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• BurkinaFaso_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:BurkinaFaso

  Dataset EGAD00010001739

• Gambia_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Gambia

  Dataset EGAD00010001738

• Mali_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Mali

  Dataset EGAD00010001737

• Nigeria_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Nigeria

  Dataset EGAD00010001736

• PNG_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:PNG

  Dataset EGAD00010001735

• Ghana_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Ghana

  Dataset EGAD00010001734

• MalariaGEN_GWAS-2.5M_b37_aligned_phased

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations: phased genotypes

  Dataset EGAD00010001748

• MalariaGEN_Gambia-HLA_typing

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations: Gambian trio HLA typing

  Dataset EGAD00010001818

• SAFIR02_Cytoscan

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Dataset EGAD00010002239

• Single Cell RNA-Seq

  Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq. Nine techniques applied to samples from four PDX models: #105, #177, #233, #264

  Dataset EGAD50000000216

• Induced pluripotent stem cell derived pericytes respond to mediators of proliferation and contractility

  Differentiation of mesoderm pericytes from induced pluripotent stem cell lines.

  Study EGAS50000000176

• Breast Invasive Lobular Carcinoma CDH1 WGS dataset

  We subjected to whole genome sequencing (WGS) one ILC case lacking CDH1 biallelic mutations. Both tumor and normal samples were sequenced.

  Dataset EGAD50000000696

• Roifman DAC

  This Data Access Committee will oversee all requests for data submitted by Dr. Chaim Roifman at the Hospital for Sick Children in Toronto, Canada. Requests should be directed by email to chaim.roifman@sickkids.ca.

  Dac EGAC50000000396

• RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Transcriptomic analysis of K7M2 murine osteosarcoma cells stably modified to overexpress or repress CYR61

  Dataset EGAD50000000747

• Phenotype-modifier genes in FHHNC

  Whole exome sequencing data in FHHNC patients stratified in extreme phenotypes to identify potential phenotype modifier variants

  Dataset EGAD50000001217

• VHIR Renal Physiopathology Group DAC

  This DAC describes the members of the Data Access Committee and the policy that will regulate access to the datasets uploaded at EGA from the Renal Phyisiopathology Group at VHIR

  Dac EGAC50000000510

• Picuris Pueblo Genomic Project – Modern Dataset

  Please refer to the Supplemental Materials of the paper for more information.

  Dataset EGAD50000001245

• DAC policy The Kids Research Institute Australia

  DAC policy related to the study: Visium CytAssist Spatial Gene Expression analysis for FFPE glioblastoma samples. Committee: Emily Fletcher emily.fletcher@thekids.org.au Anya Jones anya.jones@thekids.org.au Emma Stone emma.stone@thekids.org.au

  Dac EGAC50000000734

• Glioblastoma stem cell lines RNA-seq

  RNA-seq data for three Glioblastoma stem cell (GSC) lines exposed to PRMT5 inhibitor and control samples.

  Dataset EGAD00001006095

• ONT Minion reads for a patient with ataxia-pancytopenia syndrome.

  ONT Minion reads to provide 30x coverage for a patient with ataxia-pancytopenia syndrome.

  Dataset EGAD00001005022

• Widespread hypertranscription in aggressive human cancers

  Data used to validate RNAmp tool.

  Dataset EGAD00001009285

• H3Africa EPIGEN Phenotype

  Phenotype data from pregnant mothers unexposed and exposed to the Rwandan genocide from 59 whole blood samples.

  Dataset EGAD00001009739

• mFAST-SeqS estimation of tumor fraction

  Modified Fast Aneuploidy Screening Test-Sequencing System (mFAST-SeqS) was applied to stratify samples based on their overall tumor fraction in cfDNA.

  Dataset EGAD00001006385

• Study on the Genetics of Alcoholism (COGA): African American Family GWAS

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative African American families were selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Omni2.5_080814_1 chip to genotype 3,438 subjects selected from densely affected families. Genotyping was performed at CIDR. This sample complements a set of densely affected European American families previously made available under dbGaP study accession phs000763. In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2.For version 3, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings, Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance abuse variables are made available in version 3. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study (phs000125). GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data (phs000763). GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS (phs000976). GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS (phs001208). GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000976

• Single-cell profiling reveals mechanisms of response to anti-PD-L1 versus anti-PD-L1 combined with anti-CTLA4 in head and neck squamous cell carcinoma

  Cancer patients often receive a combination of PD-(L)1 and CTLA4 inhibitors, but the mechanisms underlying their concerted actions remain unclear. We conducted a neoadjuvant study in head and neck squamous cell carcinoma (HNSCC) involving anti-PD-L1 monotherapy versus anti-PD-L1/anti-CTLA4 combination. Single-cell profiling of on- versus pre-treatment biopsies confirmed T-cell expansion as response biomarker. We identified a type 1 immune response accompanying T-cell expansion on-treatment across treatment arms, and herein characterized co-localized IgG plasma cell expansion as important contributor. In pre-treatment biopsies, similar features correlated with expansion upon anti-PD-L1, but not anti-PD-L1/anti-CTLA4. By profiling tumor-draining lymph nodes, we found the addition of anti-CTLA4 to trigger activation and subsequent trafficking of CD4+ T-cells via the blood, to become T-helper 1 cells in the tumor. anti-PD-L1/anti-CTLA4 indeed facilitated co-localized expansion of CD4+ and CD8+ T-cells in tumors versus mostly CD8+ T-cells with anti-PD-L1 alone. Hence, we identify complimentary mechanisms underlying anti-PD-L1/anti-CTLA4 therapy in HNSCC.

  Study EGAS50000000037