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• Comparison of 3 protocols for deriving pancreatic progenitors from hPSC with RNA-seq and ATAC-seq

  Several distinct differentiation protocols for deriving pancreatic progenitors (PP) from human pluripotent stem cells have been described but it remains to be shown how similar the PP are across protocols, and how well they resemble their in vivo counterparts. Here we evaluated three differentiation protocols; performed RNA and ATAC-seq on isolated PP derived with these, and compared them to fetal human pancreas populations. This enabled us to define a shared transcriptional and epigenomic signature of the PP, including several genes not previously implicated in pancreas development. Furthermore, we identified a significant and previously unappreciated cross-protocol variation of the PP through multi-omics analysis and demonstrate how such information can be applied to refine differentiation protocols for derivation of insulin-producing beta-like cells. Together, our study highlights the importance of a detailed characterization of defined cell populations derived from distinct differentiation protocols, and provides a valuable resource for exploring human pancreatic development.

  Study EGAS00001003513

• Multicenter AIDS Cohort Study (MACS)

  The Multicenter AIDS Cohort Study (MACS) - now part of the MACS-WIHS Combined Cohort Study (MWCCS) investigates the epidemiology of human immunodeficiency virus (HIV) infection among men who have sex with men. Over 7,000 participants volunteered for semiannual interview, physical examination, and laboratory testing across the 325 years of the study, in four metropolitan areas of Los Angeles, Chicago, Baltimore/Washington (DC) and Pittsburgh. The study aimed to identify risk factors for occurrence and clinical expression of the HIV infection, and to establish a repository of biologic specimens for future study. Study visits included detailed questions covering HIV-related symptoms and utilization of health services, demographic and psychosocial characteristics, a quality of life survey, a physical examination, a detailed form on medications used as prophylaxis and/or treatment, a neuropsychological screening and examination, blood samples to do measure hematologic variables including enumeration of T-cell subsets and HIV viral load and evaluate genetic risk factors via genome wide association studies using data generated using the Infinium Multi-Ethnic Global BeadChip genotyping array in all participants. Men who have sex with men, with and without HIV infection were enrolled in the MACS. MACS data continues to be available through the merged MWCCS cohort.

  Study phs002226

• Kinomics data

  To ellucidate protein activity in mRCC, Kinomics data was generated as part of the EuroTarget study

  Dataset EGAD50000002293

• Belgian epilepsy patients

  The genomic sequence of brain expressed miRNA genes was sequenced in Belgian epilepsy patients.

  Dataset EGAD00001001851

• Swedish schizophrenia patients

  The genomic sequence of brain expressed miRNA genes was sequenced in Swedish schizophrenia patients

  Dataset EGAD00001001849

• Indonesian Genome Diversity Project 2

  High-coverage whole genome sequences were collected to study patterns of genomic variation across the broad geography of Indonesia and New Guinea. This region has experienced an extremely complex demographic history, including repeated bouts of admixture with archaic and modern human groups. This dataset reports whole genome sequences for 82 individuals from different populations from Mentawai, New Guinea, Sumatra and Sumba islands. Particular attention has been paid in the original study to genomic signals that are informative for population history, including admixture with archaic hominins and the role of modern human admixture during the late Pleistocene and Holocene.

  Study EGAS00001003654

• Somatic mutations, clonal architecture and genomic evolution in multiple myeloma

  Multiple myeloma is an incurable plasma cell malignancy whose molecular pathogenesis is incompletely understood. We used whole exome sequencing, copy number profiling and cytogenetic to analyses 84 samples from 67 patients with myeloma. In addition to known myeloma genes, we identify new candidate genes, including truncations of SP140, ROBO1 and FAT3 and clustered missense mutations in EGR1. We find oncogenic mutations in cancer genes not previously implicated in myeloma, including SF3B1, PI3KCA and PTEN. We define diverse processes contributing to the mutational repertoire, including kataegis and somatic hypermutation. Most cases have at least one cluster of subclonal variants, including subclonal driver mutations, implying on-going tumor evolution. Serial samples revealed diverse patterns of clonal evolution, including linear evolution, differential clonal response and branching evolution. Our findings reveal the myeloma genome to be heterogeneous across patients and, within individual patients, to exhibit diversity in clonal admixture and dynamics in response to therapy.

