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• Tumour sample for patient SA679

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA679

  Dataset EGAD00001009346

• Tumour sample for patient SA678

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA678

  Dataset EGAD00001009345

• Tumour sample for patient SA677

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA677

  Dataset EGAD00001009344

• Tumour sample for patient SA676

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA676

  Dataset EGAD00001009343

• Tumour sample for patient SA675

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA675

  Dataset EGAD00001009342

• Tumour sample for patient SA674

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009341

• Tumour sample for patient SA673

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA673

  Dataset EGAD00001009340

• Tumour sample for patient SA218

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA218

  Dataset EGAD00001009177

• Tumour sample for patient SA219

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA219

  Dataset EGAD00001009178

• Tumour sample for patient SA272

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA272

  Dataset EGAD00001009179

• Tumour sample for patient SA274

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA274

  Dataset EGAD00001009180

• Tumour sample for patient SA275

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA275

  Dataset EGAD00001009181

• Tumour sample for patient SA276

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA276

  Dataset EGAD00001009182

• Tumour sample for patient SA279

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA279

  Dataset EGAD00001009183

• Tumour sample for patient SA283

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA283

  Dataset EGAD00001009184

• Tumour sample for patient SA287

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA287

  Dataset EGAD00001009185

• Tumour sample for patient SA394

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA394

  Dataset EGAD00001009186

• Tumour sample for patient SA395

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA395

  Dataset EGAD00001009187

• Tumour sample for patient SA398

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009188

• Tumour sample for patient SA402

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA402

  Dataset EGAD00001009189

• Tumour sample for patient SA404

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA404

  Dataset EGAD00001009190

• Tumour sample for patient SA530

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA530

  Dataset EGAD00001009191

• Tumour sample for patient SA585

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA585

  Dataset EGAD00001009192

• Tumour sample for patient SA586

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA586

  Dataset EGAD00001009193

• Tumour sample for patient SA588

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA588

  Dataset EGAD00001009194

• Tumour sample for patient SA591

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA591

  Dataset EGAD00001009197

• Tumour sample for patient SA592

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA592

  Dataset EGAD00001009198

• Tumour sample for patient SA593

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA593

  Dataset EGAD00001009199

• Tumour sample for patient SA590

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA590

  Dataset EGAD00001009196

• Tumour sample for patient SA589

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA589

  Dataset EGAD00001009195

• Tumour sample for patient SA595

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA595

  Dataset EGAD00001009200

• The EMC-HEMA-AML data access committee controlling the access to AML sequencing data generated in the Hematology department of Erasmus MC

  Dac EGAC00001002230

• The Jerusalem Perinatal Study

  The Jerusalem Perinatal Study (JPS) aimed to examine the developmental origins of cardiometabolic risk.

  Dataset EGAD00010001816

• POLG data MS-affected co-twins

  paired-end BAM files of the sequencing analysis of the mtDNA polymerase gamma (POLG) gene in the MS-affected co-twins

  Dataset EGAD00001002189

• The Genomic Map of Polad in Open Access

  Part of the population based Cohort of Polish inviduals POPULOUS (bbmri-eric:ID:PL_BLUL:collection:POPULOUS_BLUL)

  Study EGAS50000000094

• Spatial

  This dataset contains the raw sequencing data (Runs) from all of the 10x Genomics single-cell Visium Experiments, as well as the corresponding imaging data (Analyses).

  Dataset EGAD00010002379

• Copy number profile of ctDNA in ovarian cancer patients

  This study analyzes the copy number profiles from circulating tumor DNA (ctDNA) in plasma samples withdrawn from ovarian cancer patients, in a subset of samples from the MITO16A clinical trial.

  Study EGAS00001008226

• A comprehensive genetic map of cytokine responses in Lyme borreliosis

  A study on the genetic determinants of immune response in patients diagnosed with Lyme borreliosis. Examining the link between genetic variants and cytokine response in more than 1,000 patients.

