130 results for ""PhD+2001"+"cited+by"+"bioinformatics""

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• Metagenomic Deep Sequencing in Meningitis and Encephalitis

  This is a prospective observational study seeking to identify pathogens in cases of unexplained neurological disease, particularly those in which there is a presumed infectious cause. This next generation analytical approach will hopefully allow for rapid identification of foreign genomic material, and through a sophisticated bioinformatics pipeline developed in the DeRisi lab, these foreign genomic sequences can be aligned to all known sequences in publicly available databases (i.e. GenBank) which may allow for identification of novel pathogens or known pathogens that are not frequently tested for as part of standard diagnostic work-ups.

  Study phs001067

• FEGA Sweden Helpdesk

  FEGA Sweden is an archive for storing and sharing all kinds of data resulting from biomedical research projects. As a national node of the Federated European Genome-phenome Archive (FEGA), we enable researchers to store their data in Sweden in a way that meets the requirements of the General Data Protection Regulation (GDPR). Any data submitted to the archive is subject to controlled access, meaning access to the data only will be granted after a formal application procedure. Using FEGA Sweden for storing and sharing data is free of charge for academic users affiliated with a Swedish university. However, the university must have a signed Data Processing Agreement (DPA) with Uppsala University. The current list of universities with a signed DPA can be found here: https://fega.nbis.se/submission/complying-with-gdpr.html. FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. Contact the FEGA Sweden Helpdesk at fega-sweden@nbis.se for further questions.

  Dac EGAC50000000077

• Exome Sequencing of familial and sporadic Meniere disease patients

  This study aims to characterize the genetic architecture of spanish patients diagnosed with Meniere disease (MD), focusing on both familial (FMD) and sporadic (SMD) forms, by analyzing coding variants. Whole-exome sequencing was performed on these patients, and variants were called and annotated using the nf-core/sarek bioinformatics pipeline, including alignment to the GRCh38 reference genome. The resulting data provide a curated resource for investigating the potential genetic contribution to the pathophysiology of MD. All data will be made available for reuse under controlled access.

  Study EGAS50000001178

• Anaplastic_Meningioma_WGS_X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Study EGAS00001000859

• Functional Analysis of Genetic Variants in African Americans with Breast Cancer

  The goal of this study is to identify and characterize novel genetic variants associated with a predisposition to breast cancer (BCa) in African Americans (AAs) using a family case-family control study design. Variants of unknown clinical significance (VUS) were characterized using bioinformatics tools. Future studies will further characterize select VUSs using in vitro genomic editing methods and functional assays to determine the functional consequences. The targeted sequencing data is made available for 85 actionable cancer genes. These genes have been previously classified with deleterious mutation(s) and whose phenotype results in a specific, defined medical recommendation(s).

  Study phs002977

• Personalized Onco-Genomic Project for pediatric and adolescent patients in British Columbia

  This is an extension of the BC Cancer Agency's Personalized Onco-Genomics (POG) project to children and adolescents treated at BC Children's Hospital. The project provides access to whole genome and transcriptome sequencing, and integrated bioinformatics analyses, of relapsed, refractory or poor prognosis cancers with an aim to identify actionable variants that can inform clinical decision making.

  Study EGAS00001006967

• Whole exome sequencing variant data for Mendelian disorders cohort

  This dataset contains whole exome sequencing variant data (VCF files) from individuals with suspected Mendelian disorders, including sickle cell disease, muscular dystrophy, haemophilia, and Fanconi anemia. Variant calling was performed using the Illumina DRAGEN pipeline, with downstream variant prioritisation conducted using the Zi-Mendelian bioinformatics pipeline. The dataset supports research into rare genetic diseases and genomic variation in African populations.

  Dataset EGAD50000002453

• Bioinformatics analysis of chimerism in monochorionic dizygotic twins

  We conducted whole-genome sequencing on blood and buccal specimen from a family with chimerism identified in the two monochorionic dizygotic twins. Blood DNA was obtained from all family members. In addition, we obtained buccal specimen from the chimeric twins. Whole-genome sequencing was conducted on Illumina NovaSeq.

  Dataset EGAD00001009508

• RNAseq of pre- and post-5AZA-treated head and neck cancer patients refractory to anti-PD-1 therapy

  RNA sequencing (RNA-seq) was performed on baseline (before low-dose 5-aza treatment) and on-treatment (low-dose 5-aza treatment for 5 or 10 days) tumor samples from eight participants with head and neck cancer who were refractory to anti-PD-1 therapy. RNA library preparations, sequencing reactions, and initial bioinformatics analyses were conducted at GENEWIZ, LLC. In total, 16 150-bp pair-end RNAseq data were generated.

  Dataset EGAD50000001010

• The effects of bioinformatics preprocessing on cell-free DNA analysis

  The dataset contain 20 lung cancer and 20 healthy control cfDNA samples from plasma sequenced using 150bp PE sequencing.

  Dataset EGAD50000000213

• Filtering and Annotation of Variants That Are Rare (FAVR)

  The project developed a suite of new methods (FAVR) designed to assist the shortlisting of genetic variants under a rare variant-phenotype/disease model. The methods were designed to work with commonly used massively parallel sequencing analysis pipelines, such as the GATK or ANNOVAR, and have been made publically available as a suite of software tools (https://github.com/bjpop/favr). The FAVR methods use signatures in comparator sequence alignment files to facilitate the filtering of mapping artifacts and common genetic variants, and annotation of genetic variants based on evidence of co-occurrence in individuals. As relevant, FAVR methods can also be used to filter out artifacts derived from imbalanced paired-end sequencing. Pope et al., BMC Bioinformatics, accepted Dec 2012.

  Study phs000601

• Hematopoietic differentiation at single-cell resolution in NPM1-mutated AML

  To investigate the relationship between somatic mutations and phenotypic hematologic differentiation at the single-cell level, we used a droplet-based multi-omics single-cell platform on eleven NPM1-mutated AML diagnostic samples. We developed a bioinformatics framework to perform phylogeny-driven genotype correction, that allowed us to study 52 103 single cells. Intra-leukemic genetic heterogeneity was detectable in all patients, including a branched architecture in nine of them, always owing to co-occurring signaling mutations. We identified two groups of NPM1-mutated AML, one characterized by a progenitor immunophenotype and a second one with a predominant monocytic differentiation. We also identified various degrees of intra-leukemic immunophenotype heterogeneity, sometimes associated with strong genetic/phenotype correlations.

  Study EGAS00001006565

• RNA sequencing data from patient derived colorectal cancer organoids

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The pipeline was utilized to analyze RNA-seq data from ten patient-derived colorectal cancer (CRC) organoids, representing seven microsatellite stable (MSS) and three microsatellite instable (MSI) tumors. The goal was to explore the ncTSA landscape in CRC, particularly in MSS cases, which typically exhibit low tumor mutational burden and limited response to current immunotherapies. The study identified comparable ncTSA burdens across MSI and MSS tumors, suggesting new avenues for immunotherapy targeting non-canonical antigens in CRC. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000685

• RNA sequencing data from glioblastoma primary cell lines treated with indisulam

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The splicing-modulating drug indisulam was investigated for its potential to induce aberrant transcriptomes, potentially increasing ncTSAs, subsequently predicted by NovumRNA. Four glioblastoma primary cell lines were derived from patient Cavitron Ultrasonic Aspirator (CUSA) material, cultured as neurospheres, and treated with indisulam or vehicle control. RNA was extracted at 6 and 16 hours post-treatment and sequenced using the NovaSeq platform. The resulting RNA-seq data was analyzed with NovumRNA, using healthy brain GTEx samples as controls, to identify and validate ncTSAs induced by indisulam treatment. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000680

• NGS-Based Mutational Analysis of 87 PMBL Patients from the GAINED Cohort (Subset of 382 Sequenced Patients)

  Targeted DNA sequencing was performed on DNA extracted from 87 formalin-fixed paraffin-embedded (FFPE) samples, representing a subset of the 382 sequenced patients from the GAINED cohort. A custom “Lymphopanel” was used to identify mutations in 70 genes associated with lymphomagenesis. Library preparation, exome capture, sequencing, and analysis were conducted by IntegraGen SA (Evry, France). Sequencing was performed on an Illumina HiSeq4000 platform, with variant calling and annotation using established bioinformatics tools such as MuTect and VEP.

  Dataset EGAD50000001359

• CIDR/NICHD Genetic Basis of Recessive Pediatric Brain Diseases - Group 2

  The purpose of this study is to identify new genetic causes of recessive forms of pediatric neurodevelopmental disorders (NDDs) including Cerebellar hypoplasia (CBH), Lissencephaly (LIS), Microcephaly (MIC), Corpus callosum hypoplasia (CCH), Pontocerebellar hypoplasia (PCH), Pontine tegemental cap dysplasia (PTCD), and Aicardi syndrome among many others. Using whole exome sequencing on one or two affected members per family, we are able to identify many pathogenic genes for these families. Using Human SNP Linkage Scans, which takes advantage of the Illumina HumanCore Array, and parametric linkage analysis software (Genehunter, Allegro, and others), we seek to identify pathogenic loci utilizing 60-70 families per year. Through the combination of parametric linkage analysis with exome sequencing and bioinformatics approaches, we will refine our search for superior sensitivity and accuracy when investigating candidate genes and identifying causative mutations for disease.

  Study phs001267

• CIDR/NICHD Genetic Basis of Recessive Pediatric Brain Diseases

  The purpose of this study is to identify new genetic causes of recessive forms of pediatric neurodevelopmental disorders (NDDs) including cerebellar hypoplasia (CBH), lissencephaly (LIS), microcephaly (MIC), corpus callosum hypoplasia (CCH), pontocerebellar hypoplasia (PCH), pontine tegmental cap dysplasia (PTCD), and Aicardi syndrome among many others. Using whole exome sequencing on one or two affected members per family, we are able to identify many pathogenic genes for these families. Using Human SNP Linkage Scans, which takes advantage of the Illumina HumanCore Array, and parametric linkage analysis software (Genehunter, Allegro, and others), we seek to identify pathogenic loci utilizing 60-70 families per year. Through the combination of parametric linkage analysis with exome sequencing and bioinformatics approaches, we will refine our search for superior sensitivity and accuracy when investigating candidate genes and identifying causative mutations for disease.

  Study phs001060

• CIDR NICHD Genetic Basis of Recessive Pediatric Brain Diseases - Group 4

  The purpose of this study is to identify new genetic causes of recessive forms of pediatric neurodevelopmental disorders (NDDs) including Cerebellar hypoplasia (CBH), Lissencephaly (LIS), Microcephaly (MIC), Corpus callosum hypoplasia (CCH), Pontocerebellar hypoplasia (PCH), Pontine tegmental cap dysplasia (PTCD), and Aicardi syndrome among many others. Using whole exome sequencing (WES) on one or two affected members per family, we are able to identify many pathogenic genes for these families. Using Human SNP Linkage Scans, which takes advantage of the Illumina HumanCore Array, and parametric linkage analysis software (Genehunter, Allegro, and others), we seek to identify pathogenic loci utilizing 60-70 families per year. Through the combination of parametric linkage analysis with exome sequencing and bioinformatics approaches, we will refine our search for superior sensitivity and accuracy when investigating candidate genes and identifying causative mutations for disease.

  Study phs001822

• CIDR NICHD Genetic Basis of Recessive Pediatric Brain Disease - Group 3

  The purpose of this study is to identify new genetic causes of recessive forms of pediatric neurodevelopmental disorders (NDDs) including Cerebellar hypoplasia (CBH), Lissencephaly (LIS), Microcephaly (MIC), Corpus callosum hypoplasia (CCH), Pontocerebellar hypoplasia (PCH), Pontine tegmental cap dysplasia (PTCD), and Aicardi syndrome among many others. Using whole exome sequencing (WES) on one or two affected members per family, we are able to identify many pathogenic genes for these families. Using Human SNP Linkage Scans, which takes advantage of the Illumina HumanCore Array, and parametric linkage analysis software (Genehunter, Allegro, and others), we seek to identify pathogenic loci utilizing 60-70 families per year. Through the combination of parametric linkage analysis with exome sequencing and bioinformatics approaches, we will refine our search for superior sensitivity and accuracy when investigating candidate genes and identifying causative mutations for disease.

  Study phs001510

• European Genome-phenome Archive 15th Anniversary Celebration

  2023 marks the 15th Anniversary of the EGA, jointly managed by the European Bioinformatics Institute (EMBL-EBI) and the Centre for Genomic Regulation (CRG). To mark the occasion, a simultaneous celebration was held in both institutions on the 13th of December 2023. The teams gathered online to play a quiz game and celebrate all the achievements and milestones with two wonderful anniversary cakes. In 2008, the European Genome-phenome Archive was created at the EBI-EMBL in Cambridge to guarantee that human genome and phenome data were available to the international scientific community while data privacy was preserved. The six-person staff at the beginning of the project is now far behind us, with a team that reaches the number of 35 members. Since 2013, the European Bioinformatics Institute and the Centre for Genomic Regulation share responsibility for The European Genome-phenome Archive (EGA). At that time, the EGA had data for about 0,5 petabytes. Currently, the Archive contains more than 12 petabytes. 2023 comes to an end with several good news. The EGA has been renewed as an ELIXIR Core Data Resource. This was announced during the GA4GH 11th Plenary held in San Francisco last September when ELIXIR-Beacon was also confirmed to be a GA4GH Driver Project. Thus, the Beacon API has maintained this title since 2018. What’s more, the first Federated EGA dataset is now live on our website. This year we also launched new services for EGA users in September. By the numbers, in 2023 the EGA counts 2.5 PB archived, 371 studies published, 208 new submitters and 19 active projects in which the team is participating, among others. We look forward to continuing to support your research in 2024!

  Blog 15-anniversary

• Effect of Breast Feeding on Immunologic Priming in Young Infants

  The mechanisms generating immunoglobulin heavy chain (IgH) biodiversity result in over potentially unique immunoglobulin sequences within an individual. However, over the course of B cell development, B cell receptor (BCR) selection constrains the repertoire significantly. In newborn infants compared to adults, developmental regulation of terminal deoxynucleotidyl transferase (TdT) activity in the bone marrow, selective use of V, D and J gene segments in the IgH locus during fetal life, and immaturity of somatic hypermutation (SHM) and class switch recombination (CSR) mechanisms are likely to contribute to a less diverse IgH repertoire, although the extent of repertoire biodiversity in newborns has not been extensively examined. Furthermore, the fetal IgH repertoire is tightly controlled and for the most part independent of environmental antigenic influences. As a result, the neonatal repertoire, in contrast to older children and adults, is less impacted by the selective pressures of the microbiome, pathogen exposure, and environmental antigens. Evidence for developmental differences in TdT activity is seen in shorter CDR3 lengths and decreased junctional diversity in BCR in both term and preterm newborns. Next Generation Sequencing (NGS) is a sensitive approach to evaluate the neonatal IgH repertoire and assess the relative contribution of each aspect of IgH rearrangement and affinity maturation to overall IgH biodiversity prior to and following isotype class switch. NGS and bioinformatics accurately assess biodiversity by determining the number of unique sequences within the IgH repertoire. Combined with novel analytic tools, NGS provides an approach to compare the extent of somatic hypermutation (SHM), N insertions, V/D/J gene segment usage, and CDR3 length between newborns and adults. Taken together, these measures can be used to assess the earliest events in B cell development using the newborn Ig transcriptome to evaluate the IgM, IgG, and IgA IgH repertoires. The goal of this study was to define the extent of IgH biodiversity in newborns and examine the factors that contribute to the generation of biodiversity during early life. Establishment of the bioinformatics pipeline can be applied to examine the immune deficiency, response to vaccine and infection at molecular population level.