  Dataset EGAD00001000339

• Spatial Transcriptomics of Pulmonary Vascular Remodelling in IPAH

  In compliance with the research ethics and governance under which these data and samples have been collected, the transcriptomic data are available through restricted access for approved researchers who agree to the conditions of use, i.e. keeping it secure and only using it for approved purposes. To apply for access please contact either a.lawrie@imperial.ac.uk, m.keles@imperial.ac.uk, b.wojciak-stothard@imperial.ac.uk.

  Dac EGAC50000001023

• Dataset for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancew

  The dataset for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer includes 169 bam files from targeted deep sequencing on the Illumina HiSeq2500. The samples analyzed include genomic DNA from white blood cells and cell-free DNA from longitudinal blood collections of patients with gastric cancer.

  Dataset EGAD00001005750

• RNAseq of blood, fat and muscle samples from 45,X, 46,XX, 46,XY and 47,XXY

  Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. The RNA-seq libraries were multiplexed paired-end sequenced on an Illumina Novaseq 6000 (100 bp) and subjected to initial quality control using FastQC (BAbraham Bioinformatics). In addition to trimming of low-quality ends, adaptor removal was conducted using Trim Galore with default settings (BAbraham Bioinformatics).

  Dataset EGAD00001010052

• Unifying recovery dynamics in heterogeneous diseases exemplified by COVID-19

  Studying the recovery dynamics in different diseases poses many difficulties, as patients often display high heterogeneity in their recovery courses. Moreover, most attempts to study disease dynamics focus on disease progression rather than disease recovery mechanisms. To model recovery dynamics, using severe COVID-19 as the example, we align heterogeneous recovery trajectories via a novel computational scheme applied to longitudinally sampled blood transcriptomes. We thus generate pseudotime trajectories, which we then link to cellular and molecular mechanisms based on cell deconvolution analysis and molecular pathway prediction, thus presenting a unique framework for studying recovery processes over time. Specifically, mature neutrophils displayed a gradual decrease during recovery, allowing superior useability for outcome prediction compared to currently used clinical markers. Further, we discovered a recovery-related regulatory change in gene programs resulting in immune rebalancing between interferon and NFkB activity and the restoration of cell homeostasis. We thus propose regulatory mechanisms governing COVID-19 recovery and suggest mature neutrophils and additional gene markers, as novel clinical biomarkers for disease outcome. Overall, we present a novel clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

  Study EGAS00001005735

• International Multi-Center ADHD Gene Project (IMAGE) II Case Sample

  This sample represents a collection of cases across a range of sites. All of these samples were ascertained for ADHD with most meeting criteria for combined type ADHD. The collection sites span Europe and America. Further details on the source and inclusion and exclusion information can be found in Neale et al. "Case-Control Genome-Wide Association of Attention-Deficit / Hyperactivity Disorder" J Am Acad Child Adolesc Psychiatry. 2010 September; 49(9): 906-920 PMID20732627. For online access to this manuscript see: PMC2928577.

  Study phs000407

• An Unusual Genomic Variant of Pancreatic Ductal Adenocarcinoma with an Indolent Clinical Course

  We describe a patient with biopsy-proven locally advanced pancreatic ductal adenocarcinoma (PDA) who underwent a modified course of gemcitabine and stereotactic body radiation therapy. Whole exome sequencing of this patient's tumor revealed a simple genome landscape with no evidence of mutations, copy number changes, or structural alterations in genes most commonly associated with PDA, i.e. KRAS, CDKN2A, TP53 or SMAD4. An analysis of germline DNA revealed no pathogenic variants of significance. Whole exome and whole genome sequencing identified a somatic mutation of RNF213 and an inversion/deletion of CTNNA2 as the genetic basis of this PDA. Although PDA is classically characterized by a predictable set of mutations, these data suggest that alternate genetic paths to PDA may exist, which can be associated with a more indolent clinical course.

