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• Single cell atlas of human glioma

  We profiled 87 primary-recurrentpatient-matched paired GBM specimens with single-nucleus RNA and bulk-DNA sequencing and single-cell open-chromatin and spatial transcriptomics/proteomics assays. We found that recurrent GBMs are characterized by a shift to a mesenchymal phenotype in response to therapy

  Dataset EGAD00001008811

• Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer

  RNA sequencing data from breast cancers (n=18) and their matched HN tissues (n=36), healthy breast from cosmetic reduction mammoplasty (RM; n=5), and risk reducing mastectomies (RR, n=5), with peritumoral samples excised proximal to (TP, less than 2 cm) and distal from (TD, 5-10 cm) the primary tumor.

  Dataset EGAD00001006291

• Deep sequencing of 60 genes from BCP HD ALL samples on Illumina HiSeq 2000, 100 bp paired-end

  50 ng of genomic double stranded DNA was enzymatically sheared to an average size of 200 bp. Further processing was performed using Illumina Nextera Rapid Capture Custom Kit (Illumina) and 100 bp paired-end sequencing was performed with 24 samples per lane on a Illumina HiSeq 2000 (Illumina) to reach a coverage of 100-1000x.

  Dataset EGAD00001002652

• Healthy Never Smokers

  Bronchial brushing dataset from healthy never-smokers after exposure to diesel exhaust. Include 18 samples from 9 research participants who underwent bronchoscopy after controlled exposure to diesel exhaust. Main study design described in detail in Ryu et al 2022 AJRCCM (PMID: 35202552). This dataset was used in Hill et al Nature 2023.

  Dataset EGAD00001010024

• PacBio Rare Disease Study

  This study leverages PacBio HiFi long-read sequencing technology to comprehensively analyze the genomic architecture of rare diseases. By generating highly accurate, long-read sequences, we aim to resolve complex structural variants, repeat expansions, and other genomic features that are often missed by short-read sequencing. Our approach facilitates improved variant detection and interpretation, advancing the understanding of rare disease etiology and enabling more precise genetic diagnoses.

  Dataset EGAD00001015611

• Whole genome sequencing of adult glioblastoma nuclei

  Three primary adult glioblastoma specimens were dissociated and nuclei were extracted. A portion of the nuclei was used for single-cell ATAC seq and the remainder were submitted for whole genome sequencing, to provide orthogonal validation of copy number variations in the samples compared to single-cell ATAC seq. Samples were sequenced on the Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD00001007651

• Acute myeloid leukemia bulk RNA-seq (Diagnosis and Relapse)

  To gain insight into the clonal heterogeneity of diagnosis (Dx) and relapse (Re) pairs, we employed RNA-seq to longitudinally profile two t(8;21) (AML1-ETO = RUNX1-RUNX1T1), and four FLT3-ITD AML cases. All the samples are bone marrow aspirates.

  Dataset EGAD00001008374

• scRNA-seq dataset to study interactions between HSPCs, BMSCs and immune microenvironment

  Mechanisms of clonal evolution in myeloid neoplasms remain incompletely understood. Darwinian theory predicts that the (micro)environment of clone-propagating stem cells may contribute to clonal selection. Here, we provide data fitting this model, establishing a relationship between stromal niche inflammation, inflammatory stress in HSPCs, clonal resistance and leukemic evolution in human MDS.

  Dataset EGAD00001015770

• Bulk RNA sequencing data in "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2"

  This dataset includes 14 bulk RNA sequencing data (28 fastq files) in the study entitled "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2". RNA sequencing library was generated with Truseq stranded total RNA Gold kit.

  Dataset EGAD00001006241

• Ultra-fast deep-learned pediatric CNS tumor classification.

  In this study nanopore sequencing was applied to obtain sparse DNA methylation profiles from pediatric CNS tumor samples. A neural network was used to classify the tumor based on the obtained methylation profile.

  Dataset EGAD00001011303

• WES in pleural mesothelioma primary cell lines

  We performed exome sequencing on the largest cohort of patient-derived pleural mesothelioma (PM) cell lines (n=58) to explore their molecular heterogeneity. The analysis recapitulated key features of PM tumors and uncovered novel mutations specific to this cohort. These findings provide insight into the genetic landscape of PM, supporting the identification of potential therapeutic targets and advancing the understanding of its molecular diversity.

  Dataset EGAD00001015409

• PROP1_study

  The dataset for the PROP1 study consists of samples of patients with combined pituitary hormone deficiency due to two most prevalent mutations in the PROP1 gene (c.301_302delGA and c.150delA) and healthy relatives and controls. All subjects were genotyped for 21 single nucleotide polymorphisms surrounding the PROP1 gene in order to assess the potential ancestral origin of the respective mutations. The genotype data are displayed in the vcf format.

  Dataset EGAD00001001303

• Somatic mutations in 106 small intestine adenocarcinoma

  106 FFPE tumor samples from small bowel were sequenced with Illumina HiSeq 4000. Exome capture was performed with NimbleGen SeqCap EZ Exome Library v3 Kit. Reads were aligned with BWA–MEM v.0.7.12 to GRCh37 reference genome. Variant calls were produced with GATK HaplotypeCaller. Variant calls were filtered against all data from gnomAD database using allele frequency threshold 0.0001 in order to remove germline variation.

  Dataset EGAD00001003802

• Clinical Phenotypes

  Complete clinical phenotypic description of all patients; the number listed represents all the samples linked to the 609 patients present in the dataset. Please consult the key file to visualise the sample-patient relationship

  Dataset EGAD00001003991

• Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer

  We set out to determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy. We collected and sequenced 77 plasma cell-free DNA samples from 53 newly diagnosed patients with mCSPC. Targeted sequencing was also performed on DNA from 48 diagnostic prostate tissue samples.

  Dataset EGAD00001004526

• exome sequence of female patients suffering from Ovarian Meiotic Defects

  Exome sequencing was performed on 15 unrelated female patients suffering from primary infertility due to Ovarian Meiotic Defects (OMD). Each reference number corresponds to one of the tested subject. DNA was extracted from Saliva using Oragene saliva DNA collection kit (DNAgenotek Inc., Ottawa, Canada).Exome capture was performed with the Agilent V5 kit and sequencing was performed on Illumina HiSeq 2000.

  Dataset EGAD00001004035

• The contribution of POT1 variants to sporadic melanoma development (2018-06-06)

  A case-control series of melanoma cases from Leeds, UK have been sequenced in the Fluidigm platform to identify genetic variants associated with sporadic melanoma development. Samples in which potentially contributing variants have been detected are being sequenced in an orthogonal platform for variant confirmation. . This dataset contains all the data available for this study on 2018-06-06.

  Dataset EGAD00001004151

• Whole-genome sequencing of paired tumor and blood samples from 65 bladder cancer patients

  65 paired tumor and normal whole-genome sequencing samples from urothelial bladder carcinomas (UBC, the most common type of bladder cancer) are used to uncover the whole-genome mutational landscape of UBC. Recurrent mutations in noncoding regions affecting gene regulatory elements and structural variations leading to gene disruptions are prevalent in this type of cancer.

  Dataset EGAD00001004545

• Relationship between low LDL cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: a US-based cross-sectional observational study using electronic medical records

  Lipid lowering therapy using HMG-CoA reductase inhibitors (statins) is associated with an approximately 9-12% increase in the risk of new-onset type 2 diabetes (T2DM). The risk of diabetes could be increased by statins directly; however, genetic approaches have also implicated low LDL cholesterol (LDL-C) concentrations as a risk factor for T2DM. Mendelian randomization studies using functional variants in both HMGCR (GeneID:3156) and PCSK9 (GeneID:255738) genes found a higher risk of T2DM in individuals with variants associated with lower LDL-C concentrations. Since PCSK9 and HMGCR are involved in lipid metabolism through distinct molecular pathways, the altered glycemic effect associated with variants in both genes is likely to be the result of their common effect on LDL-C concentrations. Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations with increased risk of T2DM. Individuals who have very low LDL-C concentrations not due to lipid lowering therapy can provide insights into the relationship between low LDL-C concentrations and T2DM. Here, we used de-identified electronic health records (EHRs) to test the hypothesis that low LDL-C concentrations are associated with T2DM.

  Study phs001588

• Stereotyped B-cell responses are linked to IgG constant region polymorphisms in multiple sclerosis

  Clonally related B cells infiltrate the brain, meninges, and cerebrospinal fluid of multiple sclerosis (MS) patients, but the mechanisms driving the B-cell response and shaping the immunoglobulin repertoires remain unclear. Here, we used single-cell full-length RNA-seq and B-cell receptor reconstruction to simultaneously assess the phenotypes, isotypes, constant region polymorphisms, and the paired heavy- and light-chain repertoires in intrathecal B cells. We detected extensive clonal connections between the memory B cell and antibody-secreting cell compartments and observed clonally related cells of different isotypes, including IgM/IgG1, IgG1/IgA1, IgG1/IgG2, and IgM/IgA1. There was a strong dominance of the G1m1 allotype constant region polymorphisms in antibody-secreting cells, but not in memory B cells. Tightly linked to the G1m1 allotype, we found a preferential pairing of the immunoglobulin heavy-chain variable (IGHV)4 gene family with the κ variable (IGKV)1 gene family. The IGHV4-39 gene was most used and showed the highest frequency of pairing with IGKV1-5 and IGKV1(D)-33. These results link IgG constant region polymorphisms to stereotyped B-cell responses in MS and indicate that the intrathecal B-cell response in these patients could be directed against structurally similar epitopes.

  Study EGAS00001005745

• Sex chromosome aneuploidies give rise to changes in the circular RNA profile

  Purpose The landscape of circular RNAs (circRNAs), an important class of non-coding RNAs that regulate gene expression, has never been described in human disorders of sex chromosome aneuploidies. We profiled circRNAs in Turner syndrome females (45,X;TS) and Klinefelter syndrome males (47,XXY; KS) to investigate how circRNAs respond to a missing or an extra X chromosome. Methods 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. CircRNAs were identified using a combination of circRNA identification pipelines (CIRI2, CIRCexplorer2 and circRNA_finder). Results Differential expression of circRNAs was observed throughout the genome in TS and KS, in all tissues. The host-genes from which several of these circRNAs were derived, were associated with known phenotypic traits. Furthermore, several differentially expressed circRNAs had the potential to capture micro RNAs that targeted protein-coding genes with altered expression in TS and KS. Conclusion Sex chromosome aneuploidies introduce pervasive changes in the circRNA transcriptome, demonstrating that the genomic changes in these syndromes are more complex than hitherto thought. CircRNAs may help explain some of the genomic and phenotypic traits observed in these syndromes.

  Study EGAS00001006404

• PSCP_mutation analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shred by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002231

• PSCP_bisulphite analysis in hESCs

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002235

• Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis

  This dataset contains raw sequencing files associated with the paper "Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis" (https://doi.org/10.1038/s41590-023-01490-5). It is composed of two experiments, which are as follows: 1. Single-cell profiling of whole blood leukocytes: This experiment comprises sequencing files generated using the BD Rhapsody single-cell multi-omics profiling (RNA + protein) platform. This platform was used to profile the whole blood leukocyte population in a cohort of sepsis patients, cardiac surgery controls and healthy controls. There are 48 samples and four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the protein profiling (ADT-based AbSeq) library. 2. Single-cell profiling of circulating HSPCs: This experiment comprises sequencing files generated using the 10X single-cell multi-omics (RNA-seq + ATAC-seq) profiling platform. This platform was used to profile circulating HSPCs in a cohort of sepsis patients and healthy controls. There are 5 samples (or plexes), each of which consists of a pool of individuals for whom cells were multiplexed and sequenced as a single sample. There are four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the ATAC-seq library. Because these samples consists of multiplexed pools, index files are also provided. These can be used for sample deconvolution using the Cell Ranger pipeline. NOTE: Due to EGA's constrains in the number of files permitted per sample, index files (I1 and I2) for the HSPC data set are provided as a separate experiment named "FASTQ index files (I1 and I2) for deconvolution of 10X single-cell multiomics libraries".

  Dataset EGAD00001010927

• PSCP_bisulphite analysis in hESCs (2018-08-13)

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-08-13.

  Dataset EGAD00001004295