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• RNA-seq

  Stranded RNA-seq libraries were performed for 150 ng of mRNA using the TruSeq library kit (Illumina, San Diego, CA, USA). Libraries were sequenced on a NextSeq 2000 (Illumina) in a 2x50bp length.

  Dataset EGAD00001010841

• Dataset for WES PCNSL

  WES sequencing of 23 samples from PCNSL tumor and blood control samples. Sequencing was performed on a NovaSeq 6000 and NextSeq 500 using Agilent SureSelectXT HS Human All Exon V7 and V8. Sequencing was always paired.

  Dataset EGAD00001010847

• HiChIP bulk

  This dataset gather HiChIP data for H3K27ac mar in MM.1S cell line in control and Dex condition, both in two biological replicates

  Dataset EGAD00001011138

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• Ewing's Sarcoma Whole Genome Sequencing

  54 WGS Ewing's sarcoma samples sequenced at The Hospital for Sick Children Toronto (Adam Shlien's lab) and published on Science 2018. Reference Anderson et al. "Rearrangement bursts generate canonical gene fusions in bone and soft tissue tumors"

  Dataset EGAD00001004589

• A96225C

  Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96225C 1034 samples; filetype=bam

  Dataset EGAD00001005355

• PFA ependymoma study -RNA-seq data

  RNA-seq fastq files for the 16 samples used in Michealraj et al. Cell 2020. The samples include PFA and ST ependymoma tissues, normal pediatric brain as control and PFA ependymoma lines.

  Dataset EGAD00001006046

• Bulk RNAseq fastq files

  RNAseq FASTq files from 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert).

  Dataset EGAD00001006975

• Spit for Science

  Spit for Science™ is a university-wide research opportunity with the scientific goal of understanding how genetic and environmental factors come together to influence substance use and emotional health across the college years and beyond. To address this goal, we have comprehensively and longitudinally studied eligible incoming freshmen (18 years or older) from a diverse urban university, assessing a wide range of risk and protective factors, including both biological susceptibility and environmental risk, and a variety of outcome measures, particularly alcohol use and other substances, and difficulties with emotional health. Our goal is to assess how risk and protective factors dynamically interact to contribute to behavior health outcomes over time and plan to use findings from the project to inform prevention and intervention efforts and aid in university policy and programming in ways that can support and promote student success. Methods: In the fall of their freshman year, first-time college students over the age of 18 are invited to complete an online survey containing broad questions about personality and behavior, as well as family, friends, and experiences growing up. Students can also provide a saliva sample and participate in the DNA component of the project (participation in the DNA component is not a requirement for participation in the survey). Each subsequent spring students are asked to complete a follow-up survey, enabling researchers to study patterns of substance use and emotional health across the college years.

  Study phs001754

• Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

  Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

  Study phs001041

• The Genetics of Type 2 Diabetes Consortium (GoT2D): Low-Pass Sequencing and High-Density SNP Genotyping for Type 2 Diabetes

  The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome (Fuchsberger et al, 2016), and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in dbGaP will include all the Swedish, Finnish, and UK samples, but the German data will be deposited in the European Genome-phenome Archive (EGA), by virtue of the project specific funding requirements.

  Study phs000840

• Risk Factors for Asymptomatic Diverticulosis

  Data for this analysis came from a prospective study of colonic diverticulosis at the University of North Carolina Hospital in Chapel Hill, North Carolina (NIH R01DK094738). This is a case-control genetic and transcriptomic study to identify the genetic and cellular determinants underlying colonic diverticulosis and the relationship with other gastrointestinal disorders. The study inclusion and exclusion are described below. DNA and RNA sequencing were performed on colonic tissue from 404 patients with (N=172) and without (N=232) diverticulosis. We assessed variation in the transcriptome associated with diverticulosis and integrated this variation with human intestine single-cell RNA-seq data. We integrated our expression quantitative trait loci with GWAS using Mendelian Randomization. A polygenic risk score analysis examined associations between severity of diverticulosis and other gastrointestinal disorders. We identified 38 genes with differential expression and 17 genes with varied transcript usage linked to diverticulosis. Our results suggest tissue remodeling as a primary mechanism for diverticula formation. The presence of diverticulosis was linked to stromal and epithelial cells in the colon including endothelial cells, myofibroblasts, fibroblasts, goblet, tuft, enterocytes, neurons, and glia. MR highlighted five genes including CCN3, CRISPLD2, ENTPD7, PHGR1, and TNFSF13. In diverticulosis cases, ENTPD7 upregulation was confirmed. A greater burden of diverticula was positively correlated with genetic predisposition to diverticulitis. The data related to the study including total RNA-Seq, SNP array and imputed genotypes will be available through dbGaP.

  Study phs003556

• UCSF Database for the Advancement of JMML - Integration of Metadata with Omic Data

  Juvenile myelomonocytic leukemia (JMML) is a rare and frequently fatal myeloproliferative/myelodysplastic disorder of early childhood with an estimated incidence of 1.2 cases per million. It is associated with a spectrum of diverse outcomes ranging from spontaneous resolution in rare patients to transformation to acute myeloid leukemia in others. The overwhelming majority of JMML patients (~95%) will harbor mutations in canonical Ras pathway genes, including NF1, NRAS, KRAS, PTPN11, and CBL. As Ras proteins are mutated in more than 30% of human cancers, the information gleaned from the study of JMML has provided insights into Ras signaling in cancer as well as a group of congenital diseases with tumor predispositions known as the “Rasopathies”. While oncogenic Ras is one of the most common mutations in human cancer, it remains one of the most vexing targets for efficacious therapy. To better understand this disease, a JMML tissue bank was established at UCSF that allows for consenting of subjects, biobanking of tissue and collection of follow up data from patients both locally and at other institutions. Through the collection and analysis of specimens, knowledge about the genetic, epigenetic, and biochemical basis of JMML has been gained. This integrated database will enable future JMML research, and importantly, additional Ras/MAPK pathway research by depositing linked, processed data to well annotated anonymized patients in an easily accessible online database

  Study phs002504

• Ultra-long sequencing for contiguous haplotype resolution of the human immunoglobulin heavy chain locus

