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• DATA FILES FOR SJEPD

  DATA FILES FOR SJEPD

  Dataset EGAD00001000853

• CGMH data access committee for the CGMH-OCCC-WES data

  CGMH data access committee for the CGMH-OCCC-WES data

  Dac EGAC50000000028

• The data access committee for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  Dac EGAC50000000588

• DAC for pediatric AML genomic sequences

  DAC for dataset containing matched tumor-healthy genomic sequences from patients with pediatric AML

  Dac EGAC50000000666

• DAC for DLBCL dataset

  Data Access Committee for cfDNA sequencing dataset from 290 samples from patients with DLBCL and HGBL.

  Dac EGAC50000000257

• DAC for the access to IMMUcan data

  This DAC will assess the requests for the access to IMMUcan data

  Dac EGAC50000000829

• Metastatic_Prostate_Follow_Up_2

  Validation/deeper sequencing for metastatic prostate cancer samples

  Study EGAS00001000756

• Metastatic_Prostate_Follow_Up

  Validation/deeper sequencing for metastatic prostate cancer samples

  Study EGAS00001000730

• Nrf2 transcript alterations

  WGS and RNA-seq data for Nrf2 study

  Study EGAS00001001740

• Targeted Gene Panel for 171 PTCLs

  Targeted Gene Panel for 171 PTCLs

  Dataset EGAD00001003967

• DATA FILES FOR PCGP SJMEL WXS

  DATA FILES FOR PCGP SJMEL WXS

  Dataset EGAD00001001246

• DATA FILES FOR PCGP SJMEL RNASEQ

  DATA FILES FOR PCGP SJMEL RNASEQ

  Dataset EGAD00001001247

• WGS data for NRF2 study

  WGS data for cell lines and clinical samples

  Dataset EGAD00001002244

• PGRN/PAT: The genomic basis for susceptibility to drug-induced long QT syndrome (diLQTS)

  The goal of this study was to search for genetic variants that could be responsible for modifying the risk of drug-induced long QT syndrome (diLQTS). diLQTS is a relatively common adverse drug event and has been a leading cause for drug relabeling and withdrawal from the market. Our hypothesis, that variants in genes which regulate electrical properties in the heart modify the risk of diLQTS, was tested by sequencing approximately 225 patients of European descent using next-generation targeted captured or whole exome sequencing. Data from cases and controls (1:2) were analyzed to identify both rare and common genetic variation.

  Study phs000808

• Profiling RNA Translation in Pediatric Medulloblastoma

  This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

  Study phs003446

• WTCCC case-control study for Hypertension

  WTCCC genome-wide case-control association study for Hypertension (HT) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000009

• scRNA-seq and Amplicon data for MPN/HC samples

  This data set contains scRNA-seq data from MPN patients and healthy individuals. It is accompanied by amplicon data for the JAK2V617F mutation. For each individual an INFa treated and untreated sample is included.

  Dataset EGAD50000001321

• DAC for "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  This DAC will be created for sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas." The dataset includes Illumina-based exome sequencing of tumor specimens, paired blood specimens, bulk RNA-seq, and Visium FFPE.

  Dac EGAC50000000579

• Epigenomic dataset of Human Hepatocellular Carcinoma for EpiHK

  This dataset is generated for EpiHK. It contains Histone PTM ChIP-seq, WGBS, RNA-seq of Human Hepatocellular Carcinoma and tumor adjacent normal tissue sample.

  Study EGAS50000000039

• BLUEPRINT September 2016, ATAC-seq for osteoclast from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for osteoclast from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002907

• BLUEPRINT September 2016, ATAC-seq for naive B cell from tonsil, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for naive B cell from tonsil, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002903

• BLUEPRINT September 2016, ATAC-seq Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) Multiple Myeloma for plasma cell from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002920

• BLUEPRINT September 2016, ATAC-seq for plasma cell from tonsil, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for plasma cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002912

• First genome-wide association study in an Australian Aboriginal population provides insights into genetic risk factors for Body Mass Index and Type 2 Diabetes

  A body mass index (BMI) >22kg/m2 is a risk factor for type 2 diabetes (T2D) in Aboriginal Australians. To identify loci associated with BMI and T2D we undertook a genome-wide association study using 1,355,133 quality-controlled single nucleotide polymorphisms (SNPs) genotyped (Illumina 2.5M Duo Beadchip) in 402 individuals in extended pedigrees from a Western Australian Aboriginal community. Imputation using the thousand genomes (1000G) reference panel extended the analysis to 6,724,284 post quality-control autosomal SNPs. No associations achieved genome-wide significance, commonly accepted as P<5x10-8. Nevertheless, genes/pathways in common with other ethnicities were identified despite the arrival of Aboriginal people in Australia >45,000 years ago. The top hit (rs10868204 Pgenotyped=1.50x10-6; rs11140653 Pimputed_1000G=2.90x10-7) for BMI lies 5’ of NTRK2, the type 2 neurotrophic tyrosine kinase receptor for brain-derived neurotrophic factor (BDNF) that regulates energy balance downstream of melanocortin-4 receptor (MC4R). PIK3C2G (rs12816270 Pgenotyped=8.06x10-6; rs10841048 Pimputed_1000G=6.28x10-7) was associated with BMI, but not with T2D as reported elsewhere. BMI also associated with CNTNAP2 (rs6960319 Pgenotyped=4.65x10-5; rs13225016 Pimputed_1000G=6.57x10-5), previously identified as the strongest gene-by-environment interaction for BMI in African-Americans. The top hit (rs11240074 Pgenotyped=5.59x10-6, Pimputed_1000G=5.73x10-6) for T2D lies 5’ of BCL9 that, along with TCFL2, promotes beta-catenin’s transcriptional activity in the WNT signaling pathway. Additional hits occurred in genes affecting pancreatic (KCNJ6, KCNA1) and/or GABA (GABRR1, KCNA1) functions. Notable associations observed for genes previously identified at genome-wide significance in other populations included MC4R (Pgenotyped=4.49x10-4) for BMI and IGF2BP2 Pimputed_1000G=2.55x10-6) for T2D. Our results may provide novel functional leads in understanding disease pathogenesis in this Australian Aboriginal population.

  Study EGAS00001001004

• The data access committee for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  Dac EGAC00001003253