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• POETIC clinical Trial Ki67 Bookend Breast Cancer Targeted Exome and RNAseq Project

  Using RNAseq, we compare the 15% of poorest responders (PRs, n=177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant aromatase inhibitors to good responders (GRs, n=190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In the POETIC trial, 4,480 postmenopausal women with primary ER+ BC were randomised 2:1 to receive either treatment with a non-steroidal AI (letrozole or anastrozole) for 2 weeks before and 2 weeks after surgery or to no perisurgical treatment. Only AI-treated patients with HER2- tumors, paired baseline and surgery Ki67 available, and baseline Ki67 immunohistochemistry (IHC) >10% (to minimise imprecision in proportional Ki67 falls) were included for selection. Data is baseline RNAseq and targeted exome DNA sequencing analysis of POETIC Good/Poor Responders to aromatase inhibitors based on change in Ki67.

  Dataset EGAD00001010919

• SINGLE CELL ANALYSIS OF IN VITRO ERYTHROPOIESIS

  We are developing a protocol to differentiate mouse and human induced pluripotent stem (IPS) and embryonic stem (ES) cells towards the haematopoietic pathway to generate erythrocytes in vitro. This system has many applications such as the study of the role of specific genes and human polymorphisms in infectious diseases such as malaria, as well as haematological diseases such as myelodysplastic syndrome. The nature of the in vitro differentiation process means that a heterogeneous population of cells is generated. In order to understand the types of cells produced with our protocol, we have performed a single cell analysis, which has the power to reveal the different populations of cells and their characteristics. For this, a cDNA library has been made that needs to be sequenced to obtain the gene expression profiles of the different cells. With this information we will be able to assess the quality of the differentiation protocol and improve it in order to produce better cells for the downstream applications.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/

  Dataset EGAD00001000979

• Structural rearrangements generate cell-specific, gene-independent CRISPR-Cas9 loss of fitness effects.

  CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimental to cellular fitness in a gene independent manner. In contrast, amplifications caused by whole chromosomal duplications have little to no impact on fitness. This effect is cell line specific and dependent on the ploidy status. We devise a copy-number ratio metric that substantially improves the detection of gene-independent cell fitness effects in CRISPR-Cas9 screens. Furthermore, we develop a computational tool, called Crispy, to account for these effects on a single sample basis and provide corrected gene fitness effects. Our analysis demonstrates the importance of structural rearrangements in mediating the effect of CRISPR-Cas9-induced DNA damage, with implications for the use of CRISPR-Cas9 gene-editing in cancer cells.

  Dataset EGAD00001004124

• Autozygosity pilot - Born in Bradford (2014-11-20)

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing cohort samples from the Born In Bradford study will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consist of low coverage whole exome sequencing on these samples.Data Access is controlled by the Wellcome Trust Sanger Institute DAC and the Born In Bradford Executive Group. This dataset contains all the data available for this study on 2014-11-20.

  Dataset EGAD00001001079

• DAC for Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

  Dac EGAC00001001250

• cqmuGWAS1

  DNA for 1546 individuals from Chongqing was extract from peripheral blood and genotyped by Illumina Omni Zhonghua-8 version 1 gene chips.

  Dataset EGAD00010001527

• PMBCL IL4R DASL

  Expression data for 42 PMBCL patient samples (32 IL4R WT cases and 10 cases with mutations in IL4R)

  Dataset EGAD00010001542

• Copy number profiling of primary samples and cell lines of retinoblastoma

  Illumina SNP-arrays for matching retinoblastoma-blood pairs and retinoblastoma cell lines.

  Dataset EGAD00010000908

• Serum Proteomics of Aortic Diseases

  Comparative proteome-based analysis of different autologous bone entities used for alveolar onlay grafting

  Dataset EGAD00010002314

• SNParray_PGT_samples_scGBS

  PGT samples for haplotyping and copy-number profiling via SNP array

  Dataset EGAD00010002169

• SNParray_HapMap_samples_scGBS

  HapMap samples for haplotyping and copy-number profiling via SNP array

  Dataset EGAD00010002168

• scRaCH-seq data targeting BTK and SF3B1

  Data set for scRaCH-seq manuscript. We base call the fast5 using guppy.

  Dataset EGAD50000000235

• HMO-microbiome study dataset, 16S sequencing

  This dataset contains 16S sequencing of fecal and milk samples for HMO-microbiome Lifelines NEXT study

  Dataset EGAD50000000532

• Cancer Genomics, ICR, summary data

  DAC for summary level data from the Cancer Genomics group, Division of Genetics and Epidemiology at the Institute of Cancer Research, Sutton, UK.

  Dac EGAC50000000050

• Foundation Medicine Binary Calls

  Binary calls for all available samples in 4 Atezo trials.

  Dataset EGAD50000000709

• Picuris Pueblo Genomic Project (Modern Data)

  Data Access Committee for the present-day dataset of the project "Picuris Pueblo oral history and genomics reveal continuity in US Southwest".

  Dac EGAC50000000526

• DNABR

  Genome variation data for 2723 Brazilian individuals from the DNA do Brasil Project.

  Dataset EGAD50000001012

• DAC for DRS peripheral blood, University Medical Center Johannes Gutenberg University Mainz

  This DAC is in relation to the DRS samples of peripheral blood of healthy control

  Dac EGAC50000000667

• University Clinic Golnik DAC

  DAC of the University Clinic Golnik, that will decide regarding the requests for data submitted on behalf of research groups of the Clinic

  Dac EGAC50000000820

• WGS_TALL_t_14_16_translocation

  WGS data for patients with t(14;16) translocated T-ALL.

  Dataset EGAD50000001782

• NANOPORE_TALL_t_14_16_translocation

  Nanopore sequencing for patients with t(14;16) translocated T-ALL

  Dataset EGAD50000001785

• SF10432 Wildtype Primary GBM Female, 50

  Single Cell-RNA Seq of Wildtype Primary GBM for Female, Age 50.

  Dataset EGAD00001006019

• Fecal WMS HV metadata

  Metadata for fecal WMS data from NCT02749630 healthy volunteers.

  Dataset EGAD00001008819

• RNAseq data for EGAS00001004572

  Bulk RNA-seq data of tumours in EGAS00001004572.

  Dataset EGAD00001006876

• Long-term organoid culture of a small intestinal neuroendocrine tumor

  tissue, organoid and normal bam files for whole exome samples

  Dataset EGAD00001010162