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• Anaplastic Meningioma WGS-X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Dataset EGAD00001001267

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 45 low-risk myelodysplastic syndrome cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 45 low-risk myelodysplastic syndrome (LRMDS) cases. Gene expression profiles (GEPs) of the 45 LRMDS have been compared to GEPs derived from likewise highly purified mesenchymal cells obtained from bone marrow specimens of healthy donors for the identification of inflammatory signatures. Additionally, an overlap in inflammatory signatures has been determined by comparing the GEPs of these 45 LRMDS cases to the GEPs of 4 Shwachman-Diamond syndrome and 3 Diamond-Blackfan anemia cases, both representing different subclasses of congenital pre-leukemia syndromes with a tendency of leukemic progression and perturbed niche compartment. Finally, the GEPs and gene expression signatures have been utilized for prognostication and the prediction of leukemic progression.

  Dataset EGAD00001002658

• Targeted bisulfite sequencing

  Raw reads from targeted bisulfite sequencing. The SureSelect Methyl-Seq target enrichment system (Agilent Technologies, Inc., CA, USA) was used to prepare bisulfite sequencing libraries from blood DNA samples of lymphoma patients (Ly1, Ly2), healthy family members (Ly8, Ly9, Ly10, Ly11, Ly12, Ly13 and Ly14), baseline controls (Control1-5), DNMT3A mutation carriers (Id5, Id7, Id9, Id11) and their age-matched controls (Id6, Id8, Id10, Id12). In addition, blood DNA sample of a patient (HLRCC_N7) with germline fumarate hydratase (FH) mutation is included. Illumina paired-end sequencing for targeted libraries from Ly1, Ly2, Ly8, Ly9, Ly10 and Ly11 was done at Karolinska Institutet using 100 base-pair read length and the HiSeq2000 platform. Illumina paired-end sequencing for targeted libraries from Ly12, Ly13, Ly14, and DNMT3A mutation carriers and their age-matched controls was done as a service at BGI (BGI Tech Solutions Co., Ltd., China) using 126 base-pair read length and the HiSeq2500 platform.

  Dataset EGAD00001004785

• Patient tumour data (RNAseq, WGBS, ChIPseq, WGS)

  Content: 60 GB patient tumours and 4 normal brain samples combined in pairs by region (x2=8 total input samples). RNAseq: 1 lane per sample, total strand-specific rRNA-depleted (normal samples were combined = 2 lanes/samples per brain region). WGBS: 2 lanes per sample (normal samples were combined = 2 lanes/samples per brain region). ChIPseq (histone mark): a subset of 20 GB samples were profiled. For the same modification were multiplexed and sequenced on 4 lanes each (H3K27ac, H3K4me1) or a single lane (all others). WGS: used as matching input control for the 20 ChIPseq samples. Data type and technology: RNA-seq: PE 100bp sequenced on HiSeq2000. WGBS: PE 100bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000. WGS: PE 150bp sequenced on HiSeq X.

  Dataset EGAD00001005492

• Profiling molecular heterogeneity in human primary microglia

  In the brain the cells that control inflammation are called a type of white blood cell called microglia. Microglia are located throughout the brain and spinal cord and account for 10–15% of all cells found within the brain. As the resident white blood cells, they are the main active immune defence in the central nervous system (CNS). Microglia are part of an important class of cells known as macrophages that have two main states: M1 and M2. M1 cells are pro- inflammatory, leading to more inflammation, while M2 are anti-inflammatory, and drive wound healing. In this study, we will collect primary microglia from surgical biospies of 100 individuals. 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/

  Dataset EGAD00001005736

• Spatial transcriptome sequence data from cross section of cancer containing prostates

  Spatial transcriptome sequence data from two tumour containing prostates. Entire cross section of organ divided into cubes to fit spatial transcriptomics arrays. The dataset contains paired-end sequences from 21 sections of 1k array sections and 9 sections of 10x Visium sections for patient 1 as well as 28 sections of 10x Visium sections for patient 2.

  Dataset EGAD00001008644

• 10x Genomics Single Cell Gene Expression for SA1096A

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

  Dataset EGAD00001009139

• Mucosal 16S sequencing data

  16S-V4 rRNA gene sequence data for intestinal biopsies from NCT02749630 trial participants. Biopsies from patients were collected at screening, day 30, and day 85 and prepared for 16SV4 rRNA gene sequencing.

  Dataset EGAD00001008843

• RNA-Seq dataset for Genomic rearrangements in Pediatric Cancer

  RNA-Seq data for systematic gene fusion detection in Pediatric Cancer

  Dataset EGAD00001008152

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• COVID-19 Severity First Wave of Infection for Severe Patients in Madrid

  We recruited 98 hospitalised patients displaying severe COVID-19 symptoms from the first wave of infection. A stringent exclusion criteria based on non-genetic factors such as age, blood oxygen, radiologic findings and other typical COVID-19 signs was performed. Gingival or peripheral blood samples were taken for 98 individuals and whole exome sequencing performed using ExomeCapture-Seq capture KAPA HyperExome on Illumina machines.

  Dataset EGAD00001008464

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• Single Cell Genome Sequence for DLP+ library A95629B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051D passage 1 on DLP+ library A95629B

  Dataset EGAD00001009320

• Single Cell Genome Sequence for DLP+ library A95632A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA1-/- Tp53-/- cell line 184-hTERT-22 L9 83.86 on DLP+ library A95632A

  Dataset EGAD00001009321

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Single Cell Genome Sequence for DLP+ library A95635A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 116.126 on DLP+ library A95635A

  Dataset EGAD00001009324

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• Single Cell Genome Sequence for DLP+ library A95652A

  Single Cell Genome Sequence for immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 on DLP+ library A95652A

  Dataset EGAD00001009326

• Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis

  Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis. A total of 10 non-PCD patients (ALI day 14), 9 non-PCD patients (ALI day 21), 8 non-PCD patients (ALI day 28), 4 PCD patients (ALI day 14, day 21 and day 28), and 23 PCD patients (ALI day 21). Non-PCD patients and the 4 PCD patients on the three ALI days were sequenced at a depth of 100M reads, the remaining 23 PCD patients were sequenced at a depth of 70M. Overall sequencing design was rRNA depletion and 150bp paired-end.

  Dataset EGAD00001009498

• 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