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• Cylindromas_sun_protected_and_exposed

  The project aims to look at mutational signatures in a rare inherited skin tumour syndrome called CYLD cutaneous syndrome. These patients develop multiple skin tumours that are seen at sun exposed and sun protected sites. We plan to carry out WGS on carefully curated tumours from such patients. We then plan to analyse this data for mutational signatures, comparing this between sun exposed and sun protected sites.

  Study EGAS00001002521

• Misoprostol-induced high fever GWAS study

  Genome-wide association (GWAS) meta-analysis study of misoprostol-induced fever was conducted on two South American cohorts (Argentina and Ecuador). DNA was collected from blood of women who were screened for postpartum haemorrhage (PPH) and administered misoprostol were included in the study. Genotypes were acquired from the Global Screening Array (Illumina). Meta-analysis of these cohorts was completed using METAL software.

  Study EGAS00001005455

• PAH sequencing study

  The Cohort study of idiopathic and heritable PAH is an observational, prospective and longitudinal study of patients with idiopathic and heritable PAH. Follow-up information is collected as a part of routine clinical care every six months. The study allows recruitment of both incident and prevalent cases. Patients consented to the study agreed to have blood taken for next-generation sequencing and other omics studies.

  Study EGAS00001005532

• NIHR BioResource Common Disease Patients 2016

  NIHR BioResource Common Disease Patients 2016. The dataset includes 13489 samples from blood donors, they were not screened for any particular disease, and therefore they are representative of the general population. Genomic data includes 845487 snps collected using the UK BioBank V1 Affymetrix array. Phenotypic data includes gender, age, ethnicity and disease. According to our internal quality check there are 81 duplicates in this dataset.

  Study EGAS00001004870

• Gremlin 1 + fibroblastic niche maintains dendritic cell homeostasis in lymphoid tissues

  Although cross-species transcriptional analysis has been generated for DCs37, transcriptomic conservation between mouse and human FRCs at single-cell resolution has been unclear. To test whether GREM1+ FRCs might also play a role in DC homeostasis in humans, we performed scRNA-seq of CD45–PDPN+ stromal cells, as well as CD45+CD11c+ immune cells from healthy human LNs of three donors.

  Study EGAS00001006211

• RNA-seq following miR-130a overexpression (OE) in human CD34+cord blood cells

  We performed RNA-seq on CD34+ human cord blood (CB) cells transduced with Control or miR-130a OE lentiviruses to identify differentially expressed genes. Sorted CD34+ cells from 3 independent cord blood pools were transduced with lentiviruses containing mOrange (mO) reporter gene. mO+ cells were sorted 3 days post-transduction and RNA was harvested for library preparation and sequencing.

  Study EGAS00001005868

• Genetic regulation of gene expression in human brain cell types

  We leveraged single nuclei RNA-seq from 192 human brain samples to map cis-eQTLs in 8 brain cell types. We found extensive cell-type specific genetic effect on gene expression and integrated our results with GWAS to identify putative novel risk genes for brain disorders and the cell types in which the disease mechanisms are likely active.

  Study EGAS00001006345

• WES

  Exome Sequencing. 3 ug of genomic DNA from each lymph node sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

  Dataset EGAD00001005424

• RNAseq files for Klco RPAML

  RNAseq files for Klco RPAML study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008407

• Understand Paratyphoid Disease - host responses to human challenge with S. Paratyphi A (2019-08-28)

  This project aims to evaluate the transcriptional response to disease measured in whole blood of participants who developed enteric fever after challenge and, importantly, those who were challenged but stayed well throughout the challenge period. This data will provide unique coverage of the transcriptome and will yield invaluable insight after integration with a wealth of clinical data collected during this trial. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-28.

  Dataset EGAD00001005298

• WGS data of patients diagnosed with angiosarcoma

  Whole-genome sequencing (WGS) was performed for 13 pairs of tumor-normal and 5 tumor-only samples from patients diagnosed with angiosarcoma. 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 X Ten as 2x151 bp.

