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• TENX062

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX062 1 samples; filetype=fastq

  Dataset EGAD00001006477

• SCRNA10X_SA_CHIP0063_000

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0063_000 1 samples; filetype=fastq

  Dataset EGAD00001006478

• TENX064

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX064 1 samples; filetype=fastq

  Dataset EGAD00001006479

• TENX065

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX065 1 samples; filetype=fastq

  Dataset EGAD00001006480

• TENX066

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX066 1 samples; filetype=fastq

  Dataset EGAD00001006481

• TENX068

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX068 1 samples; filetype=fastq

  Dataset EGAD00001006482

• SCRNA10X_SA_CHIP0152_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0152_002 1 samples; filetype=fastq

  Dataset EGAD00001006472

• SCRNA10X_SA_CHIP0163_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0163_001 1 samples; filetype=fastq

  Dataset EGAD00001006473

• SCRNA10X_SA_CHIP0163_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0163_002 1 samples; filetype=fastq

  Dataset EGAD00001006474

• SCRNA10X_SA_CHIP0149_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0149_002 1 samples; filetype=fastq

  Dataset EGAD00001006468

• SCRNA10X_SA_CHIP0150_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0150_001 1 samples; filetype=fastq

  Dataset EGAD00001006469

• SCRNA10X_SA_CHIP0150_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0150_002 1 samples; filetype=fastq

  Dataset EGAD00001006470

• SCRNA10X_SA_CHIP0152_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0152_001 1 samples; filetype=fastq

  Dataset EGAD00001006471

• ChIP-seq of primary AML patients with t(3;3)/inv(3)

  ChIP-seq was conducted in blasts from patients with t(3;3) AML to assess differences of the GATA2 super-enhancer between the translocated allele and the non-translocated allele. The dataset includes 2x H3K27ac ChIP-seq and 1x MYB ChIP-seq. ChIP samples were processed according to the Illumina TruSeq ChIP Sample Preparation Protocol (Illumina) or Diagenode Library V3 preparation protocol (Diagenode) and either sequenced single-end (1x 50 bp) on the HiSeq 2500 platform (Illumina) or paired-end (2x100 bp) on the Novaseq 6000 platform (Illumina). Briefly, reads were aligned to the human reference genome build hg19 with bowtie for single-end runs and bowtie2 for paired-end runs.

  Dataset EGAD00001006821

• A108837A

  Whole genome sequencing for single cells for library A108837A 1435 cells; filetype=bam

  Dataset EGAD00001007090

• A108846A

  Whole genome sequencing for single cells for library A108846A 1670 cells; filetype=bam

  Dataset EGAD00001007091

• RNAseq files for Klco RPAML

  RNAseq files for Klco RPAML study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008407

• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the exome seq data.

  Study EGAS00001003306

• Analysis of Loose Ends in Cancer Genome Structure

  Short-read sequencing (SRS) forms the basis of our understanding of cancer genome evolution, yet it is widely thought to be inadequate for detecting structural variants (SVs). To understand the nature of cancer SVs missed by SRS, we introduce the concept of "loose ends" - sites of missing rearrangements revealed by balancing copy number (CN) across the genomic intervals and adjacencies of a genome graph.

  Study EGAS00001007324

• Diverse modes of genomic alterations in hepatocellular carcinoma

  Hepatocellular carcinoma is the most prevalent type of liver cancer. We intended to study the genomic landscape of this disease. We conducted whole-genome, exome and transcriptome sequencing for 42 patients. We show diverse modes in which the HCC genome is affected in these patients, including well-known and novel mutations, structural variations, and Hepatitis B-virus integration into the genome.

