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• 10x Genomics Single Cell Gene Expression for SA1056

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 116.126

  Dataset EGAD00001009112

• 10x Genomics Single Cell Gene Expression for SA1054

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 83.86

  Dataset EGAD00001009113

• 10x Genomics Single Cell Gene Expression for SA604X8XB02164

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 8

  Dataset EGAD00001009118

• 10x Genomics Single Cell Gene Expression for SA604X6XB01979

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 6

  Dataset EGAD00001009117

• 10x Genomics Single Cell Gene Expression for SA1035X4XB02879

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 4

  Dataset EGAD00001009147

• 10x Genomics Single Cell Gene Expression for SA1050FX1XB01446

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009125

• 10x Genomics Single Cell Gene Expression for SA1050DX1XB01437

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009126

• 10x Genomics Single Cell Gene Expression for SA1052BX1XB01516

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009127

• 10x Genomics Single Cell Gene Expression for SA1053FX1XB01611

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009128

• 10x Genomics Single Cell Gene Expression for SA1093CX1XB01917

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1093 passage 1

  Dataset EGAD00001009129

• 10x Genomics Single Cell Gene Expression for SA1091AX1XB01790

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1091 passage 1

  Dataset EGAD00001009130

• 10x Genomics Single Cell Gene Expression for SA1053BX1XB01603

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009131

• 10x Genomics Single Cell Gene Expression for SA1096AX1XB02034

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009132

• 10x Genomics Single Cell Gene Expression for SA1051DX1XB01482

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009133

• 10x Genomics Single Cell Gene Expression for SA1052JX1XB01535

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009134

• 10x Genomics Single Cell Gene Expression for SA1181AX1XB02700

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1181 passage 1

  Dataset EGAD00001009135

• 10x Genomics Single Cell Gene Expression for SA1096CX1XB02039

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009136

• 10x Genomics Single Cell Gene Expression for SA1096BX1XB02037

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009137

• 10x Genomics Single Cell Gene Expression for SA1162BX1XB03004

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1162 passage 1

  Dataset EGAD00001009138

• 10x Genomics Single Cell Gene Expression for SA1096A

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1096

  Dataset EGAD00001009139

• 10x Genomics Single Cell Gene Expression for SA1049CX1XB01422

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

  Dataset EGAD00001009140

• 10x Genomics Single Cell Gene Expression for SA1050EX1XB01442

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009141

• 10x Genomics Single Cell Gene Expression for SA605X3XB01966

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA605 passage 3

  Dataset EGAD00001009142

• 10x Genomics Single Cell Gene Expression for OV2295

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295

  Dataset EGAD00001009143

• 10x Genomics Single Cell Gene Expression for OV2295(R2)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295(R2)

  Dataset EGAD00001009144

• 10x Genomics Single Cell Gene Expression for SA1184SA

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1184

  Dataset EGAD00001009145

• 10x Genomics Single Cell Gene Expression for SA1047BX1XB01022

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1047 passage 1

  Dataset EGAD00001009146

• 10x Genomics Single Cell Gene Expression for SA1035X8XB03425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 8

  Dataset EGAD00001009148

• 10x Genomics Single Cell Gene Expression for SA535X6XB03101

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009149

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03211

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009150

• CM214 - Biomarker Analysis From the Phase 3 CheckMate 214 Trial of Nivolumab Plus Ipilimumab (N+I) or Sunitinib (S) in Advanced Renal Cell Carcinoma (aRCC)

  CM214 - Biomarker Analysis From the Phase 3 CheckMate 214 Trial of Nivolumab Plus Ipilimumab (N+I) or Sunitinib (S) in Advanced Renal Cell Carcinoma (aRCC)

  Study EGAS00001005501

• single cell RNA-seq data of 10 small cell lung cancer patients

  This dataset contains 10 paired fastq files sequenced on Illumina NextSeq 550 sequencer. Tumors were rapidly dissociated after the surgical procedure using the Miltenyi Biotec Human Tumor Dissociation kit (cat# 130-095-929). Libraries were constructed using the VDJ NextGEM v1.1 10x Genomics Chromium kit. Single cell RNA-seq analysis was performed using Seurat R package.

  Dataset EGAD50000002034

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 15)

  The dataset contains whole genome sequencing data of 8 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 16 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000526

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 16)

  The dataset contains whole genome sequencing data of 58 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 144 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000777

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 14)

  The dataset contains whole genome sequencing data of 42 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 100 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000507

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 11)

  The dataset contains whole genome sequencing data of 23 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 89 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000313

• Exome_sequencing_Parkinson_s_disease_patients

  In this project we will sequence the exomes of 250 patients with Parkinson's disease

  Study EGAS00001000151

• BCG-Flu_Challenge_Study_RNAseq_Human_01

  RNA sequencing data generated from human samples collected in the BCG-Flu Challenge study.

