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• Whole exome sequencing data for patients with Bosma arhinia microphthalmia syndrome (BAMS)

  Whole exome sequencing data for patients with Bosma arhinia microphthalmia syndrome (BAMS). The dataset includes 21 samples from 7 families with BAMS; see Gordon et al, Nature Genetics, 2017.

  Dataset EGAD00001003130

• Transcriptomic profiles of neuroblastoma PDXs and primary tumors

  This dataset contains bam files for RNA-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft) and 3 pairs of neuroblastoma tumors at diagnosis and at relapse.

  Dataset EGAD00001003393

• Whole Genome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Whole Genome Sequencing for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003435

• Exome and Transcriptome for pan-cancer gene-drug analysis

  Total of 584 tumor specimens and/or patient-derived cells across 14 cancer types were subjected for whole-exome/targeted-exome and/or whole-transcriptome sequencing.

  Dataset EGAD00001003441

• BLUEPRINT release January 2015, DNase-Hypersensitivity for monocyte

  DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 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_dnaseseq_analysis_20140811

  Dataset EGAD00001001185

• Whole Genome Sequencing (WGS) for St. Jude High Grade Glioma (HGG) study

  Whole Genome Sequencing (WGS) for St. Jude High Grade Glioma (HGG) study

  Dataset EGAD00001000806

• Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Dataset EGAD00001000807

• BLUEPRINT September 2016, ATAC-seq for bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002710

• Whole exome sequencing of human and mouse sarcoma samples for personalized therapy

  Whole exome sequencing of human and mouse sarcoma samples for creation of personalized therapy options. Tissues were sequenced directly; no interventions or alterations were made to the tissue samples

  Dataset EGAD00001004885

• Exome sequencing of Non-syndromic Congenital Heart Defects (2019-04-24)

  Exome sequencing of ~1,800 patients with non-syndromic Congenical Heart Defects (CHD) to identify genes enriched for damaging rare variants that increase risk of CHD . This dataset contains all the data available for this study on 2019-04-24.

  Dataset EGAD00001004975

• RNAseq files for Mullighan_GL_reALL RNASEQ2

  RNAseq files for Mullighan_GL_reALL RNASEQ2 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005510

• RNASeq files for Mullighan_GL_reALL RNASEQ1

  RNASeq files for Mullighan_GL_reALL RNASEQ1 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005511

• Exome and Targeted sequencing of GZL

  Tumor and matching normal exomes for 28 GZL cases (n=56) and targeted capture sequencing for 42 GZL cases with 3 matching normals and 2 pooled normals (n=47)

  Dataset EGAD00001006328

• Data for the genome‐wide association study of cutaneous leishmaniasis in Brazil

  DNAs were genotyped on Illumina Infinium HumanCoreExome Beadchips (Illumina Inc., San Diego, CA, USA) with probes for 551,004 single nucleotide variants (SNVs): 282,373 informative across ancestries; 268,631 exome-focused. Human genome build 37 (hg19) was used.

  Dataset EGAD00001006681

• A95646B

  Whole genome sequencing for single cells for library A95646B 507 cells; filetype=bam

  Dataset EGAD00001007306

• RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  Dataset EGAD00001009799