  Dataset EGAD00001005366

• ChIP-seq of primary AML patients with t(3;3)/inv(3)

  ChIP-seq was conducted in blasts from patients with t(3;3) AML to assess differences of the GATA2 super-enhancer between the translocated allele and the non-translocated allele. The dataset includes 2x H3K27ac ChIP-seq and 1x MYB ChIP-seq. ChIP samples were processed according to the Illumina TruSeq ChIP Sample Preparation Protocol (Illumina) or Diagenode Library V3 preparation protocol (Diagenode) and either sequenced single-end (1x 50 bp) on the HiSeq 2500 platform (Illumina) or paired-end (2x100 bp) on the Novaseq 6000 platform (Illumina). Briefly, reads were aligned to the human reference genome build hg19 with bowtie for single-end runs and bowtie2 for paired-end runs.

  Dataset EGAD00001006821

• WGS files for Klco RPAML

  WGS files for Klco RPAML study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008413

• Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES)

  The T2D-GENES/GoT2D 13K exome sequencing study includes ~13,000 samples, half T2D cases and half T2D controls, from five ancestries (~5K Europeans, ~2K each of African-American, East-Asian, South-Asian, and Hispanic). Samples underwent deep exome sequencing, with SNVs and INDEls called according to GATK best practices; variant sites were then filtered according to the GATK best practices, and then samples and variants underwent further filtering based on aggregate genotype quality as described in Fuchsberger et al. (e.g. low call rate, excess heterozygosity for samples, low call rate or coverage for variants). Please note that one of the samples in the T2D-GENES vcf does not have phenotype data.

  Dataset EGAD00001002246

• Whole Exome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Whole Exome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003434

• European Prospective Investigation into Cancer and Nutrition BAMs

  516 DNA samples were collected from individuals upon enrollment into the European Prospective Investigation into Cancer and Nutrition study between 1993 and 1998 across 17 different centers. 126bp pair-end reads sequencing data from the Illumina platform were converted to fastq format, the 2bp molecular barcode information at each read of the pair was trimmed and was written in the reads name. The Thymine nucleotide required for ligation was removed from the sequences. Burroughs-Wheeler Aligner (BWA-mem) was used for alignment of the processed fastq files to the reference hg19 genome, following indel-re-alignment using GATK. An in-house algorithm was written to collapse read families that share the same molecular barcode sequence

  Dataset EGAD00001003583

• Target-capture sequencing of FFPE tumor samples from patients diagnosed with NKTL

  211 NKTL FFPE specimens were screened for somatic mutations using deep targeted capture sequencing. FFPE rolls or slides were extracted using QIAamp DNA FFPE Tissue kit (QIAGEN). The FFPE genomic DNA was treated with NEBNext FFPE DNA Repair Mix and assessed by Quant-it PicoGreen dsDNA Assay Kit (Invitrogen). The library was generated from 10-200 ng DNA with SureSelectXT Low Input Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent Technologies) according to manufacturer’s instructions. RNA based probe was designed with SureDesign (Agilent Technologies) to target-capture 140 genes. Next, the captured libraries were pooled in equimolar concentration and sequenced on Illumina Novaseq 6000 platform with SP or S1 chip.

  Dataset EGAD00001005303

• WGS data of patients diagnosed with NKTL

  Whole-genome sequencing (WGS) was performed for 50 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 or HiSeq X Ten as 2x101 bp or 2x151 bp, respectively.

  Dataset EGAD00001005231

• A108759B

  Whole genome sequencing for single cells for library A108759B 1134 cells; filetype=bam

  Dataset EGAD00001007088

• Ipilimumab plus Decitabine for Patients with MDS or AML in Post-Transplant or Transplant Naïve Settings

  Design and AimsThis study was a phase 1 clinical trial investigating the combination of ipilimumab (IPI), a CTLA-4 checkpoint inhibitor, and decitabine (DEC), a hypomethylating agent, for treating relapsed/refractory (R/R) myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). The goal was to determine whether DEC could enhance the immune response to IPI without causing excessive immune toxicity. This study provides important insights into the use of immune checkpoint inhibitors with hypomethylating agents in treating high-risk MDS/AML and highlights the need for further research on optimizing immune-based therapies in these settings.Population InformationPost-HSCT arm: 25 patients (23 AML, 2 MDS; all relapsed/refractory).Transplant-naïve arm: 23 patients (15 AML, 8 MDS; 20 relapsed/refractory, 3 untreated).Data available through dbGaPDeidentified individual participant data, Multiplex immunofluorescence staining, Olink, RNA-Seq and Whole Exome SequencingPrincipal FindingsSafety & Tolerability: The maximum tolerated dose (MTD) for IPI was determined to be 10 mg/kg, though higher doses were associated with increased immune-related adverse events (irAEs).Efficacy: The overall response rate (ORR) was higher in transplant-naïve patients (52%) compared to post-HSCT patients (20%).Responses were more frequent at higher IPI doses (10 mg/kg). Some patients achieved durable remission (>1 year), often linked to irAE development.Toxicity: The most common grade ≥3 treatment-emergent adverse events included neutropenia (32%-48%), thrombocytopenia (28%-48%), and febrile neutropenia (36%-61%). irAEs were observed in 44%-48% of patients, with GVHD occurring only in the post-HSCT group.Survival Outcomes: Median overall survival and progression-free survival did not significantly differ between the two arms. However, in transplant-naïve patients, 1-year survival was higher in those who developed irAEs (72.7%) versus those who did not (33.3%).

