different aspects of both physical and mental components of people's lives. HRQoL data for people affected by kidney stones are not currently available for people followed over time. All participants enrolled in the RKSC registries will be invited, via email or postal mail, to participate in this study. Health-related quality of life in people with rare kidney stones enrolled in the RKSC registries will be measured. Instruments used in this study are the SF-10 for pediatric participants and SF-36v2 for adult participants. The surveys will be completed online. Participants without a computer or internet access will participate using a paper version of the survey. These surveys will be done at enrollment and annually thereafter. The SF-36v2 includes 36 questions and is estimated to take 15 minutes for its completion, while the SF-10 includes 10 questions and could be completed in 5 minutes. The research questions are: Assessment of HRQoL in patients with rare kidney stones. Comparison of HRQoL results between rare kidney stone formers, general population and other populations with relevant chronic diseases. Comparison of HRQoL results in the same populations affected by different stones and analyzed with attention to the effects of various factors included in the disease registry, such as stone activity, burden of urologic interventions, medication and other treatments. Evaluation of HRQoL and its trends over time in patients undergoing treatment for rare kidney stones. About this study: The plan is to have 400 participants from all four registries take part in this multi-center study. The assessment of your HRQoL will be done annually for 5 years.

  Study phs001770

• Uncovering RNA Signatures of C9orf72-Linked ALS and Related Disorders

  Substantial clinical and pathological variability has been reported in patients carrying an expanded repeat in C9orf72, who are generally diagnosed with amyotrophic lateral sclerosis (ALS) and/or frontotemporal dementia (FTD). Emerging evidence suggests that C9orf72 expression, RNA foci, and dipeptide-repeat proteins contribute to C9orf72-related diseases; however, the majority of the clinicopathological variability remains unexplained. We hypothesize that RNA sequencing (RNA-Seq) might reveal individual genes or groups of highly correlated genes (modules) that could account for this variability, which may help to identify much-needed druggable targets and/or biomarkers. Our preliminary studies performed in the frontal cortex, where we compared C9orf72 expansion carriers to (disease) controls, demonstrated that the top differentially expressed gene was C9orf72 itself. We also noticed that differentially expressed genes were enriched for the endocytosis pathway, which is consistent with the reported function of the C9orf72 protein in vesicle trafficking. Furthermore, we detected a module enriched for vesicular pathways, and additionally, we discovered an association with survival after onset for several promising candidates involved in vesicular transport. To find new therapeutic targets and biomarkers, here we have completed RNA-Seq on an increased number of samples to examine another relevant region: the cerebellum. As such, we performed RNA-Seq on a well-characterized cohort of C9orf72 expansion carriers, patients without this expansion, and control subjects without neurological diseases. We used multivariable linear regression models for gene-level analysis, weighted correlation network analysis for module-level analysis, and leafcutter for splicing analysis. Using the cerebellar RNA-Seq data, we found a large number (>6,000) of differentially expressed genes, with a notable increase in expression of homeobox genes in C9orf72 expansion carriers, as well as many gene modules that were associated with C9orf72 expansion status. Additionally, using leafcutter, we detected over 1,000 differential splicing events and an increase in the number of cryptic splicing events in C9orf72 expansion carriers.

  Study phs003065

• The Sea Islands Genetic Network (SIGNET): Identifying genetic contributors to diabetes and dyslipidemia in African Americans

  Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations, however most do not have a major impact on diabetes risk in populations of African descent. The African American (AA) population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture, and in general, consume a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for T2DM in AA compared with European American (EA) is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS. The Specific Aims are to: 1) Identify genetic risk factors for type 2 diabetes utilizing DNA samples and data from the Sea Island Families Project, Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited from SC, GA, NC, and AL; and a GWAS approach; 2) Identify genetic contributors to lipoprotein subclasses in African Americans using the lipoprotein subclass profile (particle size and concentration for multiple subclasses of VLDL, LDL, and HDL) assessed by NMR at LipoScience, Inc., and the GWAS data from Aim 1. The rationale for this project is that identification and validation of novel pathophysiological pathways and informed selection of candidate genes for diabetes risk will inform development of new, targeted prevention and treatment strategies in this underserved, high risk population.

