KmerKeys: a web resource for searching indexed genome assemblies and variants.
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ABSTRACT:
SUBMITTER: Pavlichin DS
PROVIDER: S-EPMC9252721 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:MotivationFor most research approaches, genome analyses are dependent on the existence of a high quality genome reference assembly. However, the local accuracy of an assembly remains difficult to assess and improve. The gEVAL browser allows the user to interrogate an assembly in any region of the genome by comparing it to different datasets and evaluating the concordance. These analyses include: a wide variety of sequence alignments, comparative analyses of multiple genome assemblies, and consistency with optical and other physical maps. gEVAL highlights allelic variations, regions of low complexity, abnormal coverage, and potential sequence and assembly errors, and offers strategies for improvement. Although gEVAL focuses primarily on sequence integrity, it can also display arbitrary annotation including from Ensembl or TrackHub sources. We provide gEVAL web sites for many human, mouse, zebrafish and chicken assemblies to support the Genome Reference Consortium, and gEVAL is also downloadable to enable its use for any organism and assembly.Availability and implementationWeb Browser: http://geval.sanger.ac.uk, Plugin: http://wchow.github.io/wtsi-geval-pluginContactkj2@sanger.ac.ukSupplementary informationSupplementary data are available at Bioinformatics online.
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Project description:For nearly 100 years serotyping has been the gold standard for the identification of Salmonella serovars. Despite the increasing adoption of DNA-based subtyping approaches, serotype information remains a cornerstone in food safety and public health activities aimed at reducing the burden of salmonellosis. At the same time, recent advances in whole-genome sequencing (WGS) promise to revolutionize our ability to perform advanced pathogen characterization in support of improved source attribution and outbreak analysis. We present the Salmonella In Silico Typing Resource (SISTR), a bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, this resource integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates. As sequencing of Salmonella isolates at public health laboratories around the world becomes increasingly common, rapid in silico analysis of minimally processed draft genome assemblies provides a powerful approach for molecular epidemiology in support of public health investigations. Moreover, this type of integrated analysis using multiple sequence-based methods of sub-typing allows for continuity with historical serotyping data as we transition towards the increasing adoption of genomic analyses in epidemiology. The SISTR platform is freely available on the web at https://lfz.corefacility.ca/sistr-app/.
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Project description:Sporadic Alzheimer's disease (AD) is a complex genetic disease, and the leading cause of dementia worldwide. Over the past 3 decades, extensive pioneering research has discovered more than 70 common and rare genetic risk variants. These discoveries have contributed massively to our understanding of the pathogenesis of AD but approximately half of the heritability for AD remains unaccounted for. There are regions of the genome that are not assayed by mainstream genotype and sequencing technology. These regions, known as the Dark Genome, often harbour large structural DNA variants that are likely relevant to disease risk. Here, we describe the dark genome and review current technological and bioinformatics advances that will enable researchers to shed light on these hidden regions of the genome. We highlight the potential importance of the hidden genome in complex disease and how these strategies will assist in identifying the missing heritability of AD. Identification of novel protein-coding structural variation that increases risk of AD will open new avenues for translational research and new drug targets that have the potential for clinical benefit to delay or even prevent clinical symptoms of disease.
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Project description:Although they have demonstrated success in searching for common variants for complex diseases, genome-wide association (GWA) studies are less successful in detecting rare genetic variants because of the poor statistical power of most of current methods. We developed a two-stage method that can apply to GWA studies for detecting rare variants. Here we report the results of applying this two-stage method to the Wellcome Trust Case Control Consortium (WTCCC) dataset that include seven complex diseases: bipolar disorder, cardiovascular disease, hypertension (HT), rheumatoid arthritis, Crohn's disease, type 1 diabetes and type 2 diabetes (T2D). We identified 24 genes or regions that reach genome wide significance. Eight of them are novel and were not reported in the WTCCC study. The cumulative risk (or protective) haplotype frequency for each of the 8 genes or regions is small, being at most 11%. For each of the novel genes, the risk (or protective) haplotype set cannot be tagged by the common SNPs available in chips (r (2) < 0.32). The gene identified in HT was further replicated in the Framingham Heart Study, and is also significantly associated with T2D. Our analysis suggests that searching for rare genetic variants is feasible in current GWA studies and candidate gene studies, and the results can severe as guides to future resequencing studies to identify the underlying rare functional variants.
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Project description:HMMER is a software suite for protein sequence similarity searches using probabilistic methods. Previously, HMMER has mainly been available only as a computationally intensive UNIX command-line tool, restricting its use. Recent advances in the software, HMMER3, have resulted in a 100-fold speed gain relative to previous versions. It is now feasible to make efficient profile hidden Markov model (profile HMM) searches via the web. A HMMER web server (http://hmmer.janelia.org) has been designed and implemented such that most protein database searches return within a few seconds. Methods are available for searching either a single protein sequence, multiple protein sequence alignment or profile HMM against a target sequence database, and for searching a protein sequence against Pfam. The web server is designed to cater to a range of different user expertise and accepts batch uploading of multiple queries at once. All search methods are also available as RESTful web services, thereby allowing them to be readily integrated as remotely executed tasks in locally scripted workflows. We have focused on minimizing search times and the ability to rapidly display tabular results, regardless of the number of matches found, developing graphical summaries of the search results to provide quick, intuitive appraisement of them.
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Project description:UnlabelledIn recent times, information on miRNAs and their binding sites is gaining momentum. Therefore, there is interest in the development of tools extracting miRNA related information from known literature. Hence, we describe GeneAFinder and miRAFinder scripts (open source) developed using python programming for the semi-automatic extraction and arrangement of updated information on miRNAs, genes and additional data from published article abstracts in PubMed. The scripts are suitable for custom modification as per requirement.AvailabilitymiRAFinder and GeneAFinder scripts are free and available for download at http://sites.google.com /site/malaheenee/software.
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Project description:Publications without authorship information have been indexed as anonymous in the Web of Science database over the years. However, discussions on this subject have not been sufficiently addressed in the scholarly literature. Since bibliometrics studies are widely used for bibliometricians, scientific disciplines, science policy, and management, missing significant data as authorship metadata characterizes a gray zone that directly impacts these three components, and by extension, for bibliometrics and scientometrics. With a data collection performed at Web of Science Core Collection (WoSCC), 1,420,842 documents under "anonymous" authorship from 1900 to 2021 were retrieved, which accounted for 1.5% of the total documents indexed in the WoSCC. The publication data such as yearly growth of research publications, document type, language, productive research areas, and other bibliometric indicators were analyzed. The findings showed that in absolute numbers, a considerable growth of anonymous publications between 1996 and 2009, and there was a downward trend after that. However, this increase has not been proportional to the growth in the total number of publications indexed in the WoSCC. Articles, editorial materials, and news items were the top three document types among the WoSCC-indexed publications as anonymous. This study also finds two main scenarios of indexing publications as anonymous. The first is associated with the historical context of scholarly communication and practices that persist. The second is characterized by indexing persistent problems. This study suggests minimizing the error in databases, enabling an error-free indexing system and accurate bibliometrics studies.Supplementary informationThe online version contains supplementary material available at 10.1007/s11192-022-04494-4.
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Project description:Water buffalo (Bubalus bubalis), belonging to the Bovidae family, is an economically important animal as it is the major source of milk, meat, and drought in numerous countries. It is mainly distributed in tropical and subtropical regions with a global population of approximately 202 million. The advent of low cost and rapid sequencing technologies has opened a new vista for global buffalo researchers. In this study, we utilized the genomic data of five commercially important buffalo breeds, distributed globally, namely, Mediterranean, Egyptian, Bangladesh, Jaffrarabadi, and Murrah. Since there is no whole-genome sequence analysis of these five distinct buffalo breeds, which represent a highly diverse ecosystem, we made an attempt for the same. We report the first comprehensive, holistic, and user-friendly web genomic resource of buffalo (BuffGR) accessible at http://backlin.cabgrid.res.in/buffgr/, that catalogues 6028881 SNPs and 613403 InDels extracted from a set of 31 buffalo tissues. We found a total of 7727122 SNPs and 634124 InDels distributed in four breeds of buffalo (Murrah, Bangladesh, Jaffarabadi, and Egyptian) with reference to the Mediterranean breed. It also houses 4504691 SSR markers from all the breeds along with 1458 unique circRNAs, 37712 lncRNAs, and 938 miRNAs. This comprehensive web resource can be widely used by buffalo researchers across the globe for use of markers in marker trait association, genetic diversity among the different breeds of buffalo, use of ncRNAs as regulatory molecules, post-transcriptional regulations, and role in various diseases/stresses. These SNPs and InDelscan also be used as biomarkers to address adulteration and traceability. This resource can also be useful in buffalo improvement programs and disease/breed management.
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Project description:The proteins in a cell often assemble into complexes to carry out their functions and play an essential role of biological processes. The PCFamily server identifies template-based homologous protein complexes [called protein complex family (PCF)] and infers functional modules of the query proteins. This server first finds homologous structure complexes of the query using BLASTP to search the structural template database (11,263 complexes). PCFamily then searches the homologous complexes of the templates (query) from a complete genomic database (Integr8 with 6,352,363 protein sequences in 2274 species). According to these homologous complexes across multiple species, this sever infers binding models (e.g. hydrogen-bonds and conserved amino acids in the interfaces), functional modules, and the conserved interacting domains and Gene Ontology annotations of the PCF. Experimental results demonstrate that the PCFamily server can be useful for binding model visualizations and annotating the query proteins. We believe that the server is able to provide valuable insights for determining functional modules of biological networks across multiple species. The PCFamily sever is available at http://pcfamily.life.nctu.edu.tw.
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Project description:BackgroundWithin the past decade, Africa has faced several recurrent outbreaks of Ebola virus disease (EVD), including the 2014-2016 outbreak in West Africa and the recent 2018-2020 Kivu outbreak in the Democratic Republic of Congo. The study thus aimed at quantifying and mapping the scientific output of EVD research published within 2010-2020 though a bibliometric perspective.MethodsEVD-related publications from 2010 to 2020 were retrieved from the Web of Science (WoS) and Scopus databases by using the keywords 'Ebola', 'Ebola Virus Disease', 'Ebolas', and 'ebolavirus'. Biblioshiny software (using R-studio cloud) was used to categorise and evaluate authors', countries' and journals' contribution. VOSviewer was used for network visualisation.ResultsAccording to the used search strategy, a total of 3865 and 3848 EVD documents were published in WoS and Scopus, respectively. The average citation per document was 16.1 (WoS) and 16.3 (Scopus). The results show an overall increase in the publication trend within the study period. The leading countries in EVD research were the USA and UK, with over 100 papers in both databases, including Nigeria and South Africa. NIAID and CDC-USA were the most influential institutions, while "Infectious Diseases" and "Medicine" were the most decisive research fields. The most contributing authors included Feldmann H and Qiu XG with over 60 papers in each database, while Journal of Infectious Diseases was the most crucial journal. The most cited article was from Aylward et al. published in 2014, while recent years displayed a keyword focus on "double-blind", "efficacy", "ring vaccination" and "drug effect".ConclusionThis bibliometric analysis provides an updated historical perspective of progress in EVD research and has highlighted the role played by various stakeholders. However, the contribution of African countries and institutions is not sufficiently reflected, implying a need for increased funding and focus on EVD research for effective prevention and control.
| S-EPMC7486633 | biostudies-literature