  Genetic diversity within the human immunoglobulin heavy chain (IGH) locus influences the expressed antibody repertoire and susceptibility to infectious and autoimmune diseases. However, repetitive sequences and complex structural variation pose significant challenges for large-scale characterization. Here, we introduce a method that combines Oxford Nanopore ultra-long sequencing and adaptive sampling with a bioinformatic pipeline to produce haplotype-resolved, annotated IGH assemblies. Notably, our strategy overcomes prior limitations in phasing resolution, enabling single-contig haplotype assemblies that span the entire IGH locus. We applied this method to four individuals and validated the accuracy of the IGH assemblies using Pacific Biosciences HiFi reads, demonstrating near-complete sequence congruence, detecting only indels with a high degree of confidence. Moreover, when applied to the reference material HG002, our pipeline revealed no base differences and a limited number of indels compared with the Telomere-to-Telomere genome benchmark across the IGH region. Importantly, in the four individuals, our approach uncovered 30 novel alleles and previously uncharacterized large structural variants, including a 120 kb duplication spanning IGHE to IGHA1 and an expanded seven-copy IGHV3-23 gene haplotype. These findings underscore the power of our method to resolve the full complexity of the IGH locus and uncover previously unrecognized variants that may affect immune function and disease susceptibility. Thus, our method provides a strong basis for future immunological research and translational applications.

  Study EGAS50000001042

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

  Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

  Study EGAS00001004301

• NIPT samples for systematic evaluation of BinDel, a software tool for detecting clinically significant microdeletions in low-coverage WGS-based NIPT samples

  This dataset contains three sets of samples. The first sample set contains euploid fetus pregnancies reported by NIPTIFY screening test and postnatal evaluation. Dataset was processed similarly to previously published guidelines from KU Leuven, with modifications [1]. Briefly, peripheral blood samples were collected in cell-free DNA BCT tubes (Streck, USA), and plasma was separated with standard dual centrifugation. Cell-free DNA was extracted from 3 ml plasma using MagMAX Cell-Free DNA Isolation Kit (ThermoFisher Scientific). Whole-genome libraries were prepared using the FOCUS (Fragmented DNA Compact Sequencing Assay, Competence Centre on Health Technologies, Estonia) NIPT method protocol with 12 cycles for the final PCR enrichment step. In the following quantification, equal amounts of 36 samples were pooled, and the quality and quantity of the pool were assessed on Agilent 2200 TapeStation (Agilent Technologies, USA). Whole genome sequencing was performed on the NextSeq 550 instrument (Illumina Inc.) with an average coverage of 0.32× (minimum 0.08 and maximum 0.42) and producing 85 bp single-end reads. The second sample set contains a single NIPT sample postnatally diagnosed with Prader-Willi syndrome. The sample was sequenced with Illumina NextSeq 500 platform, producing 85 bp single-end reads with an average per-sample coverage of 0.32× at the University of Tartu, Institute of Genomics Core Facility, according to the manufacturer’s standard protocols, as described previously [2]. The third sample set contains samples SC005 (SeraCare Life Sciences Inc lot #10446565), SC0042 (#10571706), and SC016 (#10560229). These are SeraCare Life Sciences Inc circulating cell-free DNA (ccfDNA) like mixture of human genomic DNA that consists of matched maternal and fetus. SC005 and SC0042 consist of matched DNA of maternal and fetus with DiGeorge Syndrome. SC016 is a custom-ordered DNA Mix with fetus DNA having a pathogenic loss of the terminal region of 20p13 and a pathogenic 3q29 duplication. SC016 was processed as the first sample set was processed, and SC0042 was processed as the second sample set was processed. Sample SC005 was processed once as was sample set 1 and once as was sample set 2 processed. This study was performed with the approval of the Research Ethics Committee of the University of Tartu (#352/M-12). 1. Bayindir B, Dehaspe L, Brison N, Brady P, Ardui S, Kammoun M, et al. Noninvasive prenatal testing using a novel analysis pipeline to screen for all autosomal fetal aneuploidies improves pregnancy management. Eur J Hum Genet. 2015;23: 1286– 1293. doi:10.1038/ejhg.2014.282 2. Žilina O, Rekker K, Kaplinski L, Sauk M, Paluoja P, Teder H, et al. Creating basis for introducing noninvasive prenatal testing in the Estonian public health setting. Prenat Diagn. 2019;39: 1262–1268. doi:10.1002/pd.5578

  Dataset EGAD00001009512

• Abundant Quantitative Trait Loci Exist for DNA Methylation and Gene Expression in Human Brain

  These data are derived from iterative data collection and analysis partly reported in three primary publications (Gibbs et al., 2010, PMID: 20485568, Hernandez et al. 2011, PMID: 21216877, Hernandez et al. 2012, PMID: 22433082). This study includes an assessment of common genetic variability across the genome, chip based gene expression analysis and array based methylation analysis, across a series of 150 subjects from whom we had cerebellum, frontal cortex, pons, and temporal cortex tissue (600 tissue samples). In each tissue we assessed 27,578 DNA methylation sites and the expression level of 22,184 genes. This work was then expanded to include assessment of 232 additional subjects and two tissues (cerebellum and frontal cortex) for whom we collected genotype, RNA expression and DNA methylation data.

  Study phs000249

• DNA Methylation Analysis of Peripheral Blood Cells from Siblings Discordant for ASD

  Autism is a common disorder whose causes are poorly understood. Both genetic and environmental influences are thought to act together causing autism. Epigenetics is an area that bridges genetic and environmental influencing and commonly is studied by examining dynamic methylation changes to the DNA. We have screened a total of 78 autistic boys and their fathers by this method in 807 genes and find 116 methylation changes that together can correctly identify nearly 80% of the affected boys from their fathers. We propose to confirm these exciting data in a much larger set of genes in 1,200 autistic boys and their families, including unaffected brothers. These data not only could provide new insight into the causes of autism but could also result in a screening test for autism.

  Study phs000619

• Developing Targeted Therapy for Patients with Multiple Myeloma and Gain or Amplification of Chr1q (1q+)

  Multiple myeloma (MM) frequently presents with gain or amplification of chr1q (1q+), which is associated with inferior response to treatment and poor outcomes. To develop targeted therapy for MM with 1q+, we leveraged external and in-house dependency screens and drug screens, along with single-cell sequencing of patient tumors with subclonal 1q+. We demonstrated that MM with 1q+ exhibits higher sensitivity to MCL1 and PI3K inhibitors, which may be synergistic and act through established and novel mechanisms. Two human MM cell lines with 1q+, KMS12BM and KMS11, were profiled with either single-cell RNA-sequencing (scRNA-seq) alone (KMS12BM, KMS11) or both scRNA-seq and whole-genome sequencing (WGS; KMS12BM) to understand the factors that determine response to MCL1 and PI3K inhibitors and how these inhibitors work.

