ERNA: A graphic user interface-based tool for RNA sequencing data analysis [microRNA-Seq]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE53451 | GEO | 2014/06/01
SECONDARY ACCESSION(S): PRJNA232039
REPOSITORIES: GEO
Similar Datasets
Project description:we performed RNA sequencing analysis using 7 human plasma samples and evaluated efficiency and accuracy of eRNA on miRNA-seq data analysis. We sequenced microRNAs from the 7 human tissue samples with replicates (A1/A8, B2/B9, C3/C10, D4/D11, E5/E12, F6/F13, G7/G14) using NEBNext Multiplex Small RNA library Prep Set from New England Biolab (NEB). After that, we identified miRNAs in these plasma samples against known human matured miRNAs.
2014-06-01 | E-GEOD-53451 | biostudies-arrayexpress
Project description:we performed RNA sequencing analysis using 10 tissue samples from human prostate and evaluated efficiency and accuracy of eRNA on mRNA-seq data analysis. We sequenced mRNAs from the 10 human tissue samples. After that, we identified mRNAs in these samples against known human genes.
2014-06-01 | E-GEOD-53450 | biostudies-arrayexpress
Project description:we performed RNA sequencing analysis using 10 tissue samples from human prostate and evaluated efficiency and accuracy of eRNA on mRNA-seq data analysis.
2014-06-01 | GSE53450 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-06-01 | E-GEOD-53452 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2014-06-01 | GSE53452 | GEO
Project description:BackgroundRNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers.ResultsWe developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification" includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module "mRNA identification" includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module "Target screening" provides expression profiling analyses and graphic visualization. The module "Self-testing" offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program's functionality.ConclusionseRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory.
| S-EPMC4029068 | biostudies-literature
Project description:Amplicon sequencing of the 16S rRNA gene is commonly performed for the assessment and comparison of microbiomes. Here, we introduce GenePiper, an open-source R Shiny application that provides an easy-to-use interface, a wide range of analytical methods, and optimized graphical outputs for offline microbiome data analyses.
| S-EPMC6940285 | biostudies-literature
Project description:Nowadays, studying microorganisms has become faster and deeper than the last decades, thanks to the modeling of genome-scale metabolic networks. Completed genome sequencing projects of microorganisms and annotating these sequences have provided a worthwhile platform for reconstructing and modeling genome-scale metabolic networks. The genome-scale metabolic network reconstruction is a laborious and time-consuming task which needs an extensive study and search in different types of databases. Furthermore, it also requires an iterative process of creating and curating the obtained network, particularly with experimental methods. Hence, different types of reconstructions and models of a targeted microorganism can be found with different qualities, as the goal and need of researchers differ. Due to these circumstances, scientists have to continue with only one of the reconstructed metabolic networks of each microorganism and ignore the rest in their in silico works. It is clear that having a tool which merges different metabolic networks of a single organism can be a useful and effective way to study them with minimal cost and time. To meet this need, we have developed iMet, the standalone graphical user interface (GUI) software tool to merge multiple reconstructed metabolic networks of microorganisms. As a case study, we merged three reconstructed metabolic networks of a cyanobacterium using iMet, and then all of them (including the new merged one) became modeled. The results of our evaluations including Flux Balance Analysis (FBA), revealed enhancing metabolic network coverage as well as increasing yield of desired products in the new obtained model.
| S-EPMC6587100 | biostudies-literature
Project description:Over the years, the various mediums available for storytelling have progressively expanded, from spoken to written word, then to film, and now to Virtual Reality (VR) and Augmented Reality (AR). In 2016, the cutting-edge Head-Mounted Display (HMD) AR Microsoft HoloLens was released. However, though it has been several years, the quality of the user experience with narration using HMD-based AR technology has been rarely discussed. The present study explored interactive narrative in HMD-based AR regarding different user interfaces and their influence on users' presence, narrative engagement and reflection. Inspired by an existing exhibition at the National Holocaust Centre and Museum in the U.K., a HoloLens narrative application, entitled The AR Journey, was developed by the authors using two different interaction methods, Natural User Interface (NUI) and Graphical User Interface (GUI), which were used to perform an empirical study. As revealed from the results of the between-subject design experiment, NUI exhibited statistically significant advantages in creating presence for users without 3D Role Playing Game (RPG) experience, and GUI was superior in creating presence and increasing narrative engagement for users with 3D RPG experience. As indicated by the results of the interviews, the overall narrative experience in HMD-based AR was acceptable, and the branching narrative design was engaging. However, HoloLens hardware issues, as well as virtuality and reality mismatch, adversely affected user experience. Design guidelines were proposed according to the qualitative results.Supplementary informationThe online version contains supplementary material available at 10.1007/s11042-021-11723-0.
| S-EPMC8717307 | biostudies-literature
Project description:BackgroundWith the growing impact of observational research studies, there is also a growing focus on data quality (DQ). As opposed to experimental study designs, observational research studies are performed using data mostly collected in a non-research context (secondary use). Depending on the number of data elements to be analyzed, DQ reports of data stored within research networks can grow very large. They might be cumbersome to read and important information could be overseen quickly. To address this issue, a DQ assessment (DQA) tool with a graphical user interface (GUI) was developed and provided as a web application.MethodsThe aim was to provide an easy-to-use interface for users without prior programming knowledge to carry out DQ checks and to present the results in a clearly structured way. This interface serves as a starting point for a more detailed investigation of possible DQ irregularities. A user-centered development process ensured the practical feasibility of the interactive GUI. The interface was implemented in the R programming language and aligned to Kahn et al.'s DQ categories conformance, completeness and plausibility.ResultsWith DQAgui, an R package with a web-app frontend for DQ assessment was developed. The GUI allows users to perform DQ analyses of tabular data sets and to systematically evaluate the results. During the development of the GUI, additional features were implemented, such as analyzing a subset of the data by defining time periods and restricting the analyses to certain data elements.ConclusionsAs part of the MIRACUM project, DQAgui is now being used at ten German university hospitals for DQ assessment and to provide a central overview of the availability of important data elements in a datamap over 2 years. Future development efforts should focus on design optimization and include a usability evaluation.
| S-EPMC9367129 | biostudies-literature