Search Results - EGA European Genome-Phenome Archive

High hyperdiploid ALL single cell whole genome sequencing

This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15).

Dataset EGAD00001008988

Bone marrow microenvironment of 6 newly diagnosed myeloma patients using 10X Genomics scRNA- and TCR-sequencing

10X Genomics scRNA- and TCR-sequencing (Chromium Next GEM Single Cell 5’ Reagent Kit v1.1) was performed on the plasma cell depleted mononuclear fraction of bone marrow aspirates from 6 patients with newly diagnosed multiple myeloma. Generated gene expression libraries were paired-end sequenced on the NovaSeq 6000 S2. Generated V(D)J libraries were paired-end sequenced on the NextSeq 550.

Dataset EGAD00001009270

Whole exome sequencing of sequential samples from a CLL patient over the course of venetoclax treatment, BCR inhibitor treatment, and venetoclax re-treatment

The dataset contains whole exome sequencing data (libraries prepared using the Agilent SureSelect Human All Exon V6 kit, and paired-end sequenced on Illumina HiSeq4000 (2 x 150bp)) of 6 samples taken from peripheral blood mononuclear cells (PBMCs) (Samples 1-5) and bone marrow (BM). Data are provided as fastq files. Sample 1 was taken prior to initial venetoclax treatment. Sample 2 was taken as disease progression on venetoclax. Sample 3 was taken during response to BTK and PI3K inhibitor therapy. Sample 4 and the BM sample were taken at disease progression/prior to venetoclax re-treatment. And Sample 5 was taken during venetoclax re-treatment response.

Dataset EGAD00001008685

sWGS of OV04 patient samples for ACN rascal study

This dataset contains 142 .bam files of shallow WGS data (~0.1X) from OV04 patient samples. Sequencing reads were aligned to the 1000 Genomes Project GRCh37-derived reference genome using the BWA aligner (v.0.07.17; CRUK-CI alignment pipeline).

Dataset EGAD00001008121

Warm_autopsy__mutational_signatures_and_clonal_units

Aims and objectives 1. To produce a ‘first generation map’ of mutational burdens and mutational processes that operate in normal human tissues. 2. To examine clonal units and their distribution across normal human tissues with the emphasis on these particular areas: a) Tissues with an architecturally defined unit: Are architectural structures populated by a progeny derived from a single stem cell? Are clonal units confined to a given architectural structure? Examples of tissues where such approach will be used include prostate gland (acini and ducts), small bowel (crypts), thyroid gland (follicles) and others. b) Tissues without an architecturally defined unit: What is the average size of clonal populations? This group includes stratified/pseudostratified epithelia with a basal layer within which there are stem cells that give rise to a progeny of cells showing upwards migration and lateral expansion (e.g. urothelium, cervical squamous epithelium, respiratory epithelium). This approach can also be used in tissues with a sheet-like cell arrangement, for example brain and adrenal gland. Methods To answer these questions, we will use a range of normal human tissue samples which have already been collected from a single deceased individual. The samples are currently stored in a -80C freezer. Ethanol fixed frozen sections will be prepared from these biopsies. Putative clonal units will be identified and dissected out using laser capture microscopy. DNA extraction will be performed using the in-house (CGP) protease based method. In terms of sequencing methods, the project will be split into 2 phases (2 different approaches): - Phase 1: This part of the project will utilise a combination of low input library preparation (developed by Peter Ellis) and standard whole genome sequencing (HiSeqX). The phase has already started (December 2016). This approach will be particularly useful in investigation of mitotically active tissues. - Phase 2: This part of the project will utilise a combination of low input library method (Peter Ellis) and Bottle-neck sequencing (BotSeqS). BotSeqS is a type of duplex sequencing method that offers a more accurate variant calling and allows genome interrogation at a single cell level. This method is currently being developed and is expected to be implemented in 3-6 months (March-April 2017). This approach will be particularly useful for post-mitotic tissues and tissues without pre-defined architectural units.

Study EGAS00001002216

Mayo-Perlegen LEAPS (Linked Efforts to Accelerate Parkinson's Solutions) Collaboration