  Study EGAS50000001677

• USH genes sequencing

  Sequencing of a panel including the whole genomic sequence of Usher genes.

  Study EGAS50000000476

• Brain_Disease_Wellcome_Leap_Delta_Tissue_RNA

  Utilising Single-Nucleus sequencing to investigate how the tumour microenvironment regulates glioblastoma cell states.

  Study EGAS00001005800

• Finnish - THL SUPER

  The dataset encompasses 852 Runs from the WGSPD Project 3 - Genomic Strategies to Identify High-impact Psychiatric Risk Variants Project

  Dataset EGAD50000001466

• Samples from the Greek island of Crete, MANOLIS cohort

  Whole-genome sequencing at 4x of 250 samples from the Greek isolatecollection HELIC

  Dataset EGAD00001001636

• Covacta OLINK NPX

  Olink Explore 1536 dataset from serum of patients enrolled in the COVACTA trial. This dataset includes the NPX values provided by Olink.

  Dataset EGAD00001011169

• Whole_Exome_Sequencing_of_INTERVAL

  Whole exome sequencing of a subset of participants from the INTERVAL study.

  Study EGAS00001000825

• Exome sequencing identifies mutation of the ribosome in T-cell acute lymphoblastic leukemia

  Exome sequencing identifies mutation of the ribosome in T-cell acute lymphoblastic leukemia

  Dataset EGAD00001000291

• Exome sequences of three individuals from the EXCEED study

  Exome sequences of three unrelated individuals of south Asian ancestry from the EXCEED study

  Dataset EGAD00001007649

• Whole exome sequencing and RNA-seq of esophageal squamous cell carcinoma

  We perform integrative genome-wide analyses such as whole-exome sequencing, copy number variant(CNV) analysis, and gene expression analysis using next-generation sequencing and other methods to elucidate driver genes and signaling pathways causing tumorigenesis and cancer progression, leading novel molecular diagnostics and molecular therapies.

  Study JGAS000367

• The study provides comprehensive access to the set of EGA studies which may be useful as controls.

  The subjects studies in these datasets were selected due to being healthy control individuals or otherwise provide well characterised phenotype or exclude certain disease phenotype categories such that they may be useful as control population, such as to derive allele frequencies from a known reference population.

  Study EGAS00001000646

• COVID-19 GWAS in Japanese

  The Japan COVID-19 Task Force (JCTF) was established in early 2020 as a nation-wide multicenter consortium to overcome the COVID-19 pandemic in Japan. We conducted a genome-wide association study (GWAS) involving 2,393 Japanese COVID-19 cases collected in initial pandemic waves with 3,289 controls. GWAS genotyping was performed using Infinium Asian Screening Array (Illumina, USA).

  Study EGAS00001006284

• Family Genomics of Bipolar Disorder

  This study examined the segregation of variants with phenotype in pedigrees harboring bipolar disorder.

  Study phs000866

• Juvenile Idiopathic Arthritis exome sequencing in a consanguineous family

  Identify the causative gene defect in three affected patients with JIA.

  Study EGAS00001003510

• SCC tumor sequencing

  In this study we have sequenced the tumor of 28 Squamous Cell Carcinoma patients.

  Study EGAS00001003988

• Belgian epilepsy control individuals

  Genomic DNA from Belgian control individuals was pooled. Then the genomic sequence of brain expressed miRNA genes was determined in the pools.

  Dataset EGAD00001001852

• Swedish schizophrenia control individuals

  Genomic DNA from Swedish control individuals was pooled. Then the genomic sequence of brain expressed miRNA genes was determined in the pools.

  Dataset EGAD00001001850

• He et al. WGS data

  This dataset are the bam files of WGS data from the paper by He et al.

  Dataset EGAD00001007133

• Finnish - THL Health2000 Dataset

  The dataset encompasses 208 Runs from the WGSPD Project 3 - Genomic Strategies to Identify High-impact Psychiatric Risk Variants Project

  Dataset EGAD00001008684

• Genomic and transcriptomic profiling of combined hepatocellular and intrahepatic cholangiocarcinoma reveals distinct molecular subtypes

  We performed genomic and transcriptomic sequencing of 133 combined hepatocellular and intrahepatic cholangiocarcinoma (cHCC-ICC) cases, including separate, combined, and mixed subtypes.