  Study EGAS50000000024

• NanoSeq of buccal swab samples

  16 buccal swab samples were analyzed by Nanoseq. S3 in the file names indicates 28 mm^2 swab size, and S5 indicates 254 mm^2 swab size. We analyzed 28 mm^2 swab samples using paired 254 mm^2 swab samples as controls. The files were generated by the Nanoseq pipeline using GRCh37 as the reference genome.

  Dataset EGAD50000000999

• NSCCG_CRC_GWAS

  Genotype data of 7,281 individuals with colorectal cancer from the National Study of Colorectal Cancer Genetics (NSCCG) study. Individuals genotyped on the Illumina OncoArray. Data provided in plink format and has not been quality controlled. Control samples used were obtained from the PRACTICAL and BCAC consortia, and are available through the respective Data Access Coordination Committees (http://practical.icr.ac.uk and http://bcac.ccge.medschl.cam.ac.uk/)

  Dataset EGAD00010002184

• PDX_HTA2.0_Guergen2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) and RCC metastases related to Guergen et al, Front Oncol 12:2022 889789. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.34.0). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 25).

  Dataset EGAD00010002392

• RCC_HTA2.0_Buettner2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Buettner et al, Genome Med 2022. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002353

• Whole_Genome_Sequencing_OMELib__Cord_blood_

  The mutational landscape of haematopoietic cells will be characterized by WGS following amplification of DNA and preparation of libraries by PTA(primary template-directed amplification). Samples have been sourced from the Cambridge Biobank.

  Study EGAS00001007453

• Dynamic N6-methyladenosine Epitranscriptomic Landscape in Lung Adenocarcinoma

  Systematically evaluate the global effect of dysregulated m6A regulators on the m6A epitranscriptome in patient tumors, and identify prognostic m6A markers by linking with patients' clinicopathological and outcome information.

  Study EGAS00001005524

• Osteosarcoma whole genome rearrangement screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from Osteosarcoma cancer patients and subjected to short paired end sequencing on the llumina platform. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Dataset EGAD00001000368

• Highlighted samples from the BCH CRDC

  These exomes are from some of the patients and family members detailed in our forthcoming publication, Children’s Rare Disease Cohorts: an integrative research and clinical genomics initiative. While this paper details an institutional collection of exomes, the samples here were specifically highlighted as having significant findings.

  Study EGAS00001004436

• Genetic dysregulation of gene expression and splicing during a ten-year period of human aging in the PIVUS study

  We performed RNA sequencing in whole-blood from the same individuals from the PIVUS study at ages 70 and 80 to quantify how gene expression, alternative splicing, and their genetic regulation are altered during this 10-year period of advanced aging.

  Study EGAS00001003583

• Case-control study with RNA-seq transcriptome between ASD patients and non ASD controls.

  Aim: To elucidate gene expression differences in the cerebellar tissues between ASD and normal control segmented by age. Object: The cerebellar tissues used in our study are from 16 autistic patients and 17 control patients. Method: We investigated the mRNA expression differences using RNA-seq between ASD and controls by age. We further investigated mRNA isoform expressions segmented by age.

  Study JGAS000668

• Longitudinal Single-cell Genomic Analysis of Initial and Recurrent Meningioma

  This study investigates the genomic evolution of meningioma through single-cell whole genome sequencing analysis of paired tumor samples. We analyzed tumor tissues from initial and recurrent meningiomas from the same patients to understand clonal evolution and tumor progression. The research aims to characterize copy number alterations and genomic heterogeneity at single-cell resolution across different time points of tumor development.

  Study EGAS50000000860

• Whole_Genome_sequencing_of_individuals_from_Carlantino__Italy

  This study includes whole-genome sequencing data (at 4x depth) of 100 individuals from an Italian genetic isolate population (Carlantino, abbreviated CARL) of the Italian Network of Genetic Isolates (INGI). The INGI-CARL_SEQ project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits.

  Study EGAS00001000460