• IL-17 Signaling in Human iPSC-derived Midbrain Neurons in Parkinson's Disease

  To determine IL-17-induced global transcriptome changes in midbrain neurons derived from induced pluripotent stem cells (iPSC) from three sporadic Parkinson's disease (PD) patients and three age- and sex-machted controls, deep RNA sequencing (RNA-Seq) of IL-17-treated and untreated PD and control iPSC-dderived midbrain neurons was performed. Total RNA was isolated from untreated and IL-17-treated cells with the TruSeq RNA Sample Preparation Kit v2 (Illumina). RNA libraries were quantified using the KAPA SYBR FAST ABI Prism Library Quantification Kit (Kapa Biosystems) and cluster generation was performed on the cBot with the TruSeq SR Cluster Kit v3 (Illumina). The sequencing run was performed on a HiSeq 1000 instrument (Illumina) using the indexed, 50 cycles single read (SR) protocol and the TruSeq SBS v3 Kit (Illumina). Image analysis and base calling resulted in .bcl files that were then converted into .fastQ files by the CASAVA1.8.2 software. FastQ files were aligned to the human genome (hg19) using STAR.and annotated with gencode.v19. DESeq2 was used to determine differential expression. Criteria to determine significantly dysregulated genes were as follows: adjusted p-value below 0.05 and log2FC (fold change) of greater than one. Only genes with a mean expression value of greater than one RPKM (reads per kilobase per million mapped reads) throughout the dataset were considered. Control and PD samples were analyzed as two independent datasets. Upon IL-17 treatment only 17 genes were found to be dysregulated in controls but 125 genes were dysregulated in iPSC-derived midbrain neurons from PD patients. The 125 IL-17-dependent genes in PD iPSC-derived neurons separated the treated from untreated PD samples using an unsupervised, hierarchical clustering applying an Euclidean distance metric. More detailed study information can be found in Sommer A, Maxreiter F, Krach F, Fadler T, Grosch J, Maroni M, Graef D, Eberhardt E, Riemenschneider MJ, Yeo GW, Kohl Z, Xiang W, Gage FH, Winkler J, Prots I, Winner B. Th17 Lymphocytes Induce Neuronal Cell Death in a Human iPSC-Based Model of Parkinson's Disease. Cell Stem Cell. 2018 Jul 5;23(1):123-131.e6. doi: 10.1016/j.stem.2018.06.015. PMID: 29979986

  Study phs001686

• Comparison of fresh and slow-frozen cancer samples for different applications

  Surplus tissues from multiple solid human cancers directly slow-frozen after resection can subsequently be used for different types of methods including the establishment of 2D, 3D, and ex vivo cultures as well as single cell RNA sequencing (scRNAseq) with similar results when compared to freshly analyzed material.

  Study EGAS00001005891

• MicroRNA profiling by next-generation sequencing for colorectal cancer screening

  The study was conducted as the marker discovery phase to identify potential microRNA (miRNA) candidates for colorectal cancer (CRC) screening. Genome-wide profiling with next-generation sequencing (NGS) was performed using plasma samples from 20 newly diagnosed CRC cases and 20 controls free of colorectal neoplasms matched by age and sex.

  Study EGAS00001005030

• BLUEPRINT September 2016, ChIP-Seq for class switched memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002951

• BLUEPRINT September 2016, ChIPmentation for effector memory CD8-positive, alpha-beta T cell, terminally differentiated from venous blood, on Genome GRCh38

  ChIPmentation data for 1 sample(s) for effector memory CD8-positive, alpha-beta T cell, terminally differentiated from venous blood, on Genome GRCh38. 5 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002943

• scRNA-seq using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data for 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert). Dissociated cells from each tumor sample have been sorted to isolate live cells from the 3 compartments: tumor, immune and stromal. Each of the compartments has been analyzed separately by scRNAseq, excluding some desert tumors for which cells from the stromal and immune compartments have been pooled. Sequencing was performed using 10X Genomics Chromium Single Cell platform (v2 Chemistry).

  Dataset EGAD00001006974

• Sequencing data for oesophageal and related samples - Izadi et al (WGS, RNA)

  Data supporting: "Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma" Izadi et al. WGS for tumour and normal samples. RNAseq for tumour samples.

  Dataset EGAD00001007493

• cfMeDIP data for 72 VPC samples for validation

  We analyzed the cell free DNA methylomes using 72 plasma samples from patients with mCRPC prostate cancer in the VPC project for validation. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology. Files from multiple lanes exists per sample.

  Dataset EGAD00001008737

• Ontario Familial Colon Cancer Registry Single Nucleotide Polymorphisms and CpG Methylation (OFCCR SNP-CpG)

  We profiled the methylation landscape of ~2100 DNA samples (~1100 cases of colorectal cancer and ~1000 controls) from the Ontario Familial Colon Cancer Registry (OFCCR) using the HumanMethylation450 array from Illumina. DNA was extracted from lymphocyte pellets, except for 99 samples for which DNA was extracted from lymphoblastoid cell lines. Samples were genotyped on the Affymetrix Human Mapping 100k and 500k arrays. The aim the study was to evaluate the interplay between genetic variation and methylation, including long-range epigenetic regulation.

  Study phs000779