  Study EGAS00001003093

• CATNON: IDH-mutant astroctyoma RNA FASTQ

  Raw fastq files obtained by RNA sequencing 138 IDH-mutant astrocytomas included in the CATNON trial. RNA was extracted from formalin-fixed paraffin-embedded (FFPE) tissue blocks using the RNeasy FFPE kit. RNA sequencing was performed on an Illumina NovaSeq 6000 (GenomeScan BV, Leiden, The Netherlands) with 150bp paired-end reads including UMI tags.

  Dataset EGAD50000000558

• Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma

  Discovery of resistance mechanisms to the BRAF inhibitor vemurafenib in metastatic BRAF mutant melanoma by massively-parallel sequencing of tumour samples. Comparison of genomic characteristics of pretreatment 'sensitive' to recurrence 'resistant' tumours to identify the genetics of drug resistance.

  Dataset EGAD00001000707

• Complete Metagenomics from feces

  Complete Microbiome Metagenomics from feces of 461 IBD patients; The sequencer used was the Illumina HiSeq 2000 with a paired end reads design, reflected in the 2 FastQ format files per sample.

  Dataset EGAD00001004194

• Haemoglobin_E_beta_thalassaemia_in_a_patient_group_from_Sri_Lanka

  Exome sequencing of 32 patient samples from Sri Lanka with the condition haemoglobin E beta thalassaemia

  Study EGAS00001000626

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Total RNA was extracted from the PaxFPE biopsy specimens (n = 116)

  Study EGAS50000000337

• Genomic profiling of two pathogenic germline truncating variants of BRCA2 confer different haploinsufficiency phenotype

  Observation of the loss of heterozygosity of BRCA2

  Study EGAS50000000613

• BAM files ChIP-Seq

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001669

• Molecular landscape of C1498 cells

  We characterized the genomic background of C1498 cells by whole genome sequencing analysis.

  Study EGAS50000001284

• SCLC tumor sequencing

  In this study we have sequenced the tumor of 28 Small Cell Lung Cancer patients.

  Study EGAS00001003985

• Tumor Profiler AML Study

  Multi-omics data generated from 22 samples from the Tumor Profiler AML cohort

  Study EGAS50000000577

• Targeted_sequencing_of_in_vitro_colonies___bulks

  In this study we will perform targeted sequencing on the bulk samples of in vitro colonies

  Study EGAS00001003175

• Targeted_EMSeq___Development

  Development of a targeted methylation assay to determine the cell-type composition of a sample.

  Study EGAS00001007202

• Finnish - THL Psychiatric Family Collection Dataset

  The dataset encompasses 172 Runs from the WGSPD Project 3 - Genomic Strategies to Identify High-impact Psychiatric Risk Variants Project

  Dataset EGAD00001009315

• Genetic and methylation profiles distinguish benign, malignant and spitzoid melanocytic tumors

  Genetic and methylation profiles distinguish benign, malignant and spitzoid melanocytic tumors

  Study EGAS00001006205

• WES of paired gDNAs and PPGL tumor DNA from patients with CCHD-PPGL.

  WES of paired germline DNA (12) and PPGL tumor DNA (14) from peripheral blood/saliva and formalin-fixed paraffin-embedded (FFPE) blocks from surgery, respectively, from patients with congenital heart disease (CCHD) and pheochromocytoma and paraganglioma (PPGL).

  Study EGAS50000000815

• MSI_Cancer_Models___RNAseq

  The study will use RNAseq to aid in define determinants of WRN dependency in MSI Cell lines.

  Study EGAS00001004180

• Single cell RNAseq of PDAC organoids

  To study the role of WNT7B, three organoid lines were sequenced using SORT-Seq

  Study EGAS50000001544

• 15x_WGS_HELIC_MANOLIS_

  15x whole genome sequencing in samples from the Cretan Greek isolate collection HELIC MANOLIS

  Study EGAS00001001207

• Ni_Vanuatu_Omni2.5

  Blood DNA samples from 1,433 contemporary ni-Vanuatu were genotyped on the Illumina Infinium Omni 2.5-8 array. Genotype calling was performed using the Illumina GenomeStudio software.

  Dataset EGAD00010002344

• Targeted deep sequencing of somatic mutations

  We used targeted deep sequencing to accurately establish the allele frequencies of the mutations identified by exome sequencing

  Dataset EGAD00001000763

• WES from two human osteosarcoma with two samples each from the corresponding cell line

  WES from two human osteosarcoma with two samples each from the corresponding cell line, BAM files

  Dataset EGAD00001005370

• WGS data set used in the study, 2 samples

  WGS data set used in the study, 2 samples

  Dataset EGAD00001007966

• Pilot_Fetal_Cell_Atlas_RNAseq

  As part of the Human Cell Atlas we will study fetal tissue.