  Study phs003886

• Head and neck tumor organoid biobank for modelling individual responses to radiation therapy according to the TP53/ HPV status

  Head and neck cancers (HNC) represent an extremely heterogeneous group of diseases with a poorly predictable therapy outcome. Here, we have established a comprehensive molecularly and functionally characterized head and neck organoid biobank recapitulating the clinically relevant subtypes of TP53 mutant and human papillomavirus type 16 (HPV 16) infection-driven HNC. Organoids were exposed to radiotherapy and genetically engineered normal and tumor organoids were used for testing the direct functional consequences of TP53-loss and HPV infection. We identified subtype-associated transcriptomic signatures and pathological features, including sensitivity to TP53 stabilization by the MDM2 inhibitor Nutlin-3. TP53 loss-of-function alone was insufficient to promote radiation resistance, whereas HPV 16 oncogenes E6/E7 mediated radiosensitivity via induction of cell cycle arrest.

  Study EGAS50000001219

• Truncated FOS impairs osteogenic differentiation and induces prostaglandin and NFkB signalling in an in vitro cell-of-origin model for osteoid osteoma and osteoblastoma

  The effect of FOS truncation on osteogenic differentiation and proliferation was investigated in an in vitro model for osteoid osteoma and osteoblastoma. In this model, truncated FOS (FOSΔ) was overexpressed in human foetal mesenchymal stem cells through a lentiviral vector. Osteogenic differentiation - assessed by measuring mineralization, ALPL expression and ALP activity - and proliferation rate were reduced in cells overexpressing FOSΔ compared to mesenchymal stem cells with an empty lentiviral vector (pLV). Transcriptome-sequencing and differential gene expression analysis revealed decreased gene expression of genes in pathways involving cell cycling and mitosis, and osteogenic differentiation, including WNT signalling, extracellular matrix (ECM) organization and matrix metalloproteinases (MMPs), in FOSΔ as compared to empty vector cells, indicating decreased proliferation and osteogenesis.

  Study EGAS50000001291

• WGoxBS and SureSelect data of the POPS placenta samples

  We carried out whole-genome oxidative bisulfite sequencing (WGoxBS) in the placentas of two healthy female and two healthy male pregnancies generating an average genome depth of coverage of 25x. The sex-specific differential methylation pattern observed in this region was validated in additional 8 healthy placentas (including 2 from the WGoxBS) using SureSelect in-solution target capture. For WGoxBS, placental genomic DNA (4 µg) from 4 healthy pregnancies was processed to achieve 10 kb fragments with the g-Tube (Covaris), according to the manufacturer's instructions. To increase the number of uniquely sequenced reads, two independent libraries were generated for each individual. Multiplexed sequencing was carried out on the Illumina MiSeq, HiSeq 2000, and HiSeq 2500 instruments with 2x100, 2x50 and 2x125 cycles using MiSeq Reagent Kit v3, HiSeq SBS Kit v3 and HiSeq SBS Kit v4, respectively. For SureSelect in-solution capture, placental genomic DNA (3.5 µg) from 8 healthy pregnancies (including 2 from the WGoxBS) was fragmented by the Covaris S220 system according to the SureSelect Methyl-Seq target enrichment protocol (Agilent). All 8 libraries were pooled and sequenced on the Illumina HiSeq 2500 instrument with 2 × 125 cycles using HiSeq SBS Kit v4 and a single lane of the Illumina HiSeq 4000 instrument with 2 × 150 cycles using HiSeq 3000/4000 SBS Kit following Illumina's guidelines (Illumina Application Note: Epigenetics February 2016).

  Dataset EGAD00001003136

• Samples linked to the study "Performance comparison of three DNA extraction kits on human whole-exome data from formalin-fixed paraffin-embedded normal and tumor samples"

  We generated 42 human whole-exome sequencing data sets from fresh-frozen (FF) and FFPE samples. These samples include normal and tumor tissues from two different organs (liver and colon), that we extracted with three different FFPE extraction kits (QIAamp DNA FFPE Tissue kit and GeneRead DNA FFPE kit from Qiagen, Maxwell\textsuperscript{TM} RSC DNA FFPE Kit from Promega). Variant calling analysis shows a very high rate of concordance between matched FF / FFPE pairs and equivalent performance for the three kits we analyzed. We find a significant variation in the difference of total number of variants called between FF and FFPE samples for the three different FFPE DNA extraction kits. Coverage analysis shows that FFPE samples have less good indicators than FF samples, yet the coverage quality remains above accepted thresholds. We detect limited but significant variations in coverage indicator values between the three FFPE extraction kits. Globally, the GeneRead and QIAamp kits have better variant calling and coverage indicators than the Maxwell kit on the samples used in this study, although this kit performs better on some indicators and has advantages in terms of practical usage. Taken together, our results confirm the potential of FFPE samples analysis for clinical genomic studies, but also indicate that the choice of a FFPE DNA extraction kit should be done with careful testing and analysis beforehand in order to maximize the accuracy of the results.

  Dataset EGAD00001004066

• Characterization of genomic landscape of Peripheral T-cell Lymphomas, not otherwise specified (PTCL-NOS) (2018-10-30)

  Peripheral T-cell lymphomas not otherwise specified (PTCL-NOS) represent a heterogeneous group of nodal and extra-nodal mature T-cell lymphomas, with a low prevalence in Western countries. PTCL-NOSs account for about 25% of all PTCLs and are currently diagnosed based on exclusion criteria, as this lymphomas lack unifying morphological, phenotypic and genomic features. Cytogenetic and FISH analysis of PTCL-NOS samples have not revealed recurrent pathogenetic abnormalities, while gene expression profiling has shown only partial ability to segregate cases representing homogeneous clinic-pathological entities. This underscores the need to look at PTCL-NOS with innovative and high-throughput approaches to identify recurrent genetic lesions that could further our understanding of the biology of this heterogeneous group of diseases, provide better diagnostic tools and perhaps new targets for innovative treatments. Our aim is to study ~15 patients affected by PTCL-NOS. Out study will be funded by a private, non-profit Italian cancer research fund (Associazione Italiana per la Ricerca sul Cancro, www.airc.it) based on a grant owned by Anna Dodero and Cristiana Carniti, hematologists at INT. Samples will be analysed by whole genome sequencing using Illumina X10 machines, on a 150bp-PE protocol. Data will be analysed using the pipeline available in Team 78, under the supervision of Peter Campbell, the WTSI faculty who will oversee the project, and by Francesco Maura, visiting scientist at the WTSI. . This dataset contains all the data available for this study on 2018-10-30.

