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• BLUEPRINT release August 2016, ChIP-Seq for CD38-negative naive B cell, on genome GRCh38

  ChIP-Seq data for 9 CD38-negative naive B cell sample(s). 48 run(s), 44 experiment(s), 44 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002524

• BLUEPRINT release August 2016, RNA-Seq for immature conventional dendritic cell - GM-CSF_IL4_T=6_days, on genome GRCh38

  RNA-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 3 run(s), 3 experiment(s), 3 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 EGAD00001002526

• The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk RNA-seq)

  RNA was isolated from purified human CD8 cells that were incubated with anti-HER2/CD3 TDB in the presence of SK-BR-3 cells. Sequencing libraries were generated and submitted for transcriptome profiling by high-throughput sequencing. Experiments were performed in triplicates for anti-HER2/CD3 TDB treatment and control. This Dataset is associated with the following ArrayExpress Experiment: E-MTAB-8211 - The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk)

  Dataset EGAD00001005187

• The identification of genetic vulnerabilities in head and neck cancers for the development of novel treatments. (2019-06-10)

  Exome Sequencing in a set of Asian Head and Neck cancer cell lines, to identify mutations that can be used to genomically classify the cell lines. . This dataset contains all the data available for this study on 2019-06-10.

  Dataset EGAD00001005082

• Keratinocyte CRISPR screens (2019-08-14)

  Immortalised HaCaT keratinocytes were transduced with Cas9 and the CRISPR-KO v1.1 genome-wide gRNA library. The gRNA library was prepared from genomic DNA isolated 14 days post library transduction. gRNA representation will be compared to the original CRISPR-KO v1.1 library to reveal genes essential for HaCaT survival and growth. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005252

• Spatial RNA-sequencing of metastatic melanoma

  We performed RNA sequencing of 48 different regions sub-sampled from a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. RNAseq was performed on samples with a minimum RNA integrity number (RIN) of 5.5 except for two cases (6A10 and 8A3) with RINs greater than 3. A minimum of 700ng of RNA were required for all samples undergoing RNAseq. Paired-end transcriptome reads were aligned using TopHat2, to the UCSC hg19 reference genome.

  Dataset EGAD00001005820

• RNA sequencing of human intra- and extracranial endothelial cells

  This data set contains the raw .fastq files from one RNA-sequencing experiment. Endothelial cells of the basilar artery and endothelial cells of the carotid artery were post-mortem derived with laser microdissection and sequenced. For this analysis both the basilar- and the carotid artery endothelial cells of eleven individuals were sequenced. For more details please see: DMA Hermkens et al. "Profiling the Unique Protective Properties of Intracranial Arterial Endothelial Cells" Acta Neuropathol Commun. 2019 Oct 14; PMID: 31610812.

  Dataset EGAD00001006203

• Bottleneck Sequencing Of Human Tissue (Wgs) (2020-10-20)

  Bottleneck sequencing of human tissue including neurons, cord blood, sperm. 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/ . This dataset contains all the data available for this study on 2020-10-20.

  Dataset EGAD00001006459

• CRUK Accelerator: Non-small cell lung cancer whole exome and RNA sequencing

  Whole exome and RNASeq raw sequencing data for a cohort 24 patients with non-small cell lung cancer, 15 adenocarcinoma (8 female, 7 male) and 9 squamous cell carcinoma(5 female, 4 male). Median age at diagnosis was 69. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001007934

• Sequencing data for rare tumors and sarcomas

  This dataset contains DNA and RNA sequencing information for AML, Gliomas, brain tumors (medulloblastoma and ependymoma), DIPG, rhabdoid tumors and soft tissue sarcomas. In total 39 samples are present (14 matched normal, 25 tumor samples). Not all samples have matched normals and not all samples have RNA sequencing data..

  Dataset EGAD00001008974

• WES of breast and larynx cancer cases

  The dataset is based on 37 FFPE samples obtained from 12 patients diagnosed with breast or larynx cancer, For each patient 3 sample types were obtained P - primary tumor, L - malignant lymph node and C - benign lymph node (control). For patient G46 two malignant lymph nodes were used. DNA isolated from all samples was subject to exome selection using Agilent SureSelect Human All Exon V7. The obtained material was sequenced using NovaSeq 6000 platform with 2x150 reads. The sequencing was conducted by Novogene company.

  Dataset EGAD00001009081

• fibroblast RNAseq from a GINS3 patient and two parents

  RNA-seq was performed from 3 separate GINS3 patient fibroblast cultures and 1 replicate of fibroblasts derived from each of the two parents. RNA-seq libraries were generated with NEBNext Ultra II Directional RNA library prep for Illumina with NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and sequenced on Illumina NextSeq500 with paired-end 150 bp read length. SIRV Set 3 (Lexogen) spike-ins were added. Two fastq files are provided for each RNAseq sample.

  Dataset EGAD00001008571

• 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