  Study phs003292

• Spatial Transcriptomics of Vaccine Therapy With or Without Cyclophosphamide in Treating Patients Undergoing Chemotherapy and Radiation Therapy for Stage I or Stage II Pancreatic Cancer That Can Be Removed by Surgery

  Pancreatic ductal adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. Here, spatial transcriptomics data were generated from 16 pancreatic cancer patients treated with GVAX, whose tumors presented with induced intratumoral TLS. Resected tumor specimens were embedded in OCT media and freshly frozen. Sections were cut into 6.5 x 6.5 mm dimensions compatible with Visium spatial transcriptomics slides. TLS-positive tumor sections from 14 patients (14 tumor samples in total) and lymph nodes from remaining patients (2 lymph node samples in total) were selected by an expert pathologist for profiling. We used 4 Visium slides and covered the 16 capture areas with sections cut in a cryostat at 10 µm. The fresh frozen Visium protocol was followed according to manufacturer's recommendations (10x Genomics Spatial 3' v1). Tissue permeabilization and library construction was carried out according to the manufacturer's protocols. Permeabilization time was optimized to 30 minutes. The captured tissue sections were permeabilized to allow RNA to be captured onto the slide where it reverse-transcribed to cDNA. The cDNA was then amplified, and sequencing libraries were prepared using the 10x Genomics Visium Spatial Gene Expression Reagent Kit for Library Preparation. The libraries were then sequenced using an Illumina NovaSeq sequencer. The raw data obtained from the sequencing were processed using the SpaceRanger (spaceranger-1.2.0) pipeline for alignment onto the GRCh38-2020-A reference transcriptome quantification of gene expression. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation.

  Study phs003862

• DNA Methylation in Prostate Tumor and Paired Benign Tissue for African and European Ancestry Men

  We recruited prostate cancer (PCa) patients undergoing robotic-assisted laparoscopic radical prostatectomy at the University of Chicago Medical Center Urology Clinic between 2011 and 2017. Our study includes 76 African American (AA) and 75 European American (EA) men with PCa of Gleason Score (GS) ≥7, recruited by the Epidemiology Research Recruitment Core at the University of Chicago. All patients consented to the collection of questionnaire data, prostate tissue, and medical records. The study was approved by the Institutional Review Board of the University of Chicago. Following prostatectomy, prostate tissue was sent to the Human Tissue Research Center (HTRC) at the University of Chicago. Each sample underwent histological examination and Gleason scoring by University of Chicago genitourinary pathologists. The presence of adenocarcinoma was confirmed by overexpression of alpha-methylacyl-coenzyme-A racemase (AMACR) and areas for DNA extraction were marked. Tissue samples used for DNA extraction were obtained using with either a 1mm biopunch or laser microdissection of a 100 µm2 area of tissue. Genome-wide DNA methylation profiles were generated using Illumina's Infinium MethylationEPIC BeadChip array kit. Genome-wide SNP data was generated (from benign tissue DNA) using the Illumina Infinium Multi-Ethnic Global-8 v1.0 array at the University of Chicago Genomics Core Facility. We performed imputation using the Haplotype Reference Consortium (HRC, Version r1.1 2016) panel, which includes all samples from the 1,000 Genomes Project (Phase 3), using the Michigan Imputation Server. The imputed SNP data for mQTL analysis was imputed based on genotype SNP data which was all from benign tissue DNA and the methylation data was identified in both tumor and benign tissue, both AA and EA men, and identified QTLs co-occuring with prostate cancer susceptibility loci.Data including SNP genotypes, DNA methylation, tissue type, and participant characteristics will be available in dbGaP.

