scholarly journals FaDA: A web application for regular laboratory data analyses

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261083
Author(s):  
Richard Danger ◽  
Quentin Moiteaux ◽  
Yodit Feseha ◽  
Estelle Geffard ◽  
Gérard Ramstein ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Web Application ◽  
Multiple Testing ◽  
Laboratory Data ◽  
Principal Component ◽  
Nonparametric Tests ◽  
Web Based ◽  
Data Analyses ◽  
R Shiny ◽  
Common Laboratory

Web-based data analysis and visualization tools are mostly designed for specific purposes, such as the analysis of data from whole transcriptome RNA sequencing or single-cell RNA sequencing. However, generic tools designed for the analysis of common laboratory data for noncomputational scientists are also needed. The importance of such web-based tools is emphasized by the continuing increases in the sample capacity of conventional laboratory tools such as quantitative PCR, flow cytometry or ELISA instruments. We present a web-based application FaDA, developed with the R Shiny package that provides users with the ability to perform statistical group comparisons, including parametric and nonparametric tests, with multiple testing corrections suitable for most standard wet-laboratory analyses. FaDA provides data visualizations such as heatmaps, principal component analysis (PCA) plots, correlograms and receiver operating curves (ROCs). Calculations are performed through the R language. The FaDA application provides a free and intuitive interface that allows biologists without bioinformatic skill to easily and quickly perform common laboratory data analyses. The application is freely accessible at https://shiny-bird.univ-nantes.fr/app/Fada.

scholarly journals FaDA: A Shiny web application to accelerate common lab data analyses

2020 ◽  
Author(s):  
Yodit Feseha ◽  
Quentin Moiteaux ◽  
Estelle Geffard ◽  
Gérard Ramstein ◽  
Sophie Brouard ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Data Analysis ◽  
Rna Sequencing ◽  
Quantitative Pcