TRic: a user-friendly data portal to explore the expression landscape of tRNAs in human cancers.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhang Z
PROVIDER: S-EPMC7567503 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:An easily accessible climate data portal, http://yorku.ca/ocdp, was developed and officially launched in 2018 to disseminate a super ensemble of high-resolution regional climate change projections for the province of Ontario, Canada. The spatial resolution is ~10?km?×?~10?km and temporal resolution is one day, UTC. The data covers 120 years from 1981 to 2100. This user-friendly portal provides users with thousands of static and interactive maps, decadal variation trend lines, summary tables, reports and terabytes of bias-corrected downscaled data. The data portal was generated with an emphasis on interactive visualization of climate change information for researchers and the public to understand to what extent climate could change locally under different emission scenarios in the future. This paper presents an introduction to the portal structure and functions, the large extent of the datasets available and the data development methodology.
| S-EPMC7237651 | biostudies-literature
Project description:Genotyping by re-sequencing has become a standard approach to estimate single nucleotide polymorphism (SNP) diversity, haplotype structure and the biodiversity and has been defined as an efficient approach to address geographical population genomics of several model species. To access core SNPs and insertion/deletion polymorphisms (indels), and to infer the phyletic patterns of speciation, most such approaches map short reads to the reference genome. Variant calling is important to establish patterns of genome-wide association studies (GWAS) for quantitative trait loci (QTLs), and to determine the population and haplotype structure based on SNPs, thus allowing content-dependent trait and evolutionary analysis. Several tools have been developed to investigate such polymorphisms as well as more complex genomic rearrangements such as copy number variations, presence/absence variations and large deletions. The programs available for this purpose have different strengths (e.g. accuracy, sensitivity and specificity) and weaknesses (e.g. low computation speed, complex installation procedure and absence of a user-friendly interface). Here we introduce Altools, a software package that is easy to install and use, which allows the precise detection of polymorphisms and structural variations.Altools uses the BWA/SAMtools/VarScan pipeline to call SNPs and indels, and the dnaCopy algorithm to achieve genome segmentation according to local coverage differences in order to identify copy number variations. It also uses insert size information from the alignment of paired-end reads and detects potential large deletions. A double mapping approach (BWA/BLASTn) identifies precise breakpoints while ensuring rapid elaboration. Finally, Altools implements several processes that yield deeper insight into the genes affected by the detected polymorphisms. Altools was used to analyse both simulated and real next-generation sequencing (NGS) data and performed satisfactorily in terms of positive predictive values, sensitivity, the identification of large deletion breakpoints and copy number detection.Altools is fast, reliable and easy to use for the mining of NGS data. The software package also attempts to link identified polymorphisms and structural variants to their biological functions thus providing more valuable information than similar tools.
| S-EPMC4756442 | biostudies-literature
Project description:Spatial transcriptomics (ST) is a powerful tool for understanding tissue biology and disease mechanisms. However, the advanced data analysis and programming skills required can hinder researchers from realizing of the full potential of ST. To address this, we developed spatialGE, a web application that simplifies the analysis of ST data. The application spatialGE provided a user-friendly interface that guides users without programming expertise through various analysis pipelines, including quality control, normalization, domain detection, phenotyping, and multiple spatial analyses. It also enabled comparative analysis among samples and supported various ST technologies. The utility of spatialGE was demonstrated through its application in studying the tumor microenvironment of two data sets: 10X Visium samples from a cohort of melanoma metastasis and Nanostring CosMx fields of vision from a cohort of Merkel cell carcinoma samples. These results support the ability of spatialGE to identify spatial gene expression patterns that provide valuable insights into the tumor microenvironment and highlight its utility in democratizing ST data analysis for the wider scientific community.
2024-11-21 | GSE271422 | GEO
Project description:BackgroundSeveral mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills.ResultsHere, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al.ConclusionGEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.
| S-EPMC2194737 | biostudies-literature
Project description:The digitization of herbaria and their online access will greatly facilitate access to plant collections around the world. This will improve the efficiency of taxonomy and help reduce inequalities between scientists. The Botanic Garden Meise, Belgium, is currently digitizing 1.2 million specimens including label data. In this paper we describe the user requirements analysis conducted for a new herbarium web portal. The aim was to identify the required functionality, but also to assist in the prioritization of software development and data acquisition. The Garden conducted the analysis in cooperation with Clockwork, the digital engagement agency of Ordina. Using a series of interactive interviews, potential users were consulted from universities, research institutions, science-policy initiatives and the Botanic Garden Meise. Although digital herbarium data have many potential stakeholders, we focused on the needs of taxonomists, ecologists and historians, who are currently the primary users of the Meise herbarium data portal. The three categories of user have similar needs, all wanted as much specimen data as possible, and for those data, to be interlinked with other digital resources within and outside the Garden. Many users wanted an interactive system that they could comment on, or correct online, particularly if such corrections and annotations could be used to rank the reliability of data. Many requirements depend on the quality of the digitized data associated with each specimen. The essential data fields are the taxonomic name; geographic location; country; collection date; collector name and collection number. Also all researchers valued linkage between biodiversity literature and specimens. Nevertheless, to verify digitized data the researchers still want access to high quality images, even if fully transcribed label information is provided. The only major point of disagreement is the level of access users should have and what they should be allowed to do with the data and images. Not all of the user requirements are feasible given the current technical and regulatory landscape, however, the potential of these suggestions is discussed. Currently, there is no off-the-shelf solution to satisfy all these user requirements, but the intention of this paper is to guide other herbaria who are prioritising their investment in digitization and online web functionality.
| S-EPMC5543274 | biostudies-literature
Project description:The discovery of the small regulatory RNA populations has changed our vision of cellular regulations. Indeed, loaded on Argonaute proteins they formed ribonucleoprotein complexes that target complementary sequences and achieved widespread silencing mechanisms conserved in most eukaryotes. The recent development of deep sequencing approaches highly contributed to their detection. Small RNA isolation form cells and/or tissues remains a crucial stage to generate robust and relevant sequencing data. In 2006, a novel strategy based on anion-exchange chromatography has been purposed as an alternative to the standard size-isolation purification procedure. However, the eventual biases of such a method have been poorly investigated. Moreover, this strategy not only relies on advanced technical skills and expensive material but is time consuming and requires an elevated starting biological material amount. Using bioinformatic comparative analysis of six independent small RNA-sequencing libraries of Drosophila ovaries, we here demonstrate that anion-exchange chromatography purification prior to small RNA extraction unbiasedly enriches datasets in bona fide reads (small regulatory RNA reads) and depletes endogenous contaminants (ribosomal RNAs and degradation products). The resulting increase of sequencing depth provides a major benefit to study rare populations. We then developed a fast and basic manual procedure to purify loaded small non coding RNAs using anion-exchange chromatography at the bench. We validated the efficiency of this new method and used this strategy to purify small RNAs from various tissues and organisms. We moreover determined that our manual purification increases the output of the previously described anion-exchange chromatography procedure.
2013-06-13 | GSE40748 | GEO
Project description:Pathway analysis is widely used in omics studies. Pathway-based data integration and visualization is a critical component of the analysis. To address this need, we recently developed a novel R package called Pathview. Pathview maps, integrates and renders a large variety of biological data onto molecular pathway graphs. Here we developed the Pathview Web server, as to make pathway visualization and data integration accessible to all scientists, including those without the special computing skills or resources. Pathview Web features an intuitive graphical web interface and a user centered design. The server not only expands the core functions of Pathview, but also provides many useful features not available in the offline R package. Importantly, the server presents a comprehensive workflow for both regular and integrated pathway analysis of multiple omics data. In addition, the server also provides a RESTful API for programmatic access and conveniently integration in third-party software or workflows. Pathview Web is openly and freely accessible at https://pathview.uncc.edu/.
| S-EPMC5570256 | biostudies-literature
Project description:: The composition of immune-cell subsets is key to the understanding of major diseases and pathologies. Computational deconvolution methods enable researchers to investigate immune cell quantities in complex tissues based on transcriptome data. Here we present ImmQuant, a software tool allowing immunologists to upload transcription profiles of multiple tissue samples, apply deconvolution methodology to predict differences in cell-type quantities between the samples, and then inspect the inferred cell-type alterations using convenient visualization tools. ImmQuant builds on the DCQ deconvolution algorithm and allows a user-friendly utilization of this method by non-bioinformatician researchers. Specifically, it enables investigation of hundreds of immune cell subsets in mouse tissues, as well as a few dozen cell types in human samples.Availability and implementationImmQuant is available for download at http://csgi.tau.ac.il/ImmQuant/ CONTACT: iritgv@post.tau.ac.ilSupplementary information: Supplementary data are available at Bioinformatics online.
| S-EPMC5167062 | biostudies-literature
Project description:The discovery of the small regulatory RNA populations has changed our vision of cellular regulations. Indeed, loaded on Argonaute proteins they formed ribonucleoprotein complexes that target complementary sequences and achieved widespread silencing mechanisms conserved in most eukaryotes. The recent development of deep sequencing approaches highly contributed to their detection. Small RNA isolation form cells and/or tissues remains a crucial stage to generate robust and relevant sequencing data. In 2006, a novel strategy based on anion-exchange chromatography has been purposed as an alternative to the standard size-isolation purification procedure. However, the eventual biases of such a method have been poorly investigated. Moreover, this strategy not only relies on advanced technical skills and expensive material but is time consuming and requires an elevated starting biological material amount. Using bioinformatic comparative analysis of six independent small RNA-sequencing libraries of Drosophila ovaries, we here demonstrate that anion-exchange chromatography purification prior to small RNA extraction unbiasedly enriches datasets in bona fide reads (small regulatory RNA reads) and depletes endogenous contaminants (ribosomal RNAs and degradation products). The resulting increase of sequencing depth provides a major benefit to study rare populations. We then developed a fast and basic manual procedure to purify loaded small non coding RNAs using anion-exchange chromatography at the bench. We validated the efficiency of this new method and used this strategy to purify small RNAs from various tissues and organisms. We moreover determined that our manual purification increases the output of the previously described anion-exchange chromatography procedure. Comparison of small regulatory RNA populations obtained after three different small RNA purification procedures
2013-06-13 | E-GEOD-40748 | biostudies-arrayexpress
Project description:Antibody repertoire analysis by high throughput sequencing is now widely used, but a persisting challenge is enabling immunologists to explore their data to discover discriminating repertoire features for their own particular investigations. Computational methods are necessary for large-scale evaluation of antibody properties. We have developed BRepertoire, a suite of user-friendly web-based software tools for large-scale statistical analyses of repertoire data. The software is able to use data preprocessed by IMGT, and performs statistical and comparative analyses with versatile plotting options. BRepertoire has been designed to operate in various modes, for example analysing sequence-specific V(D)J gene usage, discerning physico-chemical properties of the CDR regions and clustering of clonotypes. Those analyses are performed on the fly by a number of R packages and are deployed by a shiny web platform. The user can download the analysed data in different table formats and save the generated plots as image files ready for publication. We believe BRepertoire to be a versatile analytical tool that complements experimental studies of immune repertoires. To illustrate the server's functionality, we show use cases including differential gene usage in a vaccination dataset and analysis of CDR3H properties in old and young individuals. The server is accessible under http://mabra.biomed.kcl.ac.uk/BRepertoire.
| S-EPMC6031031 | biostudies-literature