  Study EGAS00001000824

• Transcriptomes_of_human_lymphocytes

  In this study we will compare the single cell transcriptomes of immune cells from asthmatics responding to steroids, those refractory to steroids, and a control population.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/

  Study EGAS00001001755

• CMML Collection of WES, WGS, RNA-Seq and ERRBS data

  We first performed a comprehensive analysis of the genome of 66 chronic myelomonocytic leukemia cases using whole exome (N=49) or whole genome (N=17) sequencing for paired leukemic-control DNA. Then, we realized serial analysis of whole exome sequence in 17 cases, completed with serial RNA sequencing and DNA methylation analysis in 9 cases, including patients treated or not with hypomethylating agents.

  Study EGAS00001001264

• De_novo_mutations_in_cell_free_foetal_DNA__cffDNA_

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women.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/

  Study EGAS00001000322

• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer RNA-Seq

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the patient matched RNA-Sequencing data.

  Study EGAS00001003307

• Illumina HiSeqX whole genome sequence data on 58 samples including 54 with known HTT triplet repeat expansions (2 premutation and 52 full expansions)

  Whole genome sequence (WGS) data was generated on 58 samples with validated repeat lengths for the CAG repeat associated with Huntington disease, These samples were sequenced using 2x150bp reads on an Illumina HiSeqX sequencer and the repeat expansions were called using ExpansionHunter to demonstrate the ability to call large repeats from high throughput, WGS data.

  Study EGAS00001002593

• Whole transcriptome and exome sequencing of childhood ALL

  Gene fusion is a major class of genomic abnormalities in childhood acute lymphoblastic leukemia (ALL) and sentinel chromosomal rearrangements involving EP300 and CREBBP may cause global epigenetic deregulation during leukemogenesis with potentials for therapeutic targeting. This dataset includes whole transcriptome sequencing of 231 children with acute lymphoblastic leukemia from a Singapore-Malaysia frontline clinical treatment protocol.

  Study EGAS00001001858

• Whole-genome bisulfite sequencing analysis of low-grade astrocytomas in the ICGC PedBrain Tumor Project

  Pilocytic Astrocytoma (PA) is the most common pediatric brain tumor. While genome and transcriptome landscapes are well-studied, data of the complete methylome, tumor cell composition and immune infiltration are scarce. We generated whole genome bisulfite sequence data (WGBS) of nine PAs to find evidence for a link of focal methylation differences and differential gene expression to immune infiltration.

  Study EGAS00001004019

• Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  HCHWA-D is an early onset hereditary form of Cerebral Amyloid Angiopathy (CAA) caused by a point mutation resulting in an amino acid change (NP_000475.1:p.Glu693Gln) in the Amyloid Precursor Protein (APP). Post-mortem brain tissue (9 patients and 9 age-related controls; frontal and occipital cortex) was used for next generation sequencing of RNA (RNA-Seq with ribosomal RNA depletion).

  Study EGAS00001002730

• Whole-exome sequencing of Fanconi anemia-like inherited bone marrow failure syndrome

  We identified three fibroblast cultures derived from aplastic anemia patients in the Japanese Cancer Research Resources Bank (JCRB) Cell Bank that showed high levels of sister chromatid exchanges (SCEs) in PHA-stimulated lymphoblasts. To elucidate the genetic basis of the high SCE, we carried out whole exome sequencing of these samples. Subsequently, germline variants were analysed for these patients.

  Study EGAS00001003809

• Expression-Based Subtypes Define Pathologic Response to Neoadjuvant Immune-Checkpoint Inhibitors in Muscle-Invasive Bladder Cancer

  Checkpoint immunotherapy (CPI) has increased survival for some patients with advanced stage bladder cancer (BCa). However, most patients do not respond. Here, we characterized the tumor and immune microenvironment in pre- and post-treatment tumors from the PURE01 neoadjuvant pembrolizumab immunotherapy trial, using a consolidative approach that combined transcriptional and genetic profiling with digital spatial profiling.

  Study EGAS00001005549

• Cylindromas_sun_protected_and_exposed

  The project aims to look at mutational signatures in a rare inherited skin tumour syndrome called CYLD cutaneous syndrome. These patients develop multiple skin tumours that are seen at sun exposed and sun protected sites. We plan to carry out WGS on carefully curated tumours from such patients. We then plan to analyse this data for mutational signatures, comparing this between sun exposed and sun protected sites.

