14037 results for "Buy fc coins Buyfc26coins.com is EA Sports official for FC 26 coins Their customer service is very responsive..7ZgM"

in 46.00 milliseconds.

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002901

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002905

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002921

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002919

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002900

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002917

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002914

• BLUEPRINT September 2016, ATAC-seq for naive B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002902

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002913

• GIS-LUNGTCR1-2016_WES-FASTQ

  This dataset contains FASTQ files for multi-region exome-sequencing of EGFR-mutant lung adenocarcinomas from Asian patient. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors. Multiple runs for each sample, and 368 fastq in total. Please refer to the sample-ID from filename for merging.

  Dataset EGAD00001001978

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002909

• Molecular discrimination for multicentric occurrence and intrahepatic metastasis by whole genome sequencing of multiple liver cancers

  RIKEN collection of WGS reads for 13 multicentric liver cancers or intrahepatic metastasis and matched blood samples for 12 donors.

  Dataset EGAD00001001996

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002922

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002899

• GIS-LUNGTCR1-2016_VAL-FASTQ

  This dataset contains FASTQ files of targeted Amplicon deep-sequencing data, for validation of the mutations found in WES. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors. 140 fastq in total, multiple runs for some of the samples. Please refer to the sample-ID from filename for merging.

  Dataset EGAD00001001981

• FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

  This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

  Dataset EGAD00001015356

• Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

  In this study we generated single-cell whole transcriptome and surface marker expression data for 24 samples of 19 AML patients as well as one healthy donor. We followed the CITEseq protocol with the 3' 10x Genomics scRNAseq kit version 3.1 To increase the coverage of the mitochondrial genome we generated mitochondrial libraries following a protocol termed Optimized 10x. Based on TAPseq, we generated libraries to increase the coverage of selected nuclear SNVs. Exome sequencing was generated for 15 patients to identify nuclear variants. Bulk ATAC was obtained for 9 samples to facilitate the discovery of mitochondrial SNVs. MutaSeq (modified version of SmartsSeq2) was performed on cells from 3 patients. Targeted DNAseq from single-cell derived colonies was generated for 1 patient.

  Study EGAS00001007078

• Evolutionary landscape of clonal hematopoiesis in 3359 individuals from the general population

  This project contains longitudinal data for processed somatic variant calls and data on core phenotypic variables for 3359 community-based individuals ≥60 years, a sub-cohort of the population-based Lifelines cohort (167,729 participants). Cases with peripheral blood count abnormalities and population-based controls were included. Next-generation sequencing data were generated with a median time period of 43 months between baseline and follow-up visit. For 327 individuals a third visit sample was included. Error-corrected sequencing was performed using single-molecule tagged molecular inversion probes targeting 27 myeloid and lymphoid driver genes. The threshold for variant calling was set at ≥1% VAF and ≥10 consensus variant reads. Details on sample selection, sequencing technique, variant calling procedures and data curation are described (van Zeventer et al. 2023).

  Study EGAS00001007087

• SNP Array Data for EGAS00001004666

  SNP Array Data for EGAS00001004666

  Dataset EGAD00010002257

• Heart

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000655

• Asian Genome Project(BioBank Japan genotype data)

  Biobank Japan registrants sequenced for Asian Genome Project

  Study JGAS000647

• FFPE_Normal_Panel_V3_Cancer_Panel

  FFPE normal panel generation for use with V3 cancer panel 0618521

  Study EGAS00001000836

• Oxford Nanopore sequencing for APL

  Raw fast5 file of Oxford Nanopore sequencing for an APL patient sample

  Dataset EGAD00001008151

• snv calls for subclonal reconstruction

  single nucleotide variant calls from somatic sniper, vcf format. input for subclonal reconstruction

  Dataset EGAD00001003753

• DATA FILES FOR SJLGG

  DATA FILES FOR SJLGG

  Dataset EGAD00001000695

• Longitudinal genome-wide analysis of progressive chronic lymphocytic leukemia under uniform front-line therapy of pentostatin, cyclophosphamide, and rituximab