  Dataset EGAD00001004428

• Microbiota 16S sequencing study in NSCLC patients eligible for surgery without neoadjuvant treatment

  18 non-small cell lung cancer patients eligible for surgery without neaodjuvant treatment were included in the study at Centre Jean Perrin (France). Patients did not take any antibiotics, food supplements or immunostimulants 2 months prior to inclusion. During surgery, patients underwent partial or complete lobectomy where samples of non-malignant lung tissue, peritumoural tissue and tumour were resected from the removed lobe. This was preceeded by the washing of the removed lobe and obtaining the broncho-alveolar lavage fluid. These four sample types were analysed by 16S sequencing in 17 from 18 patients. The study is a part of the project "Characterization of Microbiota (Intestinal, From Lungs, and Upper Airways) in Patients With Non-small Cell Lung Carcinoma: Exploratory Study " which is registered under ref. NCT03068663 (clinicaltrials.gov).

  Study EGAS00001004728

• SNP array data for the Milieu Intérieur cohort

  The Milieu Intérieur Consortium aims at identifying the environmental and genetic factors driving variation in innate and adaptive immune systems among healthy individuals. In the last four years, we combined standardized flow cytometric analysis of blood leukocytes, transcriptional profiles of whole blood after immune stimulation and genome-wide DNA genotyping in 1,000 healthy, unrelated donors of western European ancestry, to show that age, sex, as well as persistent infections and smoking, are the most important drivers of inter-individual differences in blood cell composition and transcriptional response to pathogens. The EGAS00001002460 study includes genotype data for 5,699,237 genotyped and imputed SNPs in the 816 healthy donors of the Milieu Intérieur cohort. Note that 184 of the 1,000 initial donors did not agree to share their data online.

  Study EGAS00001002460

• Genome-wide associations of human gut microbiota variation and implications for causal inference analyses

  Here we use appropriate taxon-specific models along with support from independent cohorts to show association between human host genotype and gut microbiome variation. Using fecal derived 16S rRNA gene sequences and host genotype data from the Flemish Gut Flora Project (FGFP) we identify genetic associations involving multiple microbial traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease, however in the absence of clear microbiome driven effects, caution is needed in interpretation. This work marks a growing catalog of genetic associations which will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

  Study EGAS00001004420

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Study EGAS50000000156

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study

  This is a case-control study of primary open angle glaucoma (POAG). POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. For this study we have formed a collaborative consortium contributing 2170 POAG cases and 2347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition has also been harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The NEIGHBOR consortium has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). The consortium includes eleven different centers where data collection and analysis take place. The eleven sites and investigators are: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman, D. Zack); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Eye Institute (X01HG005259).

  Study phs000238

• Starr County Health Studies' Genetics of Diabetes Study

  An initial observation in the 1970s that Starr County, Texas, had the highest diabetes-specific mortality of any of the 254 Texas counties led to the establishment of a field office in Rio Grande City, Texas (the county seat of Starr County) and the initiation of a series of studies to understand the epidemiology and genetics of type 2 diabetes, its complications and related conditions in this predominantly (97%) Mexican American population. The field office opened in February 1981 and has operated continuously since then. During this time, three systematic surveys of the population have been conducted as well as family and longitudinal studies. Culturally sensitive diabetes education programs have been developed and implemented and also a weight loss intervention. In total, more than 23,000 Mexican American individuals have been examined with more than 200,000 aliquots of biological specimens stored. Collectively, these studies are known as the Starr County Health Studies. The present Genetics of Diabetes Study has the goal of identifying loci/alleles that underlie susceptibility to type 2 diabetes in this high risk population using genome wide markers and association testing. The study makes use of two primary resources that have been developed in order to identify 1,000 type 2 diabetes cases and 1,000 disease free controls. In the first instance we have identified a subset of unrelated cases from the total cases that we have identified. Where multiply affected sibships were available, the youngest onset case with detailed phenotyping (including assessment of diabetic retinopathy) was selected. Controls came from a recent survey to establish a representative sample of the Starr County population. Blocks were randomly selected, households on selected blocks enumerated and one individual randomly selected from each household for a detailed examination. The examination included an oral glucose tolerance test. Those included as controls are those with no prior diagnosis of diabetes and a negative oral glucose tolerance test. This collection of cases and controls provides the opportunity to identify susceptibility loci for type 2 diabetes and its complications, specifically diabetic retinopathy and albuminuria. The data set also allows the examination of impaired fasting glucose and impaired glucose tolerance. The samples are split between those born in the United States and those born in Mexico and this gives a natural contrast for examining genotype and environmental interactions. It is anticipated that the understanding that will come will lead to strategies for delaying and preventing the onset of diabetes and its complications.

  Study phs000143

• Genome-Wide Association of Native and Post Aspirin Platelet Function Phenotypes

  The goal of this study was to identify genetic variants in a genome-wide association study (GWAS) that are associated with previously obtained platelet function phenotypes measured in each individual under baseline conditions and following 2 weeks of low dose aspirin (ASA). During this study we performed a high density 1 million-SNP genome scan on subjects from GeneSTAR (representing 800 2-generational families with a family history of premature coronary artery disease, 60% white and 40% African American, N=3232). We identified genomic loci associated with quantitative platelet phenotypes prioritized for their biological interest, determined associations between genomic loci and baseline platelet phenotypes (primary phenotypes are platelet aggregation in platelet rich plasma induced by collagen, adenosine diphosphate (ADP), arachidonic acid (AA), and epinephrine (Epi), determined associations between genomic loci and post-ASA platelet phenotypes, ie, measures of ASA "resistance" (primary phenotypes are as above, plus urinary levels of the prostaglandin metabolite, 11-dehydro-thromboxane B2 ), and compared peaks of association between genomic loci and three common baseline platelet phenotypes (collagen-, epinephrine-, and ADP-induced aggregation in platelet rich plasma) with associations found for these same phenotypes in the Framingham Heart Study. We also determined whether any significant genotype-phenotype associations in the 1 million SNP genome scan could be localized to any specific genes or potential genes of interest using publicly available databases and further examined whether candidate genes previously associated with a specific platelet phenotype are located in a genomic region of interest as determined from the SNP genome scan. We conducted replications of our findings, and are presently involved in larger scale meta-analysis of findings for pre-aspirin and post-aspirin associations. The study population is constituted of full siblings (SIBS) (ages 35-78 years) identified from The Johns Hopkins Sibling Study, now called GeneSTAR, the spouses of the SIBS, and their adult offspring (>21 years of age). They include 3200 individuals from approximately 300 African American and 500 white extended families. "Spouse" refers to the other parent of any SIB offspring, independent of marital status. Sibship sizes among families range from 1 to 16 (excluding index cases). On average, each SIB has 2 potentially eligible offspring. A family for this study is defined by all of the full sibships and the total numbers of offspring that come from all SIBS, rather than just the nuclear family.

  Study phs000375

• Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Dynamic approaches that integrate population-based research and molecular biology are needed to explain the mechanisms underlying pediatric rhabdomyosarcoma (RMS) and to determine novel prevention strategies. RMS, the most common soft-tissue sarcoma in children and adolescents, has one of the poorest 5-year survival rates among all pediatric cancers (less than 65%). One of the strongest risk factors for RMS is having a cancer predisposition syndrome. The syndromes that are most commonly seen among those with RMS are Li-Fraumeni, neurofibromatosis type 1, Costello, Noonan, and DICER1. Based on smaller clinic-based studies, only about 7% of RMS cases are thought to be associated with the genes responsible for these syndromes. However, there have been no population-based assessments to support this estimate. Even in the most recent large-scale evaluations of germline mutations in predisposition genes among children with cancer, very few RMS cases were included (43 cases). Furthermore, no distinctions were made between the major histologic subtypes of RMS: embryonal (eRMS) and alveolar (aRMS), which display differences in terms of age distribution, incidence, and cytogenetics. For instance, nearly 80% of alveolar cases are driven by a chromosomal translocation between either PAX3 or PAX7 and FOXO1, whereas these fusions are not seen in embryonal cases. In fact, RMS research is shifting from categorization based on histology to fusion status (eRMS is overwhelmingly fusion-negative). Another limitation in previous studies has been the inability to evaluate the frequency of de novo germline mutations (DNMs) in cancer predisposition genes due to the absence of any well-characterized cohorts of RMS case-parent trios. Therefore, a major gap in our understanding of the role of cancer predisposition in pediatric RMS that limit translational impact is there have been no population-based assessments to determine the true impact of these mutations on pediatric RMS, which limits clinical sequencing guidelines and surveillance protocols in these children.Overall Project Strategy: The objective of this project is to advance our understanding of the relationship between cancer predisposition genes and pediatric RMS. Our central hypotheses are: 1) mutations in cancer predisposition genes are more common than expected in children with RMS; and 2) children with fusion-negative tumors have a higher burden of germline mutations than those with fusion-positive tumors. The framework for this study relies on >600 well annotated samples collected from newly diagnosed RMS patients and stored in the Children’s Oncology Group (COG) Biopathology Center.

  Study phs002304

• De Novo Mutation Rates at the Single-Mutation Resolution in the Human Genome

  We developed a method to measure the origination rates of target mutations of choice and applied it to the HbS and nearby mutations in the human beta-globin (HBB) gene, as well as to the equivalent mutations in the nearly identical delta-globin (HBD) gene in sperm cells from African and European donors. Specifically, after extracting DNA from the sperm of the donors, each sample is enriched for the HbS mutation and nearby mutations by the restriction enzyme Bsu36I, which cleaves the wild-type (WT) sequence CCTGAGG at positions 16–22 of HBB and the homologous positions of HBD while leaving the HbS mutant and other mutants in these positions intact. Next, unique barcodes are attached to the DNA fragments from these Bsu36I-treated samples in order to reduce error by consensus sequencing of copies originating from the same original fragment. To determine how many target WT sequences have been removed (scanned) by Bsu36I digestion and hence to be able to calculate the de novo mutation rate, we run a second reaction in parallel for each donor. This reaction involves the same steps as the former reaction except for digestion by Bsu36I (Bsu36I-untreated). Spiking into the Bsu36I-treated and untreated samples known amounts of mock HBB-like DNA molecules that are fully resistant to Bsu36I digestion allows to calculate in the sequence analysis stage the Bsu36I-enrichment score based on the change in their frequency between the two treatments, which in turn is used to calculate the number of scanned WT sequences. Our results show significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than Europeans in the HBB region studied. Finally, the rate of the 20A>T mutation, called the “HbS mutation” when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations, and no instances were observed in the European HBB ROI or in the European or African HBD ROI.12 consented subjects; samples from two subjects were pooled

  Study phs002391

• Integrative Single-Cell Analysis of Transcriptome, Epigenome, and Lineage in HIV Latency and Activation

  With the development of triple combination antiretroviral therapy, routine HIV treatment eliminates nearly all actively infected cells. Nevertheless, the small reservoir of latently infected cells, which can remain dormant for long periods of time before becoming active and producing new virus particles, represents a crucial barrier to completely curing the disease. Identifying markers that identify latently infected cells or the biochemical factors that control latency activation could enable the effective use of a “shock and kill” strategy, where specific targeting or activation of latently infected cells eliminates the viral reservoir. Our recent work suggests that the global transcriptomic and epigenomic changes during hematopoietic differentiation affect viral latency and activation. Additionally, we recently found that global inhibition of histone deacetylase activity increases viral activation in these cells, further implicating epigenomic changes during activation. These results raise fundamental questions: What are the markers of latently infected cells? How do the transcriptomic and epigenomic states of a cell affect latency and activation? How does the differentiation state relate to viral latency? Here, we leverage our experimental platform for identifying latently and actively infected cells, single-cell transcriptome and epigenome sequencing, and our recently developed computational integration methods to investigate these questions. Our interdisciplinary team combines expertise in HIV basic science, HIV clinical treatment, and bioinformatics to develop an experimental and computational framework for integrated gene expression, chromatin accessibility, and lineage into a single picture of viral latency and activation. Specifically, this project will (1) use single-cell RNA-seq and single-cell ATAC-seq to map the diversity of infected cells, (2) investigate the relationship between hematopoietic differentiation state and viral activation, (3) determine viral integration sites through single-cell RNA-seq, (4) computationally integrate single-cell transcriptome and epigenome profiles, and (5) computationally infer cell lineage relationships among viral genomes and infected cells. To accomplish these goals, we will carry out the following aims: (1) Characterize lineage, transcriptomic and epigenomic diversity of single latently and actively infected primary cells. (2) Investigate latency and activation during in vitro differentiation. (3) Survey single cell diversity of re-activated and in vitro infected cells from cART-suppressed patients. Together, these aims will produce a comprehensive, integrated transcriptomic and epigenomic atlas of the HIV reservoir, identify DNA and RNA biomarkers of latency, and characterize clonal expansion patterns. Our work also develops a broadly applicable experimental and computational framework, laying a foundation for the discovery of novel insights into HIV latency and activation.