  Study EGAS00001002521

• Misoprostol-induced high fever GWAS study

  Genome-wide association (GWAS) meta-analysis study of misoprostol-induced fever was conducted on two South American cohorts (Argentina and Ecuador). DNA was collected from blood of women who were screened for postpartum haemorrhage (PPH) and administered misoprostol were included in the study. Genotypes were acquired from the Global Screening Array (Illumina). Meta-analysis of these cohorts was completed using METAL software.

  Study EGAS00001005455

• PAH sequencing study

  The Cohort study of idiopathic and heritable PAH is an observational, prospective and longitudinal study of patients with idiopathic and heritable PAH. Follow-up information is collected as a part of routine clinical care every six months. The study allows recruitment of both incident and prevalent cases. Patients consented to the study agreed to have blood taken for next-generation sequencing and other omics studies.

  Study EGAS00001005532

• NIHR BioResource Common Disease Patients 2016

  NIHR BioResource Common Disease Patients 2016. The dataset includes 13489 samples from blood donors, they were not screened for any particular disease, and therefore they are representative of the general population. Genomic data includes 845487 snps collected using the UK BioBank V1 Affymetrix array. Phenotypic data includes gender, age, ethnicity and disease. According to our internal quality check there are 81 duplicates in this dataset.

  Study EGAS00001004870

• Gremlin 1 + fibroblastic niche maintains dendritic cell homeostasis in lymphoid tissues

  Although cross-species transcriptional analysis has been generated for DCs37, transcriptomic conservation between mouse and human FRCs at single-cell resolution has been unclear. To test whether GREM1+ FRCs might also play a role in DC homeostasis in humans, we performed scRNA-seq of CD45–PDPN+ stromal cells, as well as CD45+CD11c+ immune cells from healthy human LNs of three donors.

  Study EGAS00001006211

• RNA-seq following miR-130a overexpression (OE) in human CD34+cord blood cells

  We performed RNA-seq on CD34+ human cord blood (CB) cells transduced with Control or miR-130a OE lentiviruses to identify differentially expressed genes. Sorted CD34+ cells from 3 independent cord blood pools were transduced with lentiviruses containing mOrange (mO) reporter gene. mO+ cells were sorted 3 days post-transduction and RNA was harvested for library preparation and sequencing.

  Study EGAS00001005868

• Genetic regulation of gene expression in human brain cell types

  We leveraged single nuclei RNA-seq from 192 human brain samples to map cis-eQTLs in 8 brain cell types. We found extensive cell-type specific genetic effect on gene expression and integrated our results with GWAS to identify putative novel risk genes for brain disorders and the cell types in which the disease mechanisms are likely active.

  Study EGAS00001006345

• Single Cell Genome Sequence for DLP+ library A96210B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1047B on DLP+ library A96210B

  Dataset EGAD00001009475

• Single Cell Genome Sequence for DLP+ library A96212B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96212B

  Dataset EGAD00001009476

• Normal sample for patient SA495

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA495

  Dataset EGAD00001009372

• Normal sample for patient SA425

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA425

  Dataset EGAD00001009371

• Normal sample for patient SA423

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA423

  Dataset EGAD00001009370

• Normal sample for patient SA300

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA300

  Dataset EGAD00001009369

• Normal sample for patient SA291

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA291

  Dataset EGAD00001009368

• Normal sample for patient SA289

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA289

  Dataset EGAD00001009367

• Normal sample for patient SA286

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA286

  Dataset EGAD00001009366

• Normal sample for patient SA280

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA280

  Dataset EGAD00001009365

• Normal sample for patient SA239

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA239

  Dataset EGAD00001009364

• Normal sample for patient SA238

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA238

  Dataset EGAD00001009363

• Normal sample for patient SA221

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA221

  Dataset EGAD00001009362