  Study phs003516

• A prospective study identifies MisMatch Repair genes as candidate predisposing genes for uveal melanoma.

  Objective: The aim of this study is to identify new predisposing genes for uveal melanoma (UM), the most common intraocular malignancy in adults. Design: Prospective cohort study from Institut Curie. Participants: 381 unselected patients diagnosed with UM between July 2021 and February 2023 at Institut Curie. Methods: All patients received genetic counseling and consented to extended genetic testing. A panel of 122 genes was analyzed by targeted sequencing on germline DNA from these patients. Main outcomes measures: UM was diagnosed by ophthalmologists at Institut Curie, and a senior pathologist confirmed the diagnosis when tumor or biopsy was available. Classification of the germline genetic variants was performed according to the ACMG guidelines. Results: We identified at least one pathogenic variant (PV) in 79 patients. Among those variants, 20 were found in clinically relevant genes for the patient’s follow-up and genetic counseling. We found a significant enrichment of germline pathogenic variants in Mismatch Repair (MMR) MLH1, MSH2 and MSH6 genes in this UM cohort, suggesting that MMR germline alterations could predispose to UM. From this cohort, one tumor was available from a patient carrying a MLH1 germline mutation. The tumor was characterized by a monosomy 3, in line with a loss of heterozygosity (LOH) of MLH1, located on chromosome 3. Loss of expression of MLH1 and PMS2 was observed by immunohistochemistry, and MMR mutational signatures SBS6, ID1 and ID2 were identified from the whole genome sequencing of the tumor. These data suggest that MLH1 is implicated in the oncogenesis of this UM. Conclusions: This study is the largest prospective constitutional study performed on UM patients, and the first demonstrating that MMR germline alterations are significantly enriched among these patients. Further analyses will be needed to estimate the risk of developing UM for patients with Lynch syndrome

  Study EGAS50000000914

• Na?ve Treg-specific genomic DNA hypomethylation for autoimmune disease susceptibility

  Naturally occurring regulatory T (Treg) cells, which are specifically expressing the transcription factor FOXP3, CD25 and CTLA-4, are indispensable for the maintenance of immunological self-tolerance and homeostasis. Mutations of the FOXP3, CD25 and CTLA4 genes compromise the function of natural FOXP3+CD25+CD4+ Treg cells and cause severe autoimmune diseases showing Mendelian inheritance. Also, altered Treg-specific epigenetic changes, such as DNA hypomethylation and enhancer activation, impair the expression of these molecules in developing Treg cells, causing autoimmune diseases. It is obscure, however, whether Treg cells significantly contribute to the development of polygenic common autoimmune diseases (such as type 1 diabetes and rheumatoid arthritis), which afflict ~10% of the population. Recent genome-wide association study (GWAS) of common autoimmune diseases has revealed many autoimmune disease-associated single nucleotide polymorphisms (SNPs) in enhancer regions of immune cells, for example, in non-coding regions of T cell activation-associated genes such as CD25 and CTLA4. These findings, especially the involvement of common T-cell genes in the functions of both Treg cells and effector T cells, prompt one to ask whether autoimmune disease-associated causative SNPs impact on the functions of either disease-causing effector T cells or disease-suppressing Treg cells. Here, we have explored epigenetic profiles of human Treg and conventional T (Tconv) cells in na?ve or activated states, and found that autoimmune disease-associated SNPs are predominantly enriched in Treg-specific CpG demethylated regions (Treg-DRs), which were mostly included in Treg-specific super-enhancers. Treg-DRs are developmentally established in na?ve Treg cells before antigenic stimulation, distinct from activation-induced CpG hypomethylation in Treg or Tconv cells, and highly associated with Treg cell-specific transcriptional and epigenetic changes. Taken together, genetic variants affecting endogenous development of natural Treg cells and their Treg-intrinsic functions are causative of common autoimmune diseases, indicating natural Treg cells as a key target for their treatment and prevention.