  Study phs002915

• Single-Cell Mitochondrial Mutation Lineage Tracing of Non-Dysplastic and Dysplastic Barrett's Esophagus

  This study addresses a critical knowledge gap in understanding Barrett's esophagus (BE), a common metaplastic condition and precursor to esophageal adenocarcinoma, by identifying lineage connections and cell states underlying its development and malignant transformation. We collected biopsies from 13 Barrett's esophagus patients undergoing routine surveillance endoscopy, sampling metaplastic tissue alongside normal squamous esophagus and gastric cardia tissues when clinically appropriate. Our novel approach integrated single-cell RNA sequencing of nearly 180,000 cells with mitochondrial DNA mutation analysis for lineage tracing, coupled with spatial transcriptomics and comprehensive whole-exome sequencing. For one patient with high-grade dysplasia, we performed detailed whole-exome sequencing analysis at 100x coverage on dissociated Barrett's esophagus cells alongside matched normal esophagus and gastric cardia tissues. This genomic profiling revealed critical genetic drivers of malignant transformation, including a truncating mutation in the mutation cluster region of APC (a negative WNT regulator), mutations in the tumor suppressor genes CDKN2A and TP53, and significant copy number alterations including loss of CDKN2A on chromosome 9. These genetic alterations corresponded with the transcriptional changes observed in our single-cell data, particularly WNT pathway dysregulation and the expansion of LGR5-expressing stem cells, providing molecular evidence for how single clones can initiate the dysplastic transformation. Data deposited in dbGaP consist specifically of the whole-exome sequencing raw files, processed variant calls, and copy number analyses from the single patient with high-grade dysplasia and matched normal esophagus and stomach control tissue. Whole exome sequencing was performed on an Illumina NovaSeq 6000. Sequencing data was preprocessed following the Genome Analysis Toolkit's (GATK) Best Practices. Sequencing data was analyzed with Mutect2 (GATK, v4.2.5.0) to identify short somatic mutations including single-nucleotide polymorphisms and insertions and deletions. The Barrett's esophagus sample was run with the two matched normals, as well as the publicly available germline resource somatic-hg38_af-only-gnomad.hg38.vcf.gz (GATK). Somatic variant calls were filtered using FilterMutectCalls (GATK) and loaded into the Integrative Genomics Viewer (v2.12.3) for identification of high-quality variants in known esophageal adenocarcinoma regulators. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9). CNV, Mutect2, and SVC analyses will be made available through dbGAP. Copy number alterations in the Barrett's esophagus sample were estimated using CNVkit (v0.9.9) with the default run settings; a pooled reference was generated from the normal esophagus and stomach samples. Copy number results were plotted directly within CNVkit using the function scatter.

  Study phs003949

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Dataset SNP tumours

  This dataset contains 30 idat files each from 15 SNP array runs on patient colitis-associated colorectal cancer tumours. All phenotypes are cancer. See Baker et al. 2018 Supplementary Table 2 for patient details of 12 tumours used in the analyses in the publication.

  Dataset EGAD00010001587

• SNPArray_Thai

  The compressed file contains plink format file for the Affymetrix Human Origins SNP array data of 452 individuals generated and analyzed in Kutanan, Liu et al 2021 study of 33 ethnolinguistic groups in Thailand and Laos.

  Dataset EGAD00010002285

• Small‑scale mutations are infrequent as mechanisms of resistance in post‑PARP inhibitor tumour samples in high grade serous ovarian cancer

  These are 28 targeted exome sequencing fastq files (tumour and germline) generated from ovarian cancer samples which had been exposed to PARP inhibitors, for the described project.

  Dataset EGAD50000000206

• CRC cell line ATAC-seq

  ATAC-Seq data for C32, CACO2, CL11, HT29, SW403, SW480, SW948 MSS CRC cell lines, and HCEC-1CT normal colon cell line

  Dataset EGAD50000000296

• NTNU Data Access Committee for “ProstOmics: spatial and bulk multi-omics of prostate cancer” datasets archived in Federated EGA Norway

  The ProstOmics project of NTNU contains spatial and bulk multi-omics datasets of prostate cancer, and access request to these datasets are handled by this Data Access Committee on behalf of NTNU.

  Dac EGAC50000000277

• CRC Patient-derived-organoids Whole Genome Sequencing

  Whole Genome Sequencing raw paired-ends reads for 20 matched colorectal patient-derived-organoids (normal and tumor). Tumor samples were obtained from patients treated at Niguarda Cancer Center, (Milano, Italy) and Candiolo Cancer Institute (Candiolo, Turin, Italy).

  Dataset EGAD50000000617

• Whole Genome - HAP-1 clones

  Whole genome sequencing on HAP-1 clones wild-type or knockout for MBD4 and/or TDG. Libraries were prepared using the Kapa HyperPrep kit (Roche, 07962363001). Paired-end libraries (2 x 100 bp) were sequenced on a NovaSeq 6000 instrument (Illumina).

  Dataset EGAD50000000765

• WES patients with colorectal polyposis

  Twenty-seven patients were included and subjected to germline WES using NovaSeq 6000 platform. After filtering out variants for sequencing quality, variant allele fraction frequency, and population frequency, variants were manually prioritized by the ACMG criteria.

  Dataset EGAD50000000842

• CRC organoid RNA-seq data access committee

  This DAC is responsible for granting access to RNA-seq data (paired-end FASTQ files) from 10 patient-derived colorectal cancer organoid patients. The data was ad hoc generated as part of the development of NovumRNA, a non-canonical tumor-specific antigen prediction pipeline.

  Dac EGAC50000000406

• PETAL trial Whole Exome Sequencing (WES)

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 224 Samples (162 Tumor + 62 Normal). WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000001172

• B cell single cell sequencing (RNA + VDJ) - Autoproliferation

  10X 3' (RNA) and 10X 5' (VDJ) samples of B cells (non-proliferating/hi and autoproliferating/Dim) for healthy donor and Multiple sclerosis patients used in the paper.

