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• Transcriptome_Sequencing_of_Cancer_Cell_Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Study EGAS00001000261

• Multiple Myeloma Total Therapy trial patient sequencing

  The study of multiple myeloma (MM) genomics has identified many abnormalities that are associated with poor progression free survival (PFS) and overall survival (OS). Copy number abnormalities have been extensively studied in many datasets with long follow-up, however, the prognostic impact of mutations have not been extensively studied and available datasets have generally had a relatively short follow-up. These analyses have identified a range of mutations that are associated with prognosis, making it important to extend these observations in larger studies with robust diagnostic technologies. Samples from newly diagnosed MM patients enrolled in Total Therapy trials (n=225) were sequenced on a targeted panel consisting of 140 genes and additional regions of interest for copy number, as well as tiling of the Ig and MYC loci for detection of translocations. Samples were sequenced to a median depth of 452x using 2x75 bp paired end reads. Reads were aligned to hg19 and mutations called using Strelka and filtered with fpfilter. Translocations were called by Manta, and copy number determined by read depth ratio and loss of heterozygosity comparison with a patient matched non-tumor sample. DNA was obtained from either CD138+ cells from the bone marrow of multiple myeloma patients (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using the HyperPlus kit (KAPA Biosystems). After PCR amplification the libraries were hybridized with probes against either a targeted panel consisting of 140 genes and chromosomal regions (Nimblegen) using SeqCap reagents (Nimblegen). Hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads There are 450 (225 tumor and 225 germline) samples in this study. 263 are available as part of this dataset. The remaining 187 are available with dataset accession id EGAD00001004117.

  Study EGAS00001003223

• scRNA-seq of HSPC treated with gemcitabine and carboplatin

  4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. The raw FASTQ-files are available as read 1 and read 2 files from 4 lanes for each sample giving a total of 16 FASTQ-files. The FASTQ-files were also processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression (dge) for each cell of each sample. This has resulted in one dge text file and one dge summary text file per sample. These 8 text-files with dge data are found in the zip-compressed analysis data-file.

  Dataset EGAD00001006080

• Dataset for desmoplastic small round cell tumor - WES

  This dataset contains 45 WES sequencing samples of patients with desmoplastic small round cell tumor. Sequencing was performed on Illumina HiSeq 2500, Illumina HiSeq 4000 and NovaSeq 6000 using Agilent SureSelect Human All Exon V5 Kit. The sequencing was always paired.

  Dataset EGAD50000000910

• Primary_DIPG_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

  Dataset EGAD00001011080

• Low-coverage whole-genome sequencing (lcWGS) data of Genome in a Bottle (GIAB) reference samples

  This dataset contains low-coverage whole-genome sequencing (lcWGS) data generated from three GIAB reference samples (HG001–HG003) for method benchmarking and concordance analysis in FFPE-GWAS workflows. The data were generated using Illumina NovaSeq with paired-end 150bp reads and downsampled to 2x coverage.

  Dataset EGAD00001015533

• UK10K COHORT TWINSUK

  The UK10K project proposes a series of complementary genetic approaches to find new low-frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome-wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein-coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will directly analyse quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The TwinsUK samples will be part of the cohort study and will undergo whole genome sequencing. For further information with regard to this cohort please contact Brent Richards (brent.richards@kcl.ac.uk) or Nicole Soranzo (ns6@sanger.ac.uk).

  Study EGAS00001000108

• RNAseq profile of monomorphic epitheliotropic intestinal T-cell lymphoma and enteropathy associated T-cell lymphoma

  Background : Enteropathy-associated T-cell lymphoma (EATL) and monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL) are aggressive malignancies with limited treatment options and poor prognosis. Our research on MEITL has uncovered its genetic portrait including hallmark SEDT2 mutations, expanded its pathological spectrum, and identified molecular biomarkers influencing patients’ outcome. In this study, we aimed to establish and clarify the similar and diverging features of EATL. Methods : A large combined cohort of patients with EATL (n=30) and MEITL (n=52) was assembled and tumor samples were used for whole-exome and RNA sequencing profiling.

  Study EGAS50000001125

• Whole Exome Sequencing of monomorphic epitheliotropic intestinal T-cell lymphoma and enteropathy associated T-cell lymphoma

  Background : Enteropathy-associated T-cell lymphoma (EATL) and monomorphic epitheliotropic intestinal T-cell lymphoma (MEITL) are aggressive malignancies with limited treatment options and poor prognosis. Our research on MEITL has uncovered its genetic portrait including hallmark SEDT2 mutations, expanded its pathological spectrum, and identified molecular biomarkers influencing patients’ outcome. In this study, we aimed to establish and clarify the similar and diverging features of EATL. Methods : A large combined cohort of patients with EATL (n=30) and MEITL (n=52) was assembled and tumor samples were used for whole-exome and RNA sequencing profiling.

  Study EGAS50000001126

• Understanding_hematopoietic_stem_cell_mobilization_and_engraftment_

  This study looks at patients undergoing gene therapy for genetic blood and immune disorders, in particular sickle cell disease. From each patient, single blood HSPC colonies are grown from patient blood mononuclear cells, bone marrow mononuclear cells, or CD34+ at multiple time points: pre gene transduction, post-transduction, and post-infusion (at several time points). Whole-genome sequencing will be performed on DNA from these colonies and somatically-acquired mutations will be called. Using these mutations, a phylogeny of these cells can be inferred and further inferences can be made about the gene therapy transduction and engraftment steps.

  Study EGAS00001004620