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• Summary Statistics GWAS SSNS

  Column 1 “rsid”: SNP identifier Column 2 “chromosome”: name of chromosome on which the SNP is located Column 3: “position”: base pair position on the chromosome Column 4 “minor_test_allele”: the base that constitutes the minor allele Column 5 “major_allele”: the base that constitutes the major allele Column 6 “maf”: the frequency of the minor allele, indicated as a fraction of 1 Column 7 “allele_freq_cases”: the minor allele frequency in cases Column 8 “allele_freq_controls”: the minor allele frequency in controls Column 9 “regression_pvalue”: the p-value for the difference in allele frequency between cases and controls Column 10 “odds_ratio”: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00001008782

• Single cell sequencing of human normal luminal cells

  The dataset includes 12 paired FASTQ files (6 samples) with single cell transcriptome sequencing data of normal breast luminal cells from ducts and TDLUs derived from reduction mammoplasties from three patients. Chromium Single Cell 3’ Reagent Kit v2 or v3 (10x Genomics) were used for processing of cells, whereafter sequencing was performed using the Illumina® NextSeq500/550 High Output Kit v2. Cell Ranger was used for generating FASTQ files and files from different lanes were concatenated prior to uploading the data to EGA. "R1" files include the feature barcodes and UMIs, while "R2" files include the reads.

  Dataset EGAD00001008499

• Whole exome and transcriptome sequencing of BPDCN

  This data set contains whole exome and transcriptome data from 47 case with BPDCN. For exome data, bam files are provided (mapped against GRCh38), for transcriptome raw fastq-files (paired-end data).

  Dataset EGAD00001008692

• Single-cell omics data for COVID-19 patients

  Single-cell RNA-seq, single-cell ATAC-seq, and genotypes used in the analysis for the study "Altered and allele-specific open chromatin landscape reveal epigenetic and genetic regulators of innate immunity in COVID-19". The RNA-seq and ATAC-seq are raw data in FASTQ format while the genotypes are in the VCF format which was filtered and imputed (more details are available in the main text of the study).

  Dataset EGAD00001009331

• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  We carried out WGS and RNAseq on a cohort of 48 children and young adults with induction failure in T-cell Acute Lymphoblastic Leukemia (T-ALL) to identify genomic drivers of treatment resistance. The study includes WGS for 33 tumour/normal pairs and 15 tumour-only samples. In addition, there is RNAseq data for 37 cases.

  Dataset EGAD00001009058

• Single Cell Genome Sequence for DLP+ library A96210B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1047B on DLP+ library A96210B

  Dataset EGAD00001009475

• Sequencing data for oesophageal and related samples - Abbas et al (WGS)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (WGS for 1397 samples)

  Dataset EGAD00001011196

• Immune Response Targeted Panel + B/TCR Profiling + AbSeq + Sample Tag Multiplexing

  Multiomics data for a cohort of 20 COVID-19 patients (10 patients mild, 3 patients moderate, 4 patients severe, 3 patients critical) obtained from peripheral blood mononuclear cells (PBMCs) from longitudinally sampled at hospital admission, discharge, and 1 month thereafter. The data has been obtained a multiwell-based single-cell technology (BD Rhapsody) that includes the targeted expression of BD Immune Response Targeted Panel, the TCR/BCR profiling and a set of 52 surface proteins. The samples of the different patients at different collection times were labelled using a cell hashing strategy with the BD Single-Cell Multiplexing Kit (6 samples for each run).

  Dataset EGAD00001011319

• University of Miami Udall Center of Excellence Identification of Rare Variants in PD through Whole Exome Sequencing

  The focus of this study is to identify a new level of genetic variation, i.e. rare genetic variants with a population frequency less than 5%, usually less than 1%, which are believed to provide a stronger risk per variant than those studied to date in the large genome wide association studies (GWAS). To do this we are generating whole exome sequencing data on the Illumina HiSeq. Each HiSeq produces at least 600 billion base pairs of DNA sequence in one run. Whole exome sequencing sequence data, about 50 million base pairs, or about 1.5% of the total DNA of each person's genome, is generated. We are using this data to look for new DNA variations that give risk for Parkinson disease, as well as "modifiers", that may lead to having more severe or milder disease or later or earlier ages of onset.

  Study phs000908

• Genetic Determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo

  Oncogenic alterations in EGFR frequently co-occur with additional genetic alterations in EGFR-driven lung adenocarcinoma (LUAD), but how specific combinations of mutations affect tumor phenotypes and responses to targeted therapy is yet unknown. We leveraged a genetically engineered mouse model of EGFR mutant/Trp53-deficient LUAD to study the consequences of inactivating 10 different tumor suppressor genes on the fitness and tyorosine kinase inhibitor (TKI) sensitivity of these tumors. We found that loss of Keap1 is associated with a reduced response to therapy. In patients, we found that mutations in the KEAP1/NFE2L2/CUL3 pathway are associated with a significantly shorter time to treatment failure for EGFR TKI therapy compared to matched patients with wild-type KEAP1/NFE2L2/CUL3 tumors. We also analyzed whole exome sequencing data from tumor specimens before TKI treatment and at the time of treatment resistance for mutations in the KEAP1 pathway and these data are being submitted here.  

  Study phs002334