  Dataset EGAD50000001237

• WGS dataset for malignant pleural and peritoneal mesothelioma

  This dataset contains Whole Genome sequencing data of pleural and peritoneal mesothelioma. The number of samples is 40. Sequencing was performed on Illumina NovaSeq 6000 and Illumina NovaSeqXPlus. The sequencing was always paired.

  Dataset EGAD50000001343

• Dataset for scRNA glioblastoma samples

  This dataset contains 5 scRNA samples of human glioblastoma samples, human cortical spheroid derived from hiPSC line 028-4 and 3 samples of mouse xenografts. Sequencing has been performed on Illumina NovaSeq 6000. Sequencing has always been paired.

  Dataset EGAD50000001117

• TRACERx NSCLC - whole genome sequencing for ctDNA study

  Data used in "An ultra-sensitive and specific ctDNA assay provides novel pre-operative disease stratification in early stage lung adenocarcinoma"

  Dataset EGAD50000000452

• TRIGR collaboration between University of Helsinkin and Children's Mercy Research Institute

  DAC for collaborations between by the University of Helsinki and Children's Mercy Hospital, such as the Trial to Reduce IDDM in the Genetically at Risk (TRIGR), used to study the evolving epigenomics of immune cells in type 1 diabetes at single nuclei resolution

  Dac EGAC50000000543

• Boyes Lab - DAC policy

  Access to this data is controlled. Upon request from a third party for access to the data, a separate Data Sharing Agreement would be put in place between the University of Leeds and the third party prior to EGA granting access to the data to the third party.

  Dac EGAC50000000283

• BCR repertoir sequences from human buffy coat purified B-Cells with DIS3 and control ASO

  This dataset contains BCR sequences of buffy coat purified B-cells from 5 healthy donors. For each sample, sequences were obtained in two conditions : with control Aso and Dis Aso treatment.

  Dataset EGAD50000001601

• DAC Study assessing the efficacy and safety of durvalumab plus olaparib plus fulvestrant in selected metastatic or locally advanced ER-positive, HER2-negative breast cancer patients.

  DAC for Study assessing the efficacy and safety of durvalumab plus olaparib plus fulvestrant in selected metastatic or locally advanced ER-positive, HER2-negative breast cancer patients.

  Dac EGAC50000000694

• single cell RNA seq

  A selection of samples was analyzed using single-cell RNA sequencing to explore cellular heterogeneity. 4 inflammatory diseases were chosen for this purpose: Still’s disease, recurrent pericarditis, familial Mediterranean fever (FMF), and chronic non-bacterial osteomyelitis (CNO).

  Dataset EGAD50000002022

• SIA Subtyping Shallow Whole Genome Sequencing (sWGS)

  Associated with Molecular classification of small intestinal adenocarcinomas. Shallow Whole Genome Sequencing (sWGS) generated 214 .fastq files from 127 small intestine adenocarcinomas from 125 patients. DNA libraries for shallow whole genome sequencing were prepared using TruSeq Nano kits (Illumina).

  Dataset EGAD50000001760

• HOVON152 Trial Targetted Sequencing

  Associated with Molecular profiling of HGBCL-DH-BCL2 patients treated in the HOVON-152 triaL. Targeted sequencing of 30 samples from 30 High-grade B-cell lymphoma patients. Targeted sequencing was used for identify genomic alterations associated with patient outcome.

  Dataset EGAD50000002093

• Germline Pan-cancer Lynch syndrome sequencing dataset from India

  The dataset consists of germline whole exome sequencing data generated on the Illumina NovaSeq X Plus platform for 48 patients with MSI-high/ MMRd gastro-intestinal and genito-urinary cancers, in order to detect Lynch syndrome.

  Dataset EGAD50000002088

• T cell receptor repertoire in cell-free DNA as a proxy for tumor infiltrates in patients treated with pembrolizumab

  Bulk TCR sequences from tumor, peripheral blood mononuclear cell (PBMC), and cell-free DNA (cfDNA) samples from 81 patients with solid tumors treated with pembrolizumab.

  Dataset EGAD50000001857

• Department of Human Genetics at Yokohama City University (YCU) — Data Access Committee

  The Data Access Committee at Yokohama City University (Department of Human Genetics) is overseeing controlled access to data for our research manuscripts. Access is granted to bona fide researchers in line with the Data Access Agreement and DUO restrictions.

  Dac EGAC50000000770

• Pacbio_methylation_cases

  The PacBio cases dataset for differential methylation analysis included 10 case samples with known KMT2A loss-of-function variants, 2 VUS samples. All samples were sequenced using PacBio Revio® HiFi reads at a matched coverage of 15X, and methylation was called using pb-cpg-tools on aligned BAM files.

  Dataset EGAD00010002807

• 10x Genomics scRNA-seq for 3 samples

  This dataset contains 10x Genomics single-cell RNA-seq data from two primary leukemia samples and their corresponding patient-derived xenograft (PDX) models. All the 3 samples are in bam file type.

  Dataset EGAD50000001788

• RNA-seq for 8 samples

  This dataset contains RNA-seq data from 8 acute leukemia cases (diagnosis or relapse) belonging to a newly identified subtype, termed FOXF1/FENDRR ALL. All the 8 samples are in bam file type.

  Dataset EGAD50000001789

• ATAC-seq for 2 samples

  This dataset contains ATACseq data from ta primary sample and a patient derived model (PDX) of the novel FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001791

• sWGS of CRC patients

  Paired end (47/98) and single end (51/98) shallow whole genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of colorectal cancer (CRC) patients.

  Dataset EGAD00001006101

• Fibromyalgia versus small fiber neuropathy: Diverse keratinocyte transcriptome signature dataset

  We provide a diverse keratinocyte transcriptome signature between SFN and FMS patients, which may hint towards distinct pathomechanisms of small fiber sensitization and lay the basis for advanced diagnostics in both entities

  Dataset EGAD00001006918

• ICGC PCAWG Dataset: PAEN-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-AU.

  Dataset EGAD00001002154

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee

  Four iPSC line data were sequenced by WGS. One of them has gene MYBPC3 modified.

  Dataset EGAD00001005066

• 16S data from IBD patients

  Bacterial 16S V4 rDNA was amplified using two differently barcoded V4 fusion primers. Pooled PCR samples were purified and paired-end sequenced on MiSeq instrument for 250 cycles. The steps from DNA quantification to sequencing were conducted at Second Genome Inc.

  Dataset EGAD00001005482

• ICGC PCAWG Dataset: LICA-FR_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LICA-FR.