  Study phs000433

• A Phase 2 Study of Tipifarnib in Large Granular Lymphocyte (LGL) Leukemia

  LGL leukemia can be divided into three subsets including the following: αβ or γδT-LGL and NK-LGL leukemia. All three subtypes will be enrolled using a two-stage design. The primary endpoint of the study is assessment of overall clinical response. Correlative laboratory studies will be performed aimed at determining the mechanism of response to treatment. Thirteen participants will be accrued in the first stage at a dose of 300 mg BID administered intermittently every other week (i.e., 7 days on and 7 days off). If there are two or more responders, the protocol will be extended to a second stage of the study and accrual will be extended to 25 evaluable participants. Allowing for 10% rate of ineligibility due to unexpected events and dropout, we will accrue 14 patients in the first stage and 27 patients in total. Participants that withdraw from the study for reason unrelated to toxicity, will be replaced. There are two potential stopping rules for toxicity. If 3 or more participants out of the 13 enrolled in the first stage experiences grade IV neurotoxicity, the study will be stopped due to excessive toxicity. Dose reductions have been incorporated for hematologic toxicity. Treatment of T and NK LGL leukemia with immunosuppressive agents such as low-dose methotrexate generally require from four to six months for a clinical response and sometimes much longer. Therefore, in participants who show clinical improvement with less than grade three toxicity, tipifarnib treatment will be continued for as many as four additional months (12 months total). After the first 8 months, response will be assessed. The protocol treatment will be discontinued in participants with progression of disease. A long-term follow up will be performed for five years in patients that receive a complete clinical response. The long-term follow up will consist of vital signs, weight, CBCs, serum chemistries, and physical examination at six month intervals.

  Study phs000594

• Genome-wide Association Study of Myasthenia Gravis

  The purpose of this project was to conduct a genome-wide associate study to search for the genetic factors that predispose to myasthenia gravis. The rationale for this study lies in the fact that, although the immunological and physiological processes affecting the neuromuscular junctions of myasthenia gravis patients are well understood, the spectrum of genetic factors that predispose to myasthenia gravis and influence its disease manifestations are not well known. Identification of the myasthenia gravis-related genes will shed light on the fundamental cellular events underlying myasthenia gravis, and will provide focus for research aimed at developing therapies that alter the natural course of the disease. A consortium of fourteen institutions in North America collected DNA samples from 1028 people diagnosed with autoimmune myasthenia gravis. Relevant clinical data have been collected for each patient, including age of onset, severity of disease, response to drug therapy, personal and family history of other autoimmune diseases. Genotyping of the case cohort was performed in the Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD. Genotyping of the case cohort was performed using the HumanOmniExpress-12v1_C SNP array manufactured by Illumina Inc. For the control cohort, we downloaded genotype data from dbGAP (accession phs000196.v2.p1) for 1,998 US neurologically normal individuals. The control cohort had been previously genotyped at the Center for Inherited Disease Research at Johns Hopkins University on HumanOmni1-Quad version 1.0B beadchips (Illumina) as part of the NeuroGenetics Research Consortium GWAS of Parkinson's disease. Analyses were confined to the 677,673 autosomal SNPs that were common to both chips. Of the 1028 samples which were genotyped, 21 samples were excluded due to mismatched genders, 9 were excluded due to low genotype call rate, 5 samples were excluded as duplicates, and 25 samples were excluded as ethnic outliers. The remaining 972 samples were used in analysis.

  Study phs000726

• Structure and Diversity of Urinary Cell-Free DNA Informative of Host-Pathogen Interactions in Human Urinary Tract Infection

  The risk of acquiring urinary tract infection (UTI) is very high for patients who have received kidney transplants; nearly half will develop bacteriuria and an eighth viruria via BK polyomavirus in the first three years following transplantation. Current methodology for diagnosing viral and bacterial infections, while well practiced, is often limited in scope. The advent of next generation sequencing of cell-free DNA has shown promise in its ability to capture multiple perspectives of human health from discovering the origin of cell-free DNA in plasma; such a diagnostic has not been readily applied to urinary cell-free DNA. In this study, we selected 141 urine samples from a cohort of kidney transplant patients, which were collected and stored at Weill Cornell Medical College - New York Presbyterian Hospital. Of these samples, 43 samples were determined to be culture positive (> 10,000 CFU) for one or more bacterial species, including E. coli, Enterococcus, Klebsiella, Haemophilus, and Raoultella. A separate 23 samples were confirmed for BK virus nephropathy, with presence of BK polyomavirus confirmed via qPCR. We also included 29 samples from 14 patients who did not develop UTIs in the first three months following transplantation, and 11 samples that were negative for BK virus nephropathy. For a full description of samples, please see the Supplementary Data 1 in https://pubmed.ncbi.nlm.nih.gov/29925834/. From these urine samples, we aimed to capture and sequence urinary cell-free DNA using a single-stranded library preparation. In addition, we performed whole-genome bisulfite sequencing to 170 plasma samples collected from 27 hematopoietic cell transplant patients who developed graft-versus host disease and BK polyomavirus infection. We also performed Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) on 196 cell-free DNA (cfDNA) samples (154 plasma and 42 urine) collected from five groups of subjects. For a full description of samples, please see publications in PMID: 35864089 and PMID: 35058359.