  Study JGAS000145

• Metadata Public API

  Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

  Documentation discovery/metadata/public-metadata-api

• EGAD00010000768

  Replication data for HipSci normal samples using both HumanCoreExome-12_v1 and HumanOmni2.5-8 BeadChips

  Dataset EGAD00010000768

• Dataset for Parkinson's disease target re-sequencing project

  The dataset regards the sequencing of coding and putative regulatory sequences of 38 genes associated to either sporadic or Mendelian form of Parkinson's disease

  Dataset EGAD00001001029

• FASTQ NGS dataset for EGAS00001001632:New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs

  Dataset EGAD00001001927

• iPSC variation file (VCF) for EBiSC

  EBiSC Whole Genome Sequencing processed VCF including VEP consequences

  Dataset EGAD00001003934

• Yemen_Somali.Omni5

  The individuals were assayed for genome-wide SNP genotypes using the Illumina Human Omni5 Bead Chip (Illumina), which surveys 4,284,426 single nucleotide markers regularly spaced across the genome

  Dataset EGAD00010001651

• Colorectal cancer methylation profiling

  4 AC samples, each with adenoma, carcinoma and normal colon tissue (12 samples in total) were analysed on the Infinium MethylationEPIC BeadChip for copy number alteration analyses.

  Dataset EGAD00010001691

• Sequencing data for oesophageal and related samples - OACs release 6 (RNA)

  Dataset EGAD00001005375

• PromethION (and Illumina) WGS and MinION transcriptome for a patient with diffuse large B-cell lymphoma.

  Dataset EGAD00001006204

• P50_P681_P763_PTC209_DMSO_24h_48h_72h_Illumina HT12v4_Gene_Expression.xlsx

  Expression dataset for DAC+PTC209 treated CD34 sorted primary CML bone marrow samples

  Dataset EGAD00010002210

• Benchmark Dataset DIA Clinical Proteomics LymphNodes E.coli

  Real patient variability Benchmark Dataset for Optimization of DIA data analysis workflows

  Dataset EGAD00010002223

• Sequencing data for oesophageal and related samples - OACs release 3 (RNA)

  Dataset EGAD00001003900

• banfora_20150706_X

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - X chromosome.

  Dataset EGAD00010002579

• banfora_20150706_autosomes

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - autosomes.

  Dataset EGAD00010002581

• Batch1_Genotypes_Raw

  Genotypes generated for Puno cohort Batch 1. Case (PRE) and control (PUN) families were recruited in hospital, and additional unrelated controls were recruited in university (UNA). Raw genotypes no QC.

  Dataset EGAD00010002126

• H3K27ac HiChIP Dataset for 19 T-ALL patients and one normal control sample

  19 H3K27ac HICHIP from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference.

  Dataset EGAD50000000023

• Adaptive nanopore sequencing of chrX from peripheral samples

  Analysis of skewed X inactivation for X-linked disorders

  Dataset EGAD50000000638

• Patient TSO500 VCF files

  Tumours from MMRd EC patients treated with 2 cycles neoadjuvant ICI. TruSight Oncology 500 (TSO 500) panel for all 10 tumour samples from patients included in the trial.

  Dataset EGAD50000000694

• UniKilinikum Wuerzburg MSNZ AGRasche/AG Riedel EMD DAC

  This is a Data access committee for the Data presented in the paper tilted "Spatially resolved transcriptomics reveals profound subclonal heterogeneity and T cell dysfunction in extramedullary myeloma"

  Dac EGAC50000000173

• Profiling of human fecal microbiota for succinate consumption

  Enrichments of human stool samples in culture medium containing succinate as the main carbon source and the corresponding stool samples.

  Dataset EGAD50000000740

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  Raw bam file for bulk RNA-seq of checkpoint-blockade treated lung cancer cohorts

  Dataset EGAD50000000469

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Study EGAS50000000526

• Sequencing data for filanesib-treated hepatoblastoma samples

  This dataset contains RNA sequencing data of two hepatoblastoma PDX cell models. Cells were either treated with KSP inhibitor filanesib or with DMSO (controls).

  Dataset EGAD50000001314

• GCAT| SNParray coreSpain V3 TopMed

  4988 samples issued from GCAT cohort, genotyped with MEGAex-Infinium Array, with data for Cr1-23. Plink files with QC and imputed using TOPMed r2.

  Dataset EGAD00010002749

• RNA sequencing of mCRPC patient biopsies

  RNA sequencing of mCRPC patient biopsies obtained for the profiling of the prevalence of immune transcripts. Manuscript can be found at PMID: 35491356

  Dataset EGAD50000001811

• GCAT| SNParray GSA TopMed

  2746 samples issued from GCAT cohort, genotyped with GSA Array, with data for Cr1-23. Plink files with QC and imputed using TOPMed.

  Dataset EGAD00010002758