  Dataset EGAD00001002016

• WES and RNA-seq raw sequence data for HIFI project

  WES sequence data from 15 samples, RNA-seq sequence data from 19 samples, all sequence data are raw pair-end sequence data in fastq format, sequenced by Illumina platform.

  Dataset EGAD00001004799

• Bam files for a metastatic bladder cancer patient with BAP1 variants

  This dataset consists of three bam files (two cell-free DNA and one germline DNA) from a metastatic bladder cancer patient with BAP1 variants. Bam files were generated from targeted Illumina sequencing data.

  Dataset EGAD00001005520

• NKI-MET HNSCC RNA-Seq

  RNA-Seq data of 8 HNSCC specimens from patients diagnosed with metastatic disease at The Netherlands Cancer Institute, Amsterdam. Primary HNSCC biopsy samples obtained prior to treatment were used for polyA mRNA sequencing.

  Dataset EGAD00001005720

• DESIGN-VUMC RNA-seq

  RNA-Seq data of 55 HPV-negative HNSCC specimens from patients treated at the VU medical Centre, Amsterdam, The Netherlands. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005716

• DESIGN-MAASTRO RNA-seq

  RNA-Seq data of 17 HPV-negative HNSCC specimens from patients treated at the MAASTRO clinic, Maastricht, The Netherlands. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for polyA mRNA sequencing.

  Dataset EGAD00001005717

• DESIGN-NKI low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at The Netherlands Cancer Institute. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005718

• DESIGN-VUMC low coverage WGS

  Low-coverage whole genome sequencing data of 37 HPV-negative HNSCC specimens from patients treated at the VU Medical Centre, Amsterdam. HNSCC biopsy samples obtained prior to treatment (chemo-radiotherapy) were used for WGS to a depth of approx. 0.5X.

  Dataset EGAD00001005719

• Exome chip data 943 PDAC cases and 3,908 controls

  The illumina exome chip genotyping data for 943 PDAC cases and 3,908 controls in the Chinese population. Genotypes were called by the Illumina GenomeStudio software, and the selected variants were re-called by zCall. Standard quality control were performed.

  Dataset EGAD00001004168

• 133 CRC RNA-seq fastq

  This dataset contain 133 pairs of colorectal tumor and adjacent normal tissue. For each sample paired RNA-seq fastq were generated using an Illuma Myseq-2000. Those colorectal cancer comprise 101 MSI and 32 MSS tumors.

  Dataset EGAD00001006667

• Sequencing data for oesophageal samples - Killcoyne, Gregson et al (sWGS)

  Data supporting: "Genomic copy number predicts esophageal cancer years before transformation." Killcoyne, Gregson et al. sWGS data 1000 samples BAM files

  Dataset EGAD00001006033

• A96193B

  Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96193B 2410 samples; filetype=bam

  Dataset EGAD00001005347

• plasma dna fragmentations

  Data were generated by next-generation sequencing (Illumina) in a fastq format. This dataset involved sequencing data from pregnant women and patients with hepatocellular carcinoma (HCC). For HCC samples, the paired buffy coat and tumor DNA tissue samples were also sequenced.

  Dataset EGAD00001006054

• ICGC PCAWG Dataset: PACA-CA_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PACA-CA.

  Dataset EGAD00001003162

• ICGC PCAWG Dataset: BOCA-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BOCA-UK.

  Dataset EGAD00001002125

• ICGC PCAWG Dataset: MALY-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MALY-DE.

  Dataset EGAD00001002123

• Gut microbiota in prediabetes and diabetes

  Here, we profiled the gut microbiota in a discovery (n = 1,011) and validation (n = 484) cohort comprising Swedish subjects naive for diabetes treatment and grouped by glycemic status.

  Dataset EGAD00001006351

• SF11612 scRNA-Seq Recurrent oligodendroglioma

  Single Cell RNA seq from Recurrent oligodendroglioma sample. Gender Male Age 67. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005411

• Identification of drug resistance genes in melanoma by Exome Sequencing

  The cell lines in this study are a combination of internally sequenced (cosmic) and externally sequenced cell lines known to be “double-wild-type” (lacking BRAF and NRAS somatic mutations). These sequences were realigned in this data set for consistency.

  Dataset EGAD00001003260

• RNAseq - Colorectal organoids and tumoroids (2017-05-04)

  Transcriptome sequencing of tumour tissue, adjacent normal tissue and derived organoids/tumoroids from colorectal cancer This dataset contains all the data available for this study on 2017-05-04.

  Dataset EGAD00001003320

• RNA-Seq files for SJHGG study

  RNA-Seq files accompanying the paper titled "Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas".

  Dataset EGAD00001003905

• NKI-AvL CRC-OVC DNA-seq

  The dataset “NKI-AvL CRC-OVC DNA-seq" includes 4 normal and 4 tumor BAM files from paired-end whole exome sequencing on Illumina HiSeq2500 and Illumina NovaSeq6000 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004340

• Prognostic factors in prostate cancer: deep sequencing pilot project TAPG

  This is a pilot project to determine whether the TAPG FFPE DNA's are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.

  Dataset EGAD00001001237

• Integrative genomic study of CML patients

  This dataset contains WES and RNA-Seq fastq files for 65 CML patient samples at various stages of disease progression.

  Dataset EGAD00001004179

• eccDNA in maternal plasma

  We developed a new bioinformatics method for detecting the eccDNA in plasma. We revealed that the biological properties between eccDNA and linear DNA are different. eccDNA could be potentially provided as a new class of circulating biomarker.

  Dataset EGAD00001005286

• Martin_Ravenscroft-AUS1

  Whole genome sequencing data on D19-0702 (AUS1), presented in Martin et al. 2020 (AUS1). WGS (Illumina HiSeq) was performed at Kinghorn Centre for Clinical Genetics, Garvan Institute of Medical Research. Data was analyzed using the Seave bioinformatic analysis pipeline (https://www.seave.bio).

  Dataset EGAD00001006276

• RNA-seq of multi-regional CRC samples

  BAM files of RNA sequencing (RNA-seq) experiment on multi-regional colorectal cancer (CRC) samples. 58 samples corresponding to 16 patients were sequenced and there is one BAM file for each sample.

  Dataset EGAD00001006164

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: CLLE-ES.

  Dataset EGAD00001002130

• ICGC PCAWG Dataset: RECA-EU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: RECA-EU.

  Dataset EGAD00001002131

• ICGC PCAWG Dataset: PBCA-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PBCA-DE.

  Dataset EGAD00001002127