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• HipSci-RNAseq-healthy volunteers

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sup-study we perform RNAseq on iPS cells generated from skin biopsies from healthy volunteers.

  Study EGAS00001000593

• Breast_Cancer_Sequential_Sampling_Targeted_Capture

  This study aims to target capture sequence regions of interest from DNA derived from breast cancer patients who received neo-adjuvant chemotherapy. All patients had multiple biopsies performed before chemotherapy. Patients who had residual disease after the course of treatment underwent a further biopsy. We aim to characterise the mutations involved.

  Study EGAS00001000596

• Targeted_Sequencing_of_Human_Myeloid_Malignancies

  This study involves targeted sequencing of samples from myeloid malignancies at different timepoints to assess clonal evolution of malignancya.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 EGAS00001001289

• Mutation_burden_in_sun_exposed_eyelid__MSSE_

  Eyelid skin from blepharoplasty surgery will be collected from patients of different ethnic origin (Chinese, Malay, Indian and Caucasion) exposed to tropical sunshine. 2mm2 biopsies will be collected and DNA sequenced using a specific bait capture set and at high depth. The aim is to try and see if different mutations expand in different ethnic populations.

  Study EGAS00001002512

• Bleeding

  As part of the Bloodomics collaboration we have several categories of pedigrees with diseases/syndromes relevant to cardiovascular diseases (CVD). One such group, is from individuals who exhibit severe bleeding with an unknown cause. Exome sequencing has been performed as part of a discovery program to ascertain potential causative variants of the clinical phenotype.

  Study EGAS00001000106

• Whole-genome and transcriptome sequencing of tumor-stage mycosis fungoides

  Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma (CTCL), a group of malignancies derived from skin-homing malignant T cells. We subjected tumor biopsies from MF patients to whole-genome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001002860

• Paroxysmal_Neurological_Disorders_2

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Study EGAS00001000190

• Paroxysmal_neurological_Disorders

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Study EGAS00001000386

• Validation_of_AML_Mutational_Screening

  We recently worked-up a pulldown protocol for studying 21 genes recurrently mutated in AML (Study1770). Our manuscript is currently under revision and to address the reviewers' comments we need to validate some mutations by re-sequencing. In this add-on study we will be using PCR followed by MiSeq for this purpose.

  Study EGAS00001000430

• X10_sequencing_of_Oesophageal_Adenocarcinoma_Organoids

  X10 Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical resection of the tumour. All model derivations took place with the CGaP facility in Sanger. This PacBio data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003264