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• Low-pass nanopore whole genome sequencing of brain tumors

  Dataset EGAD00001003382

• Exome_sequencing_of_short_SGA_children_with_IGF_I_and_insulin_resistance

  Exome sequencing of short SGA children with IGF-I and insulin resistance. Collaboration with Professor David Dunger, University of Cambridge. Funded by NIHR.

  Study EGAS00001001086

• Multi-omics datasets (WES, RNA-seq) of mesothelioma MIST4 study, a phase II PD-L1/VEGF blockage clinical trial

  This study comprises 26 mesothelioma patients with whole exome and RNA sequencing, designed to examine the efficacy and correlates of response to dual inhibition of programmed death-ligand 1 and vascular endothelial growth factor inhibition.

  Study EGAS50000001818

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas

  This dataset contains BAM files for RNA-sequencing of stage I lung adenocarcinomas from Asian patients. In total, there are 107 patients and 107 tumor samples.

  Dataset EGAD00001006187

• CRLF2_sequencing_project_Exomes

  I hope to gain insight into novel genetic aberrations present in these patients that will highlight important pathways that are involved in this subtype of leukaemia. It would be interesting to see if the mutations and pathways that are activated are consistent between the patients, or differences are observed dependent upon whether the patient has the translocation or the PAR1 deletion. Of note is the high association with either numerical gains of chromosome X or numerical/structural abnormalities of chromosome 21 (Down syndrome, iAMP21) in patients with CRLF2 deregulation. I hope to find abnormalities linking chromosomes X and 21 to CRLF2 deregulation in BCP‐ALL. By including the three patients that are normal for CRLF2, but have consistent genetic abnormalities found in the experimental cohort, I expect to find genetic differences between these two groups that will help us to identify novel molecular targets specific to CRLF2 deregulation.

  Study EGAS00001000081

• Influence of the Microbiome on Epigenetic Mechanisms in IBD

  Live CD4 T cells were sorted from inflamed and non-inflamed tissue samples of IBD patients or from healthy and IBD blood samples. ATAC-Seq libraries were generated from live CD4 T cells sorted from i) inflamed and non-inflamed tissue samples, ii) healthy and IBD blood samples, or from iii) CD4 T cell subsets polarised from healthy blood samples. After isolating crude nuclei, live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry. On the other hand, single cell RNA-Seq libraries were generated exclusively from inflamed and non-inflamed tissue samples of Crohn’s disease patients. Briefly, live CD4 T cells were captured and encapsulated before cDNA amplification using the 10X Genomics Chromium Platform. Samples were prepared as outlined by 10x genomics Single Cell 3’ Reagent Kits v2 user guide. Samples were sequenced on a HiSeq 2500 with the following run parameters: Read 1 – 26 cycles, read 2 – 98 cycles, index 1 – 8 cycles.

  Dataset EGAD00001011066

• Metastatic Prostate Follow Up 2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Dataset EGAD00001000989

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

  This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

  Dataset EGAD00001004823

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: kidney (2019-03-26)

  This dataset contains all the data available for this study on 2019-03-26.

  Dataset EGAD00001004867

• WES of melanoma tumors treated with combined immune checkpoint blockade

  This study of pre-treatment melanoma tumor samples from patients subsequently treated with combined anti-CTLA-4 and anti-PD-1 checkpoint blockade sought to identify genomic biomarkers of response to therapy. A total of 26 tumor and matched normal samples underwent whole exome sequencing.

  Study EGAS00001003857