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• June 2017 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2017 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001003414

• SCLC study MGH - WES dataset

  For whole-exome sequencing 1 µg of DNA from fresh-frozen tumors was fragmented by sonication technology (for DNA from fresh-frozen tumors: Bioruptor, diagenode, Liѐge, Belgium; for DNA from FFPE material: Covaris). The fragments were end-repaired and adaptor-ligated, including incorporation of sample index barcodes. After size selection, libraries were subjected to an enrichment process with Sure select XT (Agilent). The final libraries were sequenced with a paired-end 2×75 bp protocol for an average coverage of 100-120x

  Dataset EGAD00001003970

• June 2018 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  June 2018 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001004300

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281

• Synthetic genotypes and phenotypes of 500.000 individuals

  The goal of our study is to establish a pipeline for creating synthetic genotype and phenotype data on a Biobank scale. Such data can be used for developing new methodologies of analysis of common and rare diseases without risking de-identifying the underlying samples.

  Study EGAS00001006552

• Fastq files used for searching for variants associated with endometriosis at 9p21 region

  We performed target re-sequencing for 1.29 Mb interval of chromosome 9 (chr9:21299764–22590271, hg19). NimbleGen SeqCap EZ choice system was used as a target enrichment method (Roche Diagnostics). A DNA probe set complementary to the target region was designed by NimbleDesign. The libraries were sequenced on the Illumina MiSeq platform with 2×150-bp paired-end module (Illumina). Fastq files for 48 Japanese patients with endometriosis are deposited.

  Dataset EGAD00001001942

• September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  September 2016 data update (bam/fastq/vcf) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001002724

• May 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  May 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001005060

• August 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2019 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001005335

• August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001006383

• KiCS cancer panel data for academic and for-profit use

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009734

• Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19

  These data correspond to samples used in the following papers: 1. GWAS and meta-analysis identifies 49 genetic variants underlying critical Covid-19 2. Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19. 3. Identification of Genetic Determinants of Transcriptional Response to Metformin in Primary Human Monocytes. They are the raw RNA sequencing files as used in all downstream analysis.

  Dataset EGAD00001010176

• DAC for BillionToOne

  This is the Data Access Committee for studies published by BillionToOne.

  Dac EGAC50000000418

• APL nanopore sequencing

  Nanopore sequencing for an APL patient

  Study EGAS00001005618

• Towards standardized whole exome sequencing (WES) for cancer patients: lessons from a multicentric pilot study

  A growing number of druggable targets and national initiatives for precision oncology necessitate broader genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a sensitivity between 91-95% and a positive predictive value (PPV) of 82-95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Deviations were observed for cases with low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

  Study EGAS00001007363

• This study generated Oxford Nanopore long read sequencing data of cancer cell line mixtures for validating long-read variant calls in cancer genomics

  Long-read sequencing (LRS) improves genome alignment and facilitates resolving variants in complex genomic regions, making it a promising approach for cancer variant detection and biomarker discovery. Here, we evaluate the performance of LRS to detect somatic variants across different tumour purities and sequencing depths by comparing to somatic variants from short-read sequencing. We generated experimental mixtures of cancer cell lines and matched normal cell lines to simulate 10 tumour purities (ranging from 0 to 100% tumour content). This resulted in 22 samples which were sequenced using whole genome LRS to a targeted depth of 60x and somatic variants were identified. We downsampled sequencing data to explore the optimal read depth for somatic variant detection. Our results show that long-read variant calling tools achieve recall rates comparable to short-read gold standards. While a tumour sequencing depth of 30x to 60× is generally sufficient for detecting common variants, particularly structural variants (SVs), sequencing the matched normal sample at adequate depth is crucial for accuracy. Notably, we found variants unique to LRS that may represent real and previously undetected events. This study highlights key factors for optimising cancer genome sequencing with LRS and provides a comprehensive dataset of cell line mixtures for future research and tool development.

  Study EGAS00001008107

• Elucidating Mechanisms of the Graft versus Leukemia Effect of Hematopoietic Stem Cell Transplant for Acute Myeloid Leukemia

  Donor lymphocyte infusion (DLI) is an established mode of adoptive cellular therapy for treatment of relapsed disease after allogeneic hematopoietic stem cell transplantation (HSCT). For patients with acute myeloid leukemia (AML), the response rate to DLI is only 20%. Here we use next generation sequencing technologies to understand the transcriptomic and immunologic features associated with response or resistance to therapy.

  Study phs003630

• Single-cell transcriptome analysis of B-cell development in the ABO platform

  The dataset includes samples from four individual donors, pooled at each cell-harvesting time point (days 21, 28, and 35). Single-cell RNA sequencing was performed on the 10x Genomics Chromium platform using GEM-X Single Cell 5′ v3 and GEM-X Single Cell V(D)J v3 for BCR profiling. For each timepoint, paired libraries were constructed: a 5′ GEX library and a V(D)J-B library. Per reaction 350,000-400,000 cells were loaded, aiming for 60,000 cells per reaction. Pooled libraries were sequenced on an Illumina NovaSeq X sequencer. 50,000 read pairs per cell for GEX and 5,000 read pairs per cell for V(D)J were targeted.

  Dataset EGAD50000002433

• Normal brain controls for ICGC PedBrain DNA methylation sequencing

  DNA methylation profiling of 8 control samples from adult (4) and fetal brain (4) used, for example, for the following studies: Mack, Witt, et al. Epigenomic alterations define lethal CIMP-positive ependymomas of infancy. Nature 506(7489):445-450, 2014 (see EGAS00001000443) Hovestadt, et al. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. 510(7506):537-541, 2014 (see EGAS00001000561)

  Study EGAS00001000909

• March 2019 data update for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2019 data update for cord blood CD34+CD38-, CMP, GMP, MEP, monocyte, erythroid precursor, B cell and primary AML total blasts reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium. This dataset contains data for samples: CEMT0158 CEMT0159 CEMT0160 CEMT0161 CEMT0162 CEMT0163 CEMT0164 CEMT0165 CEMT0166 CEMT0167 CEMT0168 CEMT0169 CEMT0170 CEMT0171 CEMT0172 CEMT0189

  Dataset EGAD00001004950

• The data access committee for "Validation of cfDNA fragmentome analyses for early detection of liver cancer"

  Dac EGAC00001003543

• Medulloblastoma WES

  WES for tumor and normal samples

  Study EGAS50000000261

• Deep_sequencing_of_melanoma_for_driver_mutations

  Deep sequencing of melanoma for driver mutations

  Study EGAS00001000857

• 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

• DAC for study CMMRD–associated high-grade glioma

  This Data Access Committee (DAC) is responsible for de-identified, summarized somatic variant call data derived from paired tumor–blood Whole-exome sequencing of human samples in a glioma research study. Access requests are approved without additional restrictions and are granted solely for health-related research purposes.

  Dac EGAC50000000855