  Study EGAS00001002192

• T-ALL RNA-Seq raw data files

  Bone marrow or peripheral blood samples were collected of adult patients at first diagnosis of T-precursor acute lymphoblastic leukemia. RNA was isolated from mononuclear cells and subjected to mRNA library prep using Poly-A selection and sequencing on a NovaSeq 6000 system. Obtained gene expression profiles and gene fusion calls were used to allocate samples to molecular disease subtypes.

  Study EGAS50000000213

• Adult B-precursor acute lymphoblastic leukemia transcriptomes

  Bone marrow or peripheral blood samples were collected of adult patients at first diagnosis of B-precursor acute lymphoblastic leukemia. RNA was isolated from mononuclear cells and subjected to mRNA library prep using Poly-A selection and sequencing on a NovaSeq 6000 system. Obtained gene expression profiles and gene fusion calls were used to allocate samples to molecular disease subtypes.

  Study EGAS00001006107

• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Study EGAS00001004689

• WTCCC case-control study for Rheumatoid Arthritis

  WTCCC genome-wide case-control association study for Rheumatoid Arthritis (RA) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000011

• WTCCC case-control study for Type 1 Diabetes

  WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000014

• WTCCC case-control study for Type 2 Diabetes

  WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000016

• WTCCC case-control study for Coronary Artery Disease

  WTCCC genome-wide case-control association study for Bipolar disorder (CAD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000003

• Professors Colin Palmer and Ewan Pearson, from University of Dundee, are both members of the Access Group panel for the GoDARTS bioresource, which provided the data for the current study. The current Study used genotypes (EGAD00010000282) generated by the WTCCC2 (EGAS00000000121), on which both Colin and Ewan are also DAC panel members.

  Dac EGAC00001000504

• The mutational characterization of adenoid cystic carcinoma

  Adenoid cystic carcinoma (ACC) typically emanate from the major and minor salivary glands of the head and neck. ACCs have high rates of perineural invasion, locoregional recurrence, and distant metastasis. Here we report sequencing of 60 tumor/normal pairs and find substantial mutational diversity. On pathway analysis, a significant percentage of mutations involved chromatin remodeling, DNA damage, protein kinase A signaling, and FGF/IGF/PI3K signaling. Whole genome sequencing and FISH confirmed the MYB-NFIB translocation as the main structural variant in ACC. Evaluation of potential driver mutations KDM6A and PIK3CA reveal that specific, observed alterations impart functional consequences. Collectively, our data delineate the ACC mutational landscape and establish a molecular foundation for investigating new therapies for this disease.

  Study phs000612

• There are 66 pairs of LAML cases(complete genomics) in this project which belongs to LAML-CN.The library is constructed by the Completes Genomics protocol.

  There are 66 pairs of LAML cases(complete genomics) in this project which belongs to LAML-CN..The library is constructed by the Completes Genomics protocol.

  Dataset EGAD00001003310

• There are 22 pairs of LAML cases in this project which belongs to LAML-CN. The library is constructed by the Illumina protocol.

  There are 22 pairs of LAML cases in this project which belongs to LAML-CN.The library is constructed by the Illumina protocol.

  Dataset EGAD00001003317

• Sequencing data from MethylScan assay on plasma

  Machine learning models in biomedical research are often hindered by demographic imbalances in clinical datasets, leading to biased predictions that disadvantage minority populations. Existing bias correction methods face limitations in handling the heterogeneity of biomedical data and the complexity of demographic influences. Here, we present DeBias, a computational framework for mitigating demographic biases in high-dimensional biomedical datasets. DeBias eliminates bias-associated subspaces within the entire feature space using control samples and enables global bias correction across all features, effectively preserving disease-specific signals while minimizing demographic distortions. To demonstrate its effectiveness, we applied DeBias to cfDNA methylation data for cancer detection. It achieved a >6-fold reduction in the number of features containing biases and outperformed existing methods in improving the cancer detection performance for minority populations. Our method represented a promising step toward developing machine learning models that are more accurate, reliable, and equitable for minority populations.

  Study EGAS00001008127