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• Paired exome and low-coverage genome sequencing of osteosarcoma

  We perform longitudinal genome-sequencing analysis of 12 patients with metastatic or refractory osteosarcoma. The study was approved at the University Hospital Basel, following the approval of the ethical committee for mutational analysis of anonymized samples (“Ethikkommission beider Basel” ref. 274/12). All tumor samples were evaluated by an experienced bone pathologist to confirm the diagnosis.

  Study EGAS00001005199

• Single-cell RNA sequencing dissects gene-environment interactions on gene expression and regulation in immune cells.

  This study aims to dissect gene-environment interactions on gene expression and regulation in immune cells using scRNA-seq data from 120 donors being stimulated with 3 pathogens, for 2 different timepoints. More specifically, we identified context- and cell-type-specific eQTLs and co-expression QTLs in PBMCs.

  Study EGAS00001005376

• Finding structural variation and functional consequences from the primary leukemia cells (AML) at the single-cell level

  In this study, we aimed to identify somatic structural variation of acute myeloid leukemia (AML) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 32 year old male donor.

  Study EGAS00001004903

• Bone marrow single cell genomics from blood cancer samples

  The overall goal of this study was to characterize bone marrow cells based on their transcriptome, surface protein expression and BCR- and TCR VDJ-profile for accurate identification of clinically relevant cell states. This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 824110 (EASI-Genomics)

  Study EGAS00001007332

• Deep sequencing of melanoma for driver mutations

  Deep sequencing of melanoma for driver mutations

  Dataset EGAD00001001445

• BLUEPRINT release August 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001534

• BLUEPRINT release January 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001165

• BLUEPRINT release August 2014, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 4 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 22 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000903

• BLUEPRINT release August 2016, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  RNA-Seq data for 6 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 24 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002339

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Clinical data

  Clinical data from IMvigor210, POPLAR, IMmotion150: Clinical data include demographics, tumor type, PD-L1 IHC, tumor mutation burden, objective response rate, overall survival and progression free survival for 611 patients across IMvigor210, POPLAR and IMmotion150. Clinical data from PCD4989g: Clinical data include tumor type, PD-L1 expression and objective response rate for 206 patients from PCD4989g.

  Dataset EGAD00001006630

• Tumour sample for patient SA533

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA533

  Dataset EGAD00001009517

• Tumour sample for patient SA420

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA420

  Dataset EGAD00001009519

• Tumour sample for patient SA296

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA296

  Dataset EGAD00001009520

• Tumour sample for patient SA409

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA409

  Dataset EGAD00001009518

• Tumour sample for patient SA597

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA597

  Dataset EGAD00001009521

• Sequencing data for oesophageal and related samples - Ganguli et al (WGS)

  Data supporting: "TBC" Ganguli et al (WGS for 1298 samples)

  Dataset EGAD00001011191

• AWI-GEN 2 Phenotype Dataset

  Core phentoype data for AWI-Gen Phase 2 Microbiome Project for 1824 samples.

  Dataset EGAD00001015440

• Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

  The dataset for the study Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer includes 207 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 30 individuals with non-small cell lung cancer, alongside 46 bam files from whole exome sequencing of tumor and matched normal DNA for 21 individuals with non-small cell lung cancer who received immunotherapy-containing regimens.

  Dataset EGAD00001011991

• Cancer Genomics, ICR, summary data

  DAC for summary level data from the Cancer Genomics group, Division of Genetics and Epidemiology at the Institute of Cancer Research, Sutton, UK.

  Dac EGAC50000000050

• Picuris Pueblo Genomic Project (Modern Data)

  Data Access Committee for the present-day dataset of the project "Picuris Pueblo oral history and genomics reveal continuity in US Southwest".

  Dac EGAC50000000526

• University Clinic Golnik DAC

  DAC of the University Clinic Golnik, that will decide regarding the requests for data submitted on behalf of research groups of the Clinic

  Dac EGAC50000000820

• Ontario Institute for Cancer Research; Biliary Tract Cancer

  Next Generation Sequencing data from Biliary Tract cancers

  Study EGAS50000000972

• Bulk RNA-Seq Digital Gene Expression Matrix

  Raw read counts and normalized read counts for each gene

  Dataset EGAD50000002489

• DNABR

  Genome variation data for 2723 Brazilian individuals from the DNA do Brasil Project.

  Dataset EGAD50000001012