  Study EGAS00001002553

• DNA methylation changes associated with hyperglycemia in type 1 diabetes

  This dataset includes DNA methylation profiles from 112 young with Type 1 Diabetes (T1D) at T1D diagnosis, who were longitudinally monitored for hyperglycemia over an average duration of 3 years. These datasets were generated using whole-genome bisulfite sequencing. It includes 1872 fastq files (i.e. 936 paired-end fastq files) generated through 150 bp paired-end sequencing on Illumina HiSeqX.

  Dac EGAC50000000237

• Transcriptomics for UPST-SCCHN3 cohort

  Transcriptomics of Tumor samples on UPST-SCCHN3 cohort

  Dataset EGAD50000002179

• Metadata associated with sequencing

  Associated metadata for sequencing data.

  Dataset EGAD50000000528

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

  Dataset EGAD00001001927

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - TLR_pathway_study

  upcoming publication

  Dataset EGAD00001001960

• McGill EMC Community projects Release 7 for cell line "SaOS-2"

  Complete reference epigenome (as defined by IHEC) of a SaOS-2 cell line with osteosarcoma.

  Dataset EGAD00001007678

• High coverage Whole exome DNA sequencing on pre-treatment tumor samples (n=3) matched with post-treatment metastasized lymph nodes isolated with laser microdissection (n=3)

  Data from NABUCCO cohort 1 (NCT03387761). This dataset includes High coverage Whole exome DNA sequencing on pre-treatment bladder tumor samples (n=3) matched with post-treatment metastasised adjacent lymph nodes isolated with laser microdissection (n=3) for 3 unique patients

  Dataset EGAD00001006852

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 12)

  The dataset contains whole genome sequencing data of 17 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 46 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000441

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 13)

  The dataset contains whole genome sequencing data of 32 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 82 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000442

• Detecting PKD1 variants in Polycystic Kidney Disease patients by single-molecule long-read sequencing

  Cohort of 19 ADPKD patients characterized using long-read sequencing. The variant identification provided high sensitivity in identifying PKD1 pathogenic variants, with a diagnostic yield of 94.7%. This dataset includes all sequencing data (BAM files) of the 19 patients, in addition to their raw variants (unfiltered) obtained from the long-read sequencing as well as Sanger sequencing (VCF file).

  Dataset EGAD00001003103

• MiRNome_pituitary_adenoma

  Small RNA (<100 bases in length) were purified from total RNA using miRNeasy kit (Qiagen), then sequenced. Libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq small RNA protocol (Illumina), starting from 1 µg of high quality total RNA. Single read (1 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on miRBase v.2052, then counted with STAR (v.2.5.2a).

  Dataset EGAD00001004998

• Paired RNA-Seq of four patients with advanced Parathyroid carcinoma (PC)

  Paired RNA-Seq of four patients with advanced Parathyroid carcinoma (PC). The library was prepared using the Illumina TruSeq stranded mRNA Kit, the sequencing was done either on an Illumina HiSeq 4000 or on Illumina NovaSeq 6000.

  Dataset EGAD00001009730

• Leeds Melanoma Cohort (LMC) gene expression study

  Array-based profiling (whole genome DASL HT12.4, Illumina Inc) in over 700 FFPE tumour blocks from the population-based Leeds Melanoma cohort recruited in the North of England, with a long follow up. Data used in tumour immune micro-environment investigation (Nsengimana et al 2018, J Clin Invest doi: 10.1172/JCI95351).

  Study EGAS00001002922

• GWAS study on arsenic-exposed population

  Genetic analysis of women from the Andes Mountains that are exposed to arsenic in drinking water.

  Study EGAS00001001168

• Use_of_deep_sequencing_to_detect_clonal_mutations_in_sun_exposed_human_epidermis___whole_genome

  Deep sequencing of two skin biopsies to study the landscape of somatic mutations in human adult tissues.

  Study EGAS00001000860

• Pulldown_cytosine_deaminases

  We are looking at the causal factors behind hyper-mutator phenotypes found in previous Breast Cancer sequencing studies.

  Study EGAS00001000233

• MMR (DNA mismatch repair) pathway in human samples

  This data are related to the manuscript by Germano et al. Ms2016-04-06029

  Study EGAS00001002694

• Germline sequencing

  Detection of SNVs/indels in the germline of pediatric cancer patients with a focus on CHEK2 germline variants.

  Study EGAS00001006254

• Germline sequencing

  Detection of SNVs/ indels in the germline of pediatric cancer patients with a focus on CHEK2 germline variants

  Study EGAS00001006705

• HCA_Immune_Adult_CIDP_RNA_Managed_Access

  Leveraging single-cell sequencing technologies to shed light on the immune aetiology of chronic inflammatory demyelinating polyradiculoneuropathy (CIDP)

  Study EGAS00001007419