  Study phs001564

• OurHealth - Cardiovascular Disease in South Asians

  The OurHealth Study aims to build a biobank comprised of South Asian samples from participants residing in the United States. Primary objectives are to (1) identify genetic and non-genetic drivers of cardiometabolic disease in South Asians, (2) engage participants and researchers in scientific advances and research opportunities to accelerate discovery, and (3) assess the impact of returning polygenic risk scores for cardiovascular-related health conditions. Participants use a web-based platform to complete electronic informed consent, and contribute data via (1) online health surveys, (2) mailed saliva biospecimens for sequencing, and (3) optional electronic health record sharing. Surveys capture medical history, medication data, lifestyle factors, family history, mental health history, and detailed information about cultural and ancestral background. Biospecimens, procured via saliva self-collection kits, undergo DNA isolation and are sequenced using the "blended genome exome" (BGE) method, which consists of sequencing on the NovaSeqX 10B Flowcell followed by Dynamic Read Analysis for GENomics (DRAGEN) analysis for alignment to GRCh38, mapping, and variant calling. BGE uses low-coverage whole genome sequencing (lcWGS) (2-3x) combined with deep-coverage exome sequencing (30-40x), improving on SNP arrays for common variant imputation across European and non-European populations while also capturing rare coding variants. Relative to array genotyping, coverage, genotyping breadth, imputation generalizability, and cost are more optimal.BGE requires imputation for which the NHLBI TOPMed reference panel was used, and GLIMPSE2 was used for imputation emitting genotyping dosages (i.e., 0-2 multimodal continuous). Quality control (QC) included the following procedures. Sample QC excluded those with mean coverage 3% contamination from FREEMIX/VerifyBamID, sex aneuploidy and genotype/phenotype sex-mismatch due to potential phenotyping errors, fingerprinting discordance, and sample metric-level outliers were ancestry-aware, given expected distribution differences. Variant QC metrics including allele frequencies, imputation INFO scores, and Hardy-Weinberg Equilibrium (HWE) p-values are provided with the data; the genotype files provided are not filtered.

  Study phs003821

• Dataset for CD8-Positive lymphocyte samples

  This dataset contains scRNA sequencing data for CD8-Positive lymphocytes samples. Sequencing was performed on a Illumina NextSeq 550. The sequencing was always paired.

  Dataset EGAD50000000092

• WES data from patient samples at the stage of NDMM and EMM and normal samples

  This contains the raw Whole Exome sequencing data used for the publication

  Study EGAS50000000036

• RNA-seq dataset for gamma delta (γδ) T-ALL patients

  RNA-seq data for 85 patients with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL)

  Dataset EGAD50000000027

• Bulk RNAseq of patient samlpes at the stage of NDMM, RRMM without EMM and EMM

  This study contains the raw bulk RNAseq data used for the publication

  Study EGAS50000000035

• Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Array data for oesophageal and related samples – Ganguli et al (methylation array)

  Dataset EGAD00010002682

• EARLY DIAgnosis of PAncreatic Cancer (EARLY DIAPAC) study

  Whole genome sequencing of pancreatic cyst fluid for early detection and diagnosis of pancreatic cancer.

  Study EGAS50000000611

• Helse Bergen HF Data Access Committee for the MetBreCS trial dataset submitted to Federated EGA Norway

  This Data Access Committee is appointed by Helse Bergen HF to administer access requests for the MetBreCS trial dataset submitted to Federated EGA Norway.

  Dac EGAC50000000523

• DAC for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Data access comittee for Single cell RNA sequencing of peripheral blood HSPC from patients with sickle cell anemia and healthy donors.

  Dac EGAC50000000650

• Genomic sequencing data for PNG15 and PNG16

  This data set contains genomic sequencing data and variant calls for PNG15 and PNG16.

  Dataset EGAD50000001598

• shallow Whole-Genome sequencing of 14 TNBC tumor in the MATADOR trial - for in silico spike-in experiment

  14 TNBC tumors with tumor percentage ~90% were selected for in silico spike-in experiment

  Dataset EGAD50000001863

• scRNAseq dataset of vitligo dermis and epidermis

  scRNAseq dataset of vitligo dermis and epidermis for 6 patients. For each patient nonlesional and perilesional skin were sampled and processed separately.

