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• RNAseq and ATACseq on HGSC lines, pre- and post-treatment with an epigenetic drug

  This study looked to determine changes in gene expression and chromatin accessibility of five HGSC cell lines, following treatment with a novel epigenetic drug. The epigenetic drug, HKMTi-1-005, is a compound with dual activity against H3K27 and H3K9 methylation. The cell lines used were PEO1, PEO4, PEA2, OVCAR5, OVCAR8.

  Study EGAS50000000047

• Copy-choice recombination during mitochondrial L-strand synthesis causes DNA deletions

  The dataset comprises of seven samples described below 1. Muscle samples from three patients with late-onset PEO caused by compound heterozygous POLG variants M0305 POLG W748S/R1096C M1105 POLG A467T/T251I+P587L M1804 POLG A467T/X1240G+35aa 2. Muscle sample from a patient with adPEO with heterozygous TWNK variants M0230 TWNK p.Arg357Pro 3. Blood control samples from two patients with late-onset PEO caused by compound heterozygous POLG variants DNA2012-1630_S1 POLG W748S/R1096C DNA2018-0168_S2 POLG A467T/T251I+P587L 4. Muscle samples from healthy control individuals DNA2018-0172_S4 Healthy control 2 DNA2018-0173_S5 Healthy control 1

  Dataset EGAD00001004271

• NABUCCO cohort 1 (NCT03387761) - Neo-Adjuvant Bladder Urothelial Carcinoma COmbination-immunotherapy

  NABUCCO cohort 1 sequencing data. The dataset includes: * Whole exome DNAseq pre-treatment on tumor samples (n=24) matched with blood samples (n=24) * RNAseq pre-treatment on tumor samples (n=18) * RNAseq post-treatment on tumor samples (n=18). Not all pre-treatment samples are linked with pre-treatment samples * High coverage Whole exome DNAseq on pre-treatment tumor samples (n=3) matched with post-treatment metastasized lymph nodes isolated with laser microdissection (n=3) * All samples are labelled with the response phenotype (Complete Responder or Non-Complete Responder)

  Dataset EGAD00001006250

• University of Miami Study on Genetics of Autism and Related Disorders (AutismDisorders)

  Autism spectrum disorders (ASD) are neurodevelopmental in origin and characterized by impairments in reciprocal social interaction and communication accompanied by restricted and repetitive patterns of interest or behavior. With improved surveillance and a broadening of the diagnostic criteria, the most recent prevalence studies suggest that ASD may affect as many as 1/166 children in the US. Treatments are limited resulting in little impact on the profound morbidity. Little is known about the etiology of ASD, but there is a strong genetic component. Genetic studies over the past decade have failed to identify definitive ASD genes, but have clearly shown that the underlying genetics are more complex than anticipated with the likelihood that multiple genes are acting independently and/or interactively. With this realization the field of ASD genetics is at a critical juncture. To move forward we must embrace new and creative paradigms to successfully dissect the genetic etiology of this disease. Specifically the current study will: Extend our ascertainment to the full range of ASD. We will increase our ASD dataset by collecting 600 families who meet clinical diagnostic criteria for the three most common ASDs: autism (AUT), Asperger disorder (ASP) and Pervasive Developmental Disorder-NOS (PDD-NOS). Phenotype assessment will be expanded to include the Social Responsiveness Scale (SRS) and detailed seizure data. Ascertainment will focus on parent-child trios. Further characterize the ASD-associated variations in the Gamma-Aminobutyric Acid (GABA) receptor (GABR) subunits. We will complete our GABR subunit variant analysis, including coding, UTR, regulatory, and conserved intronic sequence, concentrating on GABRA4 and GABRB1. We will also investigate the role of variation in other GABR subunits. All AUT specific findings will be examined in the entire ASD dataset. Identify the chromosome 19p ASD gene. Multiple genome-wide screens have provided significant evidence for linkage to Chromosome 19p and we have found evidence for significant association in the linked families within an ~3 Mb region. We will genotype 768 SNPs spaced at ~4 kb to refine the candidate region and delineate specific candidate genes for further testing. We will screen the strongest associated candidate genes for additional variants and evaluate evidence for association in the entire ASD dataset (SA5). Develop and apply the Phenotypic Homogeneity Distinction (PHD) algorithm for identification of the phenotypic signature of linkage and/or association signals. The PHD algorithm identifies phenotypic covariates that discriminate a target sample subset (e.g. the positively linked families or families carrying the associated risk allele) from its complement. The resulting PHD discriminators will define a homogeneous subset from our newly-ascertained ASD dataset to use, as a confirmatory dataset and for localization within genes under study in our other aims. Test for gene-gene interactions. To fully explain the spectrum of autism risk, we will test for interactions between genetic variations associated with ASD (such as those in GABR subunit genes). We will build upon our experience using the MDR method and extend our analyses across biological pathways using the entire ASD data set.

  Study phs000436

• Average_5mC_DIFF_Roadmap

  Average methylation difference 12 months vs 0 months at Roadmap Epigenomics chromatin state annotations from different cell types using nanopolish. Data from 8 individuals.

  Dataset EGAD00010002410

• CIRdb-CEU1

  Single Nucleotide Polymorphisms in autosomes of Canary Islanders

  Dataset EGAD00010002294

• Transcriptome of (peripheral blood), from donor Sample A, replicate 2 FACS processing technical replicates

  FACS processing technical replicates

  Dataset EGAD00001010087

• Single-cell multiomics reveals the interplay of clonal evolution and cellular plasticity in hepatoblastoma

  Dataset EGAD00001010049

• KUI7052

  Nanopore pericentromere hypomethylation

  Dataset EGAD00001009886

• RCRF release 1

  Transcriptome sequencing from the Rare Cancer Research Foundation: leiomyosarcoma, large cell neuroendocrine carcinoma, clear cell carcinoma

  Dataset EGAD00001010198