  Study phs002073

• Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell transcriptome sequencing and a novel bioinformatics pipeline

  We report a deconvolution and identification strategy of scRNA-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and aquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures.

  Study EGAS00001006202

• Searching for variants associated with endometriosis

  We explored regulatory mechanism of a SNP on chromosome 9p21 associated with endometriosis by leveraging “allele-specific” functional genomic approaches. By re-sequencing 1.29 Mb of 9p21 region and scrutinizing DNase-seq data from the ENCODE project, we prioritized rs17761446 as a candidate functional variant that was in perfect linkage disequilibrium with the original GWAS SNP (rs10965235) and located on DNase I hypersensitive site. Chromosome conformation capture followed by high-throughput sequencing revealed that the protective G allele of rs17761446 exerted stronger chromatin interaction with ANRIL promoter. We demonstrated that the protective allele exhibited preferential binding affinities to TCF7L2 and EP300 by bioinformatics and chromatin immunoprecipitation (ChIP) analyses. ChIP assays for histone H3 lysine 27 acetylation and RNA polymerase II reinforced the enhancer activity of the SNP site. The allele specific expression analysis for eutopic endometrial tissues and endometrial carcinoma cell lines showed that rs17761446 was a cis-regulatory variant where G allele was associated with increased ANRIL expression.

  Study EGAS00001001741

• Conjunctival fibrosis and the innate barriers to Chlamydia trachomatis intracellular infection: a genome wide association study

  This data comes from a genome-wide association study in 1090 cases of scarring trachoma and 1531 controls from a non-selected multi-ethnic sampling of The Gambia. The data constitutes hard base calls at 1457295 features from the HumanOmni2.5-8 (Omni2.5) BeadChip. Three genotype-calling algorithms were used : Illuminus (Bioinformatics 2007, 23:2741–6), GenCall (Patent US7035740, 2006) and GenoSNP (Bioinformatics 2008, 24:2209–14). Data from each calling algorithm was filtered to retain only SNPs with a call rate ≥ 0.98. To obtain a merged set of SNPs, all genotypes that matched across call-sets were retained, whilst those that mismatched between call-sets were set to missing. Genotypes that were present in one call set and missing in others were also retained. The merged SNP set contained 1467876 SNPs, which were filtered for call rate ≥ 0.99 and Hardy-Weinberg equilibrium P value < 5 x 10-8. The case and control groups were approximately equivalent with respect to gender and ethnicity. 70% of cases and 63% of controls were female. Self-described ethnic composition of the cases was 29% Jola, 27% Mandinka, 21% Wolof, 10% Fula and 13% other/no data. In controls the composition was 25% Jola, 24% Mandinka, 21% Wolof, 8% Fula and 22% other/no data. Median age was 49 (range 32-60) in cases and 37 (range 12-52) in controls (t = -3.6019, P = 0.0003). This data set has substantial levels of population structure, which reflects extensive networks of pairwise kinship between participants. First pass tests of association in EMMAX (Nat Genet 2010, 42:348–54) led to genome-wide deflation of the test statistics (λ = 0.982 SE = 1.74e-05) that could be directly attributed to the differing age and gender distributions between cases and controls. Modelling the phenotype to adjust for age and gender successfully controlled for this and no genome-wide deviation from the null was subsequently observed (λ = 1.001, SE = 8.7 x 10-7). Neither principal components analysis (PCA) nor tests of proportional identity by state (IBS) variance in PLINK identified significant levels of within or between group genetic variance. The phenotypes submitted in the phenotypes file include both uncorrected (case/control status) and corrected (age and gender corrected case/control status) phenotypes, as well as age and self-described ethnicity.

  Study EGAS00001001516

• Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

  This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

  Dataset EGAD50000001557