  Dataset EGAD50000001874

• NAR-GAB 2025 deposit data

  Human exome gVCFs: rare-disease cohort for the NAR-GAB 2025 study on splicing-SNV prioritization.

  Study EGAS50000001456

• HICHIP_TALL_t_14_16_translocation

  For patient P01, HiChIP experiment for was performed using the Arima-HiC+ kit (A510008, Arima genomics) according to the manufacturer’s protocols.

  Dataset EGAD50000002167

• Primary Neuroblastoma Circle-seq

  We generated Circle-seq data for primary neuroblastoma to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004797

• Res1_PC9_exp2_MC_01_04_22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006170

• V4_panel_bait_design_test

  Targeted gene screen of FFPEs, cell lines and primary tumours for testing the new V4 Cancer gene panel.

  Study EGAS00001001808

• Myeloma_Follow_up_Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Study EGAS00001000743

• Res1_H23_exp2_MC_13_07_22

  8 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006683

• Res1_PC9_exp1_MC_29_03_22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Study EGAS00001006169

• WXS files for Mullighan BiTE WXS

  WXS files for Mullighan BiTE WXS paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005730

• Whole-genome sequencing data for 449 Nigerian individuals

  Whole-genome sequencing data in the form of multi-sample, per-chromosome VCFs for n=449 individuals across 47 unique ethnolinguistic groups.

  Dataset EGAD00001010095

• RNASeq files for Mullighan Leventaki ALCL Project

  RNASeq files for Mullighan Leventaki ALCL Project paper titled "Integrative molecular analysis of pediatric Anaplastic large cell lymphoma reveals subtypes with distinct immune suppression signatures."

  Dataset EGAD00001005951

• WES for Patient 9 to 14 of NIBIT-M4 clinical trial

  WES for Patient 9 to 14 of NIBIT-M4 clinical trial

  Dataset EGAD00001009700

• RNAseq files for Mullighan BiTE RNASEQ1

  RNAseq files for Mullighan BiTE RNASEQ1 paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005731

• A95724A

  Whole genome sequencing for single cells for library A95724A 503 samples; filetype=bam

  Dataset EGAD00001008229

• WGS files for Millighan BiTE WGS

  WGS files for Mullighan BiTE WGS paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005729

• Brain mets discovery cohort whole-exome sequencing raw sequencing files

  These are the raw sequencing files for the 50 brain tumour, 3 extracranial tumour and 34 matched normals for the patients in the discovery cohort.

  Dataset EGAD00001005981

• Additional WGS files for Genomic Landscape ALL paper

  Additional WGS files for Genomic Landscape ALL paper titled "The genomic landscape of pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001010270

• Mucoepidermoid Carcinoma

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001003958

• Targeted sequencing using SPET for Mesothelioma.

  Targeted sequencing using SPET for Mesothelioma.

  Dataset EGAD00001001916

• WGS files for Klco-NUP98 data

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

  Dataset EGAD00001015443

• WXS files for Klco-NUP98 data

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

  Dataset EGAD00001015444

• RNASeq files for Klco-NUP98 data

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

  Dataset EGAD00001015445

• scRNASeq files for Klco-NUP98 data

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

  Dataset EGAD00001015479

• Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Dataset EGAD00001011994

• Mucoepidermoid carcinoma- normals

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001004946

• MT amplicon sequencing reads of 217 Egyptian individuals

  This data set contains for 217 Egyptian individuals the amplicon sequencing reads mapping to chrM. These were subsequently used for haplogroup assignment.

  Dataset EGAD00001006040

• neoALTTO

  RNAseq fastq files for 254 samples for the neoALTTO study of lapatinib, trastuzumab or combination in HER2+ breast cancer patients. Those are pre-treatment baseline samples.

  Dataset EGAD00001011354

• Caregiving as a Natural Stressor in Studies of the Role of Genes That Affect Serotonin Function in Regulating Risk Factors for Coronary Heart Disease (CAREGIVER)

  The burden of caregiving for an ill relative has been shown to interact with existing comorbidities to increase risk of several health outcomes including metabolic syndrome and blood pressure reactivity. The CAREGIVER study was developed to compare cardiometabolic risk factors in caregivers and controls. These risk factors include physiologic measures, psychologic measures, neighborhood characteristics, and genetic and genomic factors. DNA and plasma were collected and used for examination of cardiometabolic and stress biomarkers, genotyping and methylation analysis.

  Study phs001747