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• 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

• Serum Proteomics of Aortic Diseases

  Comparative proteome-based analysis of different autologous bone entities used for alveolar onlay grafting

  Dataset EGAD00010002314

• cqmuGWAS1

  DNA for 1546 individuals from Chongqing was extract from peripheral blood and genotyped by Illumina Omni Zhonghua-8 version 1 gene chips.

  Dataset EGAD00010001527

• Copy number profiling of primary samples and cell lines of retinoblastoma

  Illumina SNP-arrays for matching retinoblastoma-blood pairs and retinoblastoma cell lines.

  Dataset EGAD00010000908

• Long-term organoid culture of a small intestinal neuroendocrine tumor

  tissue, organoid and normal bam files for whole exome samples

  Dataset EGAD00001010162

• RNAseq data for EGAS00001004572

  Bulk RNA-seq data of tumours in EGAS00001004572.

  Dataset EGAD00001006876

• README-for-EGAS00001004349-linking-HIPO-K09R-RNA-files

  Dataset EGAD00001006785

• SF10432 Wildtype Primary GBM Female, 50

  Single Cell-RNA Seq of Wildtype Primary GBM for Female, Age 50.

  Dataset EGAD00001006019

• RNA sequencing BRAF fusion partners

  Contains RNAseq data for 14 transduced/non-transduced organoids

  Dataset EGAD00001005380

• Reference epigenome IPS01_N_Fibroblast_WGBS data generated from KEP study

  A IPS01_N_Fibroblast_WGBS paired end data for iPSC(Oct4)

  Dataset EGAD00001003473

• Reference epigenome IPS04_X_Fibroblast_WGBS data generated from KEP study

  A IPS04_X_Fibroblast_WGBS paired end data for iPSC(Oct4)

  Dataset EGAD00001003476

• MPB_Bonn

  1000Genomes imputed data set of 581 cases and 417 controls for male-pattern baldness

  Dataset EGAD00001001456

• DATA FILES FOR SJRB

  Retinoblastoma whole genome sequencing

  Dataset EGAD00001000261

• PD1-targeted delivery of an IL-2 variant induces a multifaceted anti-tumoral T cell response in human lung cancer

  To explore PD1-IL2v-specific effects on CD8 and CD4 T cells at a transcriptomic level, we performed single-cell RNA sequencing of patient-derived tumor fragments (PDTFs) which were treated with either Isotype (DP47), Isotype-IL2v (DP47-IL2v), anti-PD1 (PembroPGLALA) or PD1-IL2v (PembroPGLALA-IL2v) for 48 hours.

  Study EGAS50000000396

• Investigation of relapse prediction in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  In infants with ALL, accurate relapse prediction would enable treatment strategies that take relapse risk into account, with potential benefits for both low- and high-risk patients. Through analysis of bone marrow biopsies taken at initial diagnosis, we show that single-cell RNA sequencing can predict future relapse occurrence.

  Study EGAS00001003986

• Sex Differences in MAGEL2 Gene Promoter Methylation in High Functioning Autism - Trends from a Pilot Study Using Nanopore Cas9 Targeted Long Read Sequencing

  Using DNA extracted from peripheral blood, Cas9-targeted nanopore DNA sequencing was used to analyze MAGEL2 gene, including its entire regulatory construct (chr15:23639316-23651466), for sequence variation and 5-methyl-cytosine (5mC) modification in a cohort of adults with HFA compared to sex- and age-matched NC.

  Study EGAS50000000508

• Bulk RNA-seq of monocytes and in vitro cultured monocyte-derived macrophages of ANCA-associated vasculitis patients with active and stable disease and healthy controls

  To study monocyte and macrophage activation in ANCA-associtated vasculitis (AAV), we performed bulk RNA sequencing of bead-selected monocytes and in vitro cultured monocyte-derived macrophages from AAV patients and healthy controls. Overview patients included for sequencing monocytes: - AAV active disease, n=4, MPO-AAV=4 - AAV remission, n=10, PR3-AAV=5, MPO-AAV=5 - Healthy controls, n=6 Overview patients included for sequencing monocyte-derived macrophages: - AAV active, n=1, PR3-AAV=1 - AAV remission, n=3, PR3-AAV=3 - Healthy controls, n=3

  Dataset EGAD50000000450

• Normal sample for patient SA598

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA598

  Dataset EGAD00001009246

• Normal sample for patient SA599

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA599

  Dataset EGAD00001009247

• Normal sample for patient SA600

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA600

  Dataset EGAD00001009248

• Normal sample for patient SA601

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA601

  Dataset EGAD00001009249

• Normal sample for patient SA654

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA654

  Dataset EGAD00001009250

• Normal sample for patient SA655

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA655

  Dataset EGAD00001009251

• Normal sample for patient SA665

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA665

  Dataset EGAD00001009252

• Normal sample for patient SA667

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA667

  Dataset EGAD00001009253

• Normal sample for patient SA668

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA668

  Dataset EGAD00001009254

• Normal sample for patient SA669

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA669

  Dataset EGAD00001009255

• Normal sample for patient SA671

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA671

  Dataset EGAD00001009256

• Normal sample for patient SA672

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA672

  Dataset EGAD00001009257

• Tumour sample for patient SA1035

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1035

  Dataset EGAD00001009258

• Tumour sample for patient SA994

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA994

  Dataset EGAD00001009259

• Tumour sample for patient SA604

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA604

  Dataset EGAD00001009260

• Tumour sample for patient SA605

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA605

  Dataset EGAD00001009261

• Tumour sample for patient SA609

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA609

  Dataset EGAD00001009262

• Normal sample for patient SA596

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA596

  Dataset EGAD00001009245

• Normal sample for patient SA595

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

  Dataset EGAD00001009244

• Normal sample for patient SA593

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

  Dataset EGAD00001009243

• Normal sample for patient SA592

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

  Dataset EGAD00001009242

• RNA and whole-exome sequencing of 22 patients with non-small cell lung cancer

  Whole exome sequencing from pre-treatment samples and matched blood normals from 22 patients. Of these individuals, on-treatment samples are available for a subset of 18 patients. RNA sequencing from pre-treatment samples from 21 patients. Of these individuals, on-treatment samples are available for a subset of 15 patients.

  Dataset EGAD00001008733

• 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

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - chemo_cohort

  Dataset EGAD00001002241

• 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

• 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

• WGS data for MMML (EGAS00001002422)

  Whole genome sequencing data for MMML (7 tumors and 8 controls)

  Dataset EGAD00001003286

• RNA data for MMML (EGAS00001002422)

  RNA sequencing data for MMML (3 tumor samples and 1 gcbcell)

  Dataset EGAD00001003285

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  ChIP-Seq data for 154 CD4-positive, alpha-beta T cell sample(s). 355 run(s), 265 experiment(s), 250 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002673

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672