We performed a two-tiered, whole-genome association study of Parkinson disease (PD). For tier 1, we individually genotyped 198,345 uniformly spaced and informative single-nucleotide polymorphisms (SNPs) in 443 sibling pairs discordant for PD. For tier 2a, we individually genotyped 1,793 PD-associated SNPs (P<.01 in tier 1) and 300 genomic control SNPs in 332 matched case-unrelated control pairs. We identified 11 SNPs that were associated with PD (P<.01) in both tier 1 and tier 2 samples and had the same direction of effect. For these SNPs, we combined data from the case-unaffected sibling pair (tier 1) and case-unrelated control pair (tier 2) samples and employed a liberalization of the sibling transmission/disequilibrium test to calculate odds ratios, 95% confidence intervals, and P values. A SNP within the semaphorin 5A gene (SEMA5A) had the lowest combined P value (P=7.62E-6). The protein encoded by this gene plays an important role in neurogenesis and in neuronal apoptosis, which is consistent with existing hypotheses regarding PD pathogenesis. A second SNP tagged the PARK11 late-onset PD susceptibility locus (P=1.70E-5). In tier 2b, we also selected for genotyping additional SNPs that were borderline significant (P<.05) in tier 1 but that tested a priori biological and genetic hypotheses regarding susceptibility to PD (n=941 SNPs). In analysis of the combined tier 1 and tier 2b data, the two SNPs with the lowest P values (P=9.07E-6; P=2.96E-5) tagged the PARK10 late-onset PD susceptibility locus. Independent replication across populations will clarify the role of the genomic loci tagged by these SNPs in conferring PD susceptibility. Note: The following instruments were used: 1)clinical assessments form and manual; 2) sibling screening form and manual; 3) unrelated control screening and manual; and 4) risk factors questionnaire and manual. All cases underwent #1, as did sibling controls screening positive (see below). Unrelated controls were not examined. All siblings underwent #2. All unrelated controls underwent #3. All subjects (cases, sibling controls, and unrelated controls) underwent #4. Any publications using the data are to cite the original American Journal of Human Genetics article (Maraganore et al., 2005). Investigators using the data collection instruments are to acknowledge Drs. Maraganore and Rocca, and cite grants ES-10751 and NS-33978.

Study phs000048

Type 1 Diabetes Genetics Consortium (T1DGC): Multi-Ethnic ImmunoChip Study

Type 1 diabetes (T1D) is characterized by an autoimmune attack that destroys the insulin-producing pancreatic beta cells and is driven by diverse genetic and environmental factors. Between 8-100 chromosome regions are known to contain variants that alter T1D risk, substantially fewer than many other common diseases. Less is known about the contribution of T1D risk alleles in non-European populations, despite recent increases in T1D diagnoses in multiple non-European ancestry groups. To address these gaps in T1D genetics, we doubled the sample size from the previous largest T1D association study, genotyped ancestrally diverse T1D cases, controls, and affected families with the Illumina ImmunoChip array, and imputed additional variants using a large haplotype reference panel. After quality filtering, a total of 61,427 participants and 140,333 genotyped ImmunoChip variants were included in analysis, providing dense coverage in 188 autosomal regions ("ImmunoChip regions") and sparse genotyping in other regions of the genome. Each participant was assigned to one of five ancestry groups using k-means clustering of ImmunoChip genotype principal components: European (EUR, N = 47,319), African Admixed (AFR, N = 4,290), Finnish (FIN, N = 6,991), East Asian (EAS, N = 588) and Other Admixed (AMR, N = 2,239). In total, 16,159 T1D cases, 25,386 controls (unrelated) and 6,143 trio families (i.e., an affected child and both parents) were genotyped and included in association analyses. Imputation with the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) multi-ethnic reference panel was used to improve discovery power and fine-mapping resolution. After imputation, the number of variants in ImmunoChip regions with imputation R-squared > 0.8 and MAF > 0.005 in each ancestry group was 322,084 (AFR), 166,274 (EUR), 163,612 (FIN), 137,730 (EAS) and 188,550 (AMR). Imputed genotypes were compared in the same participants who have whole genome sequencing data, resulting in high concordance. Unrelated cases and controls (N = 41,545) were analyzed initially, assuming an additive inheritance model. T1D trio families (N = 6,143 trios, some trio families were multiplex and analyzed as multiple trios) were analyzed separately, with meta-analysis of case-control and trio results used for discovery of regions associated with T1D (p < 5×10-8). Summary-level data at each SNP (genotype and imputed) for type 1 diabetes (outcome) are provided in dbGaP.

Study phs002468

Changes in Oral and Gut Microbiota and Incidence and Severity of Patient-Reported Symptoms in Pre- and Post-Kidney Transplant Patients

This novel prospective cohort explores the relationships between oral and fecal microbiome features (alpha and beta diversity, differential relative abundances of bacterial taxa, and functional genes) and the incidence and severity of psychoneurological symptoms (e.g., pain, fatigue, depression, anxiety, and sleep disturbance) before and after patients receive a kidney transplant from a live donor. Thirty-five subjects provided fecal and saliva specimens for shotgun metagenomic sequencing of gut and oral microbiomes at 3 timepoints: 1) within 4 weeks prior to the transplant surgery (at end-stage kidney disease), 2) 1-3 weeks after the transplant surgery, and 3) at 3 months after the transplant (after restoration of kidney function). Subjects were enrolled between October, 2018, to November, 2021, and all study visits were completed by March, 2022. Data collected includes: Demographic (age, biological sex at birth, race/ethnicity, marital status); clinical data (body mass index, dialysis status, type of dialysis, high vs. low risk immune-suppression protocol, antibiotics during study period); laboratory data (serum creatinine; estimated glomerular filtration rate; serum blood urea nitrogen; immunosuppression trough levels), and outcome data (symptoms such as pain interference, pain intensity, fatigue, anxiety, depression, sleep disturbance, acute rejection, delayed graft failure, graft loss, post-transplant infections, and health-related quality of life). Incidence and severity of symptoms, including pain interference, pain intensity, fatigue, sleep dysfunction, and anxiety/depression-like symptoms, were measured using the Patient Reported Outcome Measurement Systems (PROMIS) 57 v2.1. Health related quality of life was assessed using the Kidney Disease Quality of Life Short Form (KDQOL-SF v1.3). The objective of this longitudinal study is to characterize changes in microbial features at baseline, before restoration of kidney function, and over time, after restoration of kidney function via kidney transplantation, and to identify relationships between microbiome features and transplant outcomes (rejection, infection, delayed graft function, graft failure), symptom burden, and health-related quality of life. Shotgun metagenomic sequencing of the oral and gut microbiomes will allow a higher-resolution examination of the gut microbiome compared to 16S rRNA gene amplicon sequencing, and will provide direct evidence of metabolic capabilities of the microbiota. This approach will allow us to explore the dynamic nature of symptom burden, and the effects of demographic and clinical variables on the oral and gut microbiomes before and after restoration of kidney function.

Study phs002199

Whole Genome Sequencing and Variant Calling for Autism Families

We extracted DNA from whole blood or lymphoblast-derived cell lines and assessed the DNA quality with PicoGreenTM and gel electrophoresis. Whole genome sequencing was performed (Illumina HiSeq2000 and Illumina HiSeq X). WGS reads were mapped to the human reference genome assembly hg19 (GRCh37) using Burrows-Wheeler Aligner v.0.7.12 (TCAG) or Isaac v.2.0.13 (Macrogen). For each genome, we performed local realignment and quality recalibration and detected SNVs and small indels using GATK Haplotype Caller v.3.4.6 without genotype refinement. We detected CNVs using ERDS (estimation by read depth with single nucleotide variants) and CNVnator. We detected structural variants using Manta v.0.29.6. When available by the variant caller (i.e. GATK and Manta), trio-based joint variant calling was conducted for each family.

Dataset EGAD00001008452

DAC for Central African ancient demography processes NGS dataset

Title DAC Ancient tree-topologies and gene-flow processes among human lineages in Africa Contacts: Paul Verdu +33144057317 paul.verdu@mnhn.fr CNRS-MNHN-Université de Paris UMR7206 Eco-anthropology Short description The Data Access Committee for acess to genotype and sample information used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa" by Gwenna Breton et al. 2025 ensures that data-access requests comply with the Informed Consent provided by donors, and with ethical and deontological guidelines with respect to privacy. DNA samples from individuals were collected with the subjects’ informed consent following the Declaration of Helsinki guidelines and approved by the following Ethics committees: Institut de Recherche pour le Développement (IRD, France); Cameroon Ministry of Scientific Research and Technology; Central African Republic Ministère de l’Enseignement Supérieur et de la Recherche Scientifique; France Ministère de l’Enseignement Supérieur, de la Recherche et de l’Innovation (Comité de Protection des Personnes DC-2016-2740); French Commission Nationale Informatique et Liberté CNIL (declaration n°1972648); Uganda National Council for Science and Technology; Institutional Review Board of the University of Chicago Biological Sciences Division and the Pritzker School of Medicine University of Chicago Hospitals (protocol number 16986A); Committee for the Protection of Human Subjects of the Trustees of Dartmouth College and the Dartmouth-Hitchcock Medical Center (protocol number 22410); Human Research Ethics Committee (Medical) at the University of the Witwatersrand, Johannesburg (Protocol Numbers: M980553, M050902, M090576, M10270, M180654); Working Group of Indigenous Minorities in Southern Africa (WIMSA); South African San Council (SASC); and the Swedish Ethical Review Authority (Dnr 2019-05174). Requests for accessing all or part of the Central African data used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa", by Gwenna Breton et al. 2024 (doi - PENDING), should be addressed to the DAC providing: 1) Data can only be used to explore human genetic evolution, evolutionary ecology and population history 2) The research institution where data will be stored and were analyses will be conducted. 3) The detailed coordinates of the researcher responsible for data storage and analyses. 4) A description (max 20 sentences) of the scientific finality and context of the project and classes of methodological analyses that will be performed to achieve it using the requested data. 5) When applicable, mention also other previously published data sets that will be used jointly with the requested datas et For accessing any or all the Central African genetic data used in the article "Ancient tree-topologies and gene-flow processes among human lineages in Africa", by Gwenna Breton et al. 2024 (doi - PENDING), the requester hereby ensures that: 1) Individual donor privacy should be respected at all times. Data cannot be made publicly available under any circumstances. 2) Data cannot be shared nor transferred to a third party without re-applying for eGA access to the DAC. 3) No direct or indirect commercial use of the data can be made 4) No individual medical genetics or disease diagnostics can be performed with the data 5) No medical or legal forensic investigations can be conducted with the data 6) No genealogical research can be conducted with the data (e.g. no paternity nor maternity testing, no genetic identification, no search of relatives using other datasets) 7) Appropriate citation of the article and data set used for any scientific communication using the data 8) Data is destroyed after the completion of the project. Any further re-use of the data is subject to a novel application to the DAC.

Dac EGAC50000000447

14977 results for "cancer studies using rna-seq"

in 20.48 milliseconds.