  Samples from two-center prospective phase 2 clinical trail conducted at Ohio State University (Columbus, OH) and Mayo Clinic (Rochester, MN) were analyzed in 12 cases. All patients had progressive CLL as defined by National Cancer Institute (NCI) Working Group criteria. Patients provided written informed consent for correlative studies according to the Declaration of Helsinki on an institutional review board approved protocol for the collection and use of samples for research purposes from both participating institutions. Eligible patients received a regimen consisting of pentostatin (2 mg/m2), cyclophosphamide (600 mg/m2), and rituximab (375 mg/m2) provided intravenously on day 1 of a 21-day cycle for a maximum of 6 cycles. Responses were assessed by NCI Working Group criteria and included a bone marrow evaluation and two-color flow cytometry 2 months after completion of therapy. Peripheral blood samples from these patients collected longitudinally before (Pre-Baseline), at (Baseline) and after therapy (Relapse) were analyzed for genomic heterogeneity and clonal complexity by high throughput Exome sequencing.

  Study phs000794

• POISED (Peanut Oral Immunotherapy: Safety, Efficacy, and Discovery)

  Phase 2 POISED (Peanut Oral Immunotherapy: Safety, Efficacy, Discovery) Study In this randomized, double-blind, placebo-controlled (DBPC) clinical trial, blinded placebo group received oat flour, whereas in active participants, dosage was built-up for over ~ 52 weeks and subsequently maintained on 4000 mg peanut protein, daily for next 52 weeks. 80 (98.77%) per-protocol active participants passed the food challenge at week 104. Subsequently, for 12 weeks, peanut ingestion was avoided in a randomized group of 51 blinded active participants (i.e., peanut avoidance group). 21 (41.2%) participants in the peanut avoidance group passed the 4000 mg double-blind, placebo-controlled food challenge (DBPCFC) without any allergic reaction at week 117, thus demonstrating sustained unresponsiveness. These 21 participants continued oral immunotherapy (OIT) for every three months and afterwards were allowed to continue peanut OIT discontinuation if they passed. 8 participants passed the DBPCFCs, 12 months after peanut discontinuation (week 156), i.e. they achieved long-term sustained unresponsiveness with no allergic reaction in response to food challenge. For detailed description, please refer to Chinthrajah et al., PMID: 31522849.

  Study phs003071

• NHLBI TOPMed: Whole Genome Sequencing of Venous Thromboembolism (WGS of VTE)

  This study consists of 338 VTE cases from an inception cohort of Olmsted County, MN residents (OC) with a first lifetime objectively-diagnosed idiopathic VTE during the 40-year study period, 1966-2005. All living study subjects were invited to provide a whole blood sample at the Mayo Clinical Research Unit for leukocyte genomic DNA and plasma collection. For living study subjects who did not provide a blood sample, we retrieved any leftover blood ("waste" blood) from samples collected as part of routine clinical diagnostic testing and used this to extract DNA after obtaining patient consent. For deceased cases, with IRB approval, we extracted DNA from any available stored tissue within the Mayo Tissue Archive. This "tissue" DNA has been successfully genotyped in prior studies. Three trained and experienced study nurse abstractors reviewed the complete medical records in the community of all potential cases. Note: WGS sample IDs for the previous GENEVA study cases (phs000289) are included in this dataset. The phenotypes for the GENEVA study are located under the above phs number.

  Study phs001402

• Data Access Committee for the DNA sequencing data included in the study "A generalizable machine learning framework for classifying DNA repair defects using ctDNA exomes”

  Dac EGAC00001003111

• "Usage of small amounts of DNA for Illumina sequencing"

  "Usage of small amounts of DNA for Illumina sequencing"

  Dataset EGAD00001000034

• Dataset for TIX

  All files for TIX individuals

  Dataset EGAD50000000426

• RNAseq for 4 pdx and 1 cell-line

  RNAseq for #1049, #111, #1217, #206, COV362

  Dataset EGAD50000000032

• PBMC

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000654

• DATA FILES FOR SJINF RNASeq

  DATA FILES FOR SJINF RNASeq

  Dataset EGAD00001001098

• Deep sequencing of melanoma for driver mutations

  Deep sequencing of melanoma for driver mutations

  Dataset EGAD00001001445

• Australian genomes

  Mapped data (bam files) for high-throughput whole genome sequence data for 83 modern Aboriginal Australians

  Dataset EGAD00001002001

• Resident memory CD8 T cells persist for years in human small intestine

  Resident memory CD8 T cells (Trm) have been shown to provide effective protective responses in the small intestine (SI) in mice. A better understanding of the generation and persistence of SI CD8 Trm cells in humans may have implications for intestinal immune-mediated diseases and vaccine development. Analyzing normal and transplanted human SI we demonstrated that the majority of SI CD8 T cells were bona fide CD8 Trm cells that survived for over 1 year in the graft. Intraepithelial and lamina propria CD8 Trm cells showed a high clonal overlap and a repertoire dominated by expanded clones, conserved both spatially in the intestine and over time. Functionally, lamina propria CD8 Trm cells were potent cytokine-producers, exhibiting a polyfunctional (IFN-γ+ IL-2+ TNF-α+) profile, and efficiently expressed cytotoxic mediators after stimulation. These results suggest that SI CD8 Trm cells could be relevant targets for future oral vaccines and therapeutic strategies for gut disorders.

  Study EGAS00001003676

• Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS)

  Advances in antiretroviral therapies (ART) and patient management have improved survival of people living with HIV (PLWH). However, with exposure to ART and associated side effects and toxicities as well as to the virus itself, PLWH are at an increased risk of several chronic diseases. The Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS) research network integrates longitudinal clinical data and treatment management of PLWH and provides research infrastructure to support HIV-associated clinical, social, and behavioral outcomes and comparative effectiveness research using data collected from 8 Centers for AIDS Research clinical sites across United States. For detailed study description, see Kitahata et al. (2008, PMID:18263650).

  Study phs001788

• Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia - Acute myeloid leukemia

  The advent of high-throughput next generation sequencing (NGS) technologies that are revolutionizing genomics and transcriptomics by providing a single base resolution tool for a unified deep analysis of diseases complexity allows a fast and cost-efficient fine-scale assessment of the genetic variability hidden within cohorts of patients affected by the same leukemia. That being so, by potentially highlighting inter-individual differences that may play a role in the differential success of diverse therapeutic interventions, they promise to be crucial for selecting the most appropriate medical treatments. The project aims at the identification of novel prognostic biomarkers for acute myeloid leukemia (AML) and studied the molecular differences between aneuploid and euploid AML.

  Study EGAS00001005464

• 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.

  Study EGAS00001008051

• OLD DATA FILES FOR SJMB - Superseded by EGAD00001001864

  OLD DATA FILES FOR SJMB - Superseded by EGAD00001001864

  Dataset EGAD00001000269

• RNAseq for 8 PDX

  RNAseq for #111, #1177, #206, #201, #29, #931, WO-19, WO-2

  Dataset EGAD50000000116

• Preeclampsia InterPregGen Consortium: GWAS meta-analysis summary statistics for European fetal preeclampsia cases versus controls and GWAS genotype data for European fetal preeclampsia cases

  Study EGAS00001001048

• sc-DECISION

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

  Dac EGAC50000000642

• Pulldown_DNA_methylation_study_v2

  Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

  Study EGAS00001000979

• PBMC_dual_10X_kit

  Dual snRNAseq and ATACseq of replicate PBMC samples for 10X beta testing.

  Study EGAS00001004834

• WGS data for Glioblastoma (EGAS00001003953, H016)

  Whole genome sequencing data for 20 human glioblastoma patients.

  Dataset EGAD00001006545

• McGill EMC Release 4 for assay "H3K27ac"

  McGill EMC Release 4 for assay "H3K27ac"

  Dataset EGAD00001001298

• McGill EMC Release 4 for assay "H3K9me3"

  McGill EMC Release 4 for assay "H3K9me3"

  Dataset EGAD00001001299

• McGill EMC Release 4 for assay "H3K4me1"

  McGill EMC Release 4 for assay "H3K4me1"

  Dataset EGAD00001001296

• McGill EMC Release 4 for assay "H3K36me3"

  McGill EMC Release 4 for assay "H3K36me3"

  Dataset EGAD00001001295

• BLUEPRINT: DNaseI-seq for monocytes

  DNaseI-seq for monocytes

  Dataset EGAD00001000674

• Dataset for "Genomic landscape of oral cancers" (CGI WGS)

  Dataset for "Genomic landscape of oral cancers" (CGI WGS)

  Dataset EGAD00001004339

• DATA FILES FOR Histone-NSD2_RNASeq

  DATA FILES FOR Histone-NSD2_RNASeq

  Dataset EGAD00001000655

• McGill EMC Release 4 for assay "H3K4me3"

  McGill EMC Release 4 for assay "H3K4me3"

  Dataset EGAD00001001297

• DATA FILES FOR GRUBER SJAMLM7 RNASEQ

  DATA FILES FOR GRUBER SJAMLM7 RNASEQ

  Dataset EGAD00001003135

• Dataset for "Genomic landscape of oral cancers" (Illumina WGS)

  Dataset for "Genomic landscape of oral cancers" (Illumina WGS)

  Dataset EGAD00001004356

• McGill EMC Release 4 for assay "H3K27me3"

  McGill EMC Release 4 for assay "H3K27me3"

  Dataset EGAD00001001294

• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• Susceptibility loci for tanning ability in Japanese population identified by genome-wide association study

  We performed genome-wide association studies of Japanese Skin Type for Japanese individuals from a cohort study by the Tohoku Medical Megabank Project in order to identify variants related to tanning ability and skin pigmentation. We used imputed genotype data of 9,187 Japanese individuals, of which 4,475 individuals are from Miyagi prefecture and 4,712 individuals are from Iwate prefecture. Skin Type information was obtained from the questionnaire for cohort participants.

  Study JGAS000160

• Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

  Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

  Dataset EGAD50000002132

• Mutational landscape of the transcriptome offers putative targets for immunotherapy of myeloproliferative neoplasms

  In this study, we aimed to comprehensively characterize in 113 myeloproliferative neoplasms (MPN) patients the mutational landscape of the granulocyte transcriptome using RNA sequencing data. We implemented workflows for fusion and variant calling, and differential splicing analysis for patients with hotspot SF3B1 mutations. Finally, we characterized the neoantigen landscape on individualized level taking each patient's HLA genotype (derived from the same RNA-seq dataset) into account.

  Study EGAS00001003486

• RNA Sequencing of AD OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from individuals diagnosed with Alzheimer's disease exposed to traffic-related ultrafine particles (UFPs) for 24-h and 72-h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Study EGAS50000000448

• BELLINI clinical trial single-cell RNA-Seq and TCR data: cohorts A & B

  Single-cell RNA-Seq data and TCR sequencing data (both by 10X Genomics) of 51 TNBC primary tumors obtained from 29 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (16 patients, 28 samples) received nivolumab for 4 weeks, patients in cohort B (13 patients, 23 samples) received nivolumab + ipilimumab for 4 weeks. The included sequencing data was generated from frozen material for cohort A and from fresh material for cohort B.

  Dataset EGAD50000000807

• Comprehensive molecular phenotyping of ARID1A-deficient gastric cancer reveals pervasive epigenomic reprogramming and therapeutic opportunities

  This dataset includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset.

  Dataset EGAD50000000660

• WES for 42 patients with pleural mesothelioma (Not matched)

  The dataset contains WES data (bam files) for 42 pleural mesothelioma samples. Nextera Flex for Enrichment solution (Illumina, San Diego, CA) in combination with SureSelect Human All Exon V7 probes (Agilent, Santa Clara, CA) was used for library preparation and generated libraries were sequenced on NovaSeq 6000 (Illumina, San Diego, CA) in 150 pair-end mode. Quality control of the raw data was conducted using fastQC (v. 0.11.8) (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/). WES data were then analyzed with the DRAGEN Bio IT platform 49 (version 4.2.4) and the human GRCh38 as reference genome.

  Dataset EGAD50000002127

• WES for 45 patients with pleural mesothelioma (Matched)

  The dataset contains WES data (bam files) for 45 pleural mesothelioma samples. Nextera Flex for Enrichment solution (Illumina, San Diego, CA) in combination with SureSelect Human All Exon V7 probes (Agilent, Santa Clara, CA) was used for library preparation and generated libraries were sequenced on NovaSeq 6000 (Illumina, San Diego, CA) in 150 pair-end mode. Quality control of the raw data was conducted using fastQC (v. 0.11.8) (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/). WES data were then analyzed with the DRAGEN Bio IT platform 49 (version 4.2.4) and the human GRCh38 as reference genome.

  Dataset EGAD50000002128

• Bulk 3' mRNA-Seq of dome and suspension tubuloids

  Bulk 3' mRNA-sequencing of human kidney tubuloids grown in dome and suspension culture for the identification of transcriptional differences associated with culture method, passage, and donor. Tubuloids were generated from 4 separate donors and collected for sequencing at day 7 of passage 3, 4, and 5 in dome and suspension culture.

  Study EGAS50000001629

• Whole exome sequencing of Parkinson's disease patients from the United Kingdom

  As part of the International Parkinson's Disease Genomics Consortium, exomes of Parkinson's disease (PD) patients and healthy controls were sequenced to study the genetic etiology of PD. This UK cohort consists of 70 PD patients. Researchers can apply for access to fastq, vcf and binary plink files for this cohort.

  Study EGAS00001002156

• Single cell RNA sequencing of CD19 CAR T-cell infusion products

  We performed single cell RNA sequencing of remnants from CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma. Libraries were prepared using 10X 5’ GEX chemistry and sequenced on an Illumina HiSeq 4000 to obtain >50,000 reads per cell.

  Study EGAS00001004576

• ChIP-seq and 4C-seq datasets in megakaryocytes and granulocytes from individuals with QPD and unaffected controls

  ChIP-seq was performed for the following histone modifications in both megakaryocytes and granulocytes: H3K27ac, H3K4me2, and H3K36me3. ChIP-seq was performed for H3K27me3 and CTCF in megakaryocytes only. All ChIP experiments consist of n=3 replicates for each of QPD and Control, with the exception of control granulocyte H3K4me2 for which only n=2 replicates were performed. 4C-seq datasets consist of 2 viewpoints (PLAU promoter and an intergenic enhancer), profiled in megakaryocytes from n=2 controls and n=4 QPD.

  Dataset EGAD00001006048

• SGCC GASCAD-II dataset

  The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

  Dataset EGAD00001015433

• Whole exome sequencing of ATCWGS42 primary tumour and PDX

  Genomic DNA was isolated from snap-frozen tissue and subjected to whole genome sequencing at The Center for Applied Genomics (Hospital for Sick Children, Toronto, ON) or at Beijing Genomic Institute (BGI). High-coverage whole exome-sequencing was performed at GeneSeeq Inc. (Toronto, Ontario, Canada) using IDT xGen exome panel.

  Study EGAS50000001490

• Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset EGAD00001015373

• Data from Shea et al Can Research 2025

  This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

  Dataset EGAD50000001334

• WES used for direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry

  We performed whole exome sequencing of tumor- as well as PBMC-derived DNA of five melanoma patients for identification of naturally presented patient-specific neoepitopes.

  Study EGAS00001002050

• Demultiplexed FASTQs for each volunteer

  This submission consists of 15 volunteer FASTQs, split by chemistry: Chemistry v1.1: 7 FASTQ sets, one set for each volunteer (RA1-7) Chemistry v2: 16 FASTQ sets, two for each volunteer (RA8-15; FASTQ set 1: Gene Expression (GEX); FASTQ set 2: TCR enrichment (VDJ))

  Dataset EGAD00001007586

• PPGL RNA-Seq dataset

  Dataset includes fastq files for RNA-Seq experiments for tumor samples of PPGL patients. Single end reads fastq files are available for 102 different samples

  Dataset EGAD00001008578

• Dataset-linking-WGS-via-README-for-EGAS00001004884

  This dataset contains 139 Tumor and Control WGS files for samples for Gerhauser et al.,Cancer Cell, 2018, 34:996-1011. WGS and sequencing protocol was earlier described in Weischenfeldt et al, Cancer Cell, 2013.

  Dataset EGAD00001007669

• BLUEPRINT September 2016, ATAC-seq for class switched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002908

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002915

• Exome and RNA sequencing data for Diffuse Large B Cell Lymphomas

  Exome sequencing data for 1001 DLBCL patients and RNA sequencing data for 775 DLBCL patients

  Dataset EGAD00001003600

• Long read data generated for de novo assembly

  Long read data generated for de novo assembly (PacBio and ONT FASTQ files)

  Dataset EGAD50000002367

• Neuroblastoma sequencing data

  This study shares tumor and normal DNA for a patient with neuroblastoma

  Study EGAS00001005602

• WES files for SJMDS

  WES files for SJMDS paper titled 'Genomic Landscape of Pediatric Myelodysplastic Syndromes'

  Dataset EGAD00001003155

• DATA FILES FOR PCGP MB WGS - Supersedes (EGAD00001000269)

  DATA FILES FOR PCGP MB WGS - Supersedes (EGAD00001000269)

  Dataset EGAD00001001864

• WGS files for SJMDS

  WGS files for SJMDS paper titled 'Genomic Landscape of Pediatric Myelodysplastic Syndromes'

  Dataset EGAD00001003156

• DATA FILES FOR PCGP SJINF WES

  DATA FILES FOR PCGP SJINF WES

  Dataset EGAD00001001245

• Linked-reads for Juvenile Pilocytic Astrocytomas

  Matched tumor-normal data for 6 JPAs. Generated using 10X Genomics Linked-reads

  Dataset EGAD00001011114

• National Cancer Institute (NCI) Prostate Cancer Genome-Wide Association Study for Uncommon Susceptibility Loci (PEGASUS)

  This genome-wide association study was funded by the National Cancer Institute (NCI) to identify uncommon susceptibility loci for prostate cancer. A total of 4,600 prostate cancer cases and 2,840 controls of European ancestry from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were genotyped using the Illumina HumanOmni2.5 and passed rigorous quality control filters. Additional genotype data (available in dbGap under other accession numbers) from 101 independent controls of European ancestry scanned with the HumanOmni2.5 were also included, resulting in a total of 4,600 cases and 2,941 controls for the published analysis. SNPs from the most promising regions, as determined by rank p-value, under multiple different models as well as select candidate genes were taken forward for replication using a custom Iselect chip in 6,575 cases and 6,392 controls of European ancestry. Results from the primary scan after imputation were then meta-analyzed with the Iselect results as well as results from previous GWAS. In a combined meta-analysis of the primary scan together with the custom Iselect replication and a previous GWAS, thirteen loci reached genome-wide significance (P < 5 x 10-8) for prostate cancer overall; however, each of them confirmed a previously reported locus. Although they did not reach genome-wide significance, we found evidence for two new suggestive loci at chromosome 16q22.2 (PKD1L3, rs12597458, P = 9.67 x 10-8) and 6p22.3 (CDKAL1, rs12198220, P = 2.13 x 10-7). In a combined case-only analysis of 12,518 prostate cancer cases, we identified two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49x10-9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18x10-8). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85x10-5) with no association for non-aggressive prostate cancer compared to controls (P=0.57). Only the cases and controls genotyped on the HumanOmni2.5 specifically for this study are included under this accession number. Controls (n=101) genotyped with the HumanOmni2.5 for another study are posted under a different accession number. Please note that the majority of prostate cancer cases and controls genotyped in CGEMS (and posted under a different accession number) are included in this study.

  Study phs000882

• Validation of Gene Array to Predict Bacterial Co-infection In Adults Hospitalized with Viral Lower Respiratory Tract Infections (LRTI)

  Accurate tests for microbiologic diagnosis of lower respiratory tract infections (LRTI) are needed. Gene expression profiling of whole blood represents a powerful new approach for analysis of the host response during respiratory infection that can be used to supplement pathogen detection testing. Using qPCR, we prospectively validated the differential expression of 10 genes previously shown to discriminate bacterial and non-bacterial LRTI confirming the utility of this approach. In addition, a novel approach using RNAseq analysis identified 141 genes differentially expressed in LRTI subjects with bacterial infection. Using "pathway-informed" dimension reduction, we identified a novel 11 gene set (selected from lymphocyte, α-linoleic acid metabolism, and IGF regulation pathways) and demonstrated a predictive accuracy for bacterial LRTI (nested CV-AUC=0.87). RNAseq represents a new and an unbiased tool to evaluate host gene expression for the diagnosis of LRTI.

  Study phs001248

• APOL1 Risk Variants Induce Metabolic Reprogramming of Podocytes in Patient-Derived Kidney Organoids

  Apolipoprotein L1 (APOL1) high-risk genotypes G1 and G2 are responsible for the increased risk of chronic kidney disease (CKD) in the African-American population, especially in the presence of interferon gamma (IFN-γ). Here, we applied single cell transcriptomics on kidney organoids generated from patient-derived induced pluripotent stem cells (iPSCs) to model human APOL1 nephropathy. iPSCs were generated from fibroblasts of two patients with APOL1 nephropathy homozygous for G1 or G2 risk variants, and an isogenic control (G0) was created by gene correction. Kidney organoids were generated according to previously published protocol (Takasato M et al. Nat. Protoc. 2016) and treated with IFN-γ for two days to induce APOL1. Twenty-four hours after IFN-γ removal, treated organoids from all three lines that were cultured in parallel were harvested for single cell transcriptomics.

  Study EGAS50000001223

• Exploring Extracellular Vesicle microRNAs in Usher Syndrome Type 1B: Tear-Derived EVs as Indicators of Retinal Health

  The goal of this study was to explore extracellular vesicles (EVs) from human tears and iPSC-derived RPE cells as biomarkers for Usher syndrome type 1B (USH1B), a rare inherited disorder causing deafness and retinitis pigmentosa. Researchers found that tear EVs showed higher levels and diversity of miRNAs, making them a promising non-invasive source for diagnosing USH1B. In contrast to patient-derived RPE cells, which did not express MYO7A protein despite similar expression levels in controls, the study identified specific microRNA signatures associated with retinal degeneration in both tear EVs and RPE-derived EVs. The findings suggest that tear EVs can serve as a useful biomarker for USH1B diagnosis, monitoring, and therapeutic development. Overall, this research aims to contribute to our understanding of disease mechanisms and identify potential targets for treatment in patients with Usher syndrome type 1B.

  Study EGAS50000001200

• Determining genome-wide binding of ETS2 by CUT&RUN in primary human macrophages

  This dataset consists of sequencing data from an ETS2 CUT&RUN experiment in primary inflammatory (TPP) macrophages (n = 2). Pre-cultured TPP macrophages were harvested and processed immediately using the CUT&RUN Assay kit (Cell Signaling) according to the manufacturer’s instructions with the following modifications (essentially, avoiding the use of ConA-coated beads). Anti-ETS2 (ThermoFisher) or IgG control (Cell Signaling) antibodies were used for targeted digestion of chromatin. For each donor, 5x10^5 cells were pelleted, washed in Wash Buffer, and resuspended in Antibody Binding buffer. Cells were incubated with antibodies (1:100 dilution for anti-ETS2) for 2h at 4°C. After washing in Digitonin Buffer, cells were incubated with pA/G-MNase for 1h at 4°C. Cells were washed twice in Digitonin Buffer, resuspended in the same buffer and cooled for 5 minutes on ice. Calcium chloride was added to activate pA/G-MNase digestion and cells were incubated for 30 minutes at 4°C before Stop Buffer was added, and cells were incubated for 10 min at 37°C to release cleaved chromatin fragments. Supernatants were collected by centrifugation and DNA extracted using DNA Purification Buffers and Spin Columns (Cell Signaling). Library preparation was performed according to a protocols.IO protocol (dx.doi.org/10.17504/protocols.io.bagaibse) using the NEBNext Ultra II DNA Library Prep Kit. Size selection was performed using AMPure XP beads (Beckman Coulter) and fragment sizes were determined using an Agilent 2100 Bioanalyzer (High Sensitivity DNA kit). Equimolar pools of indexed libraries were sequenced on an Illumina NovaSeq 6000 (100bp PE reads). Raw data are provided as 100 bp paired-end Illumina reads.

  Dataset EGAD00001011349

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__pancreas_LCM_

  Samples prepared by LCM - 5 cases for pilot study. Bulk DNA not available.

  Study EGAS00001003197

• Rhabdoid tumor sequencing data

  This study contains sequencing DNA and RNA sequencing data for rhabdoid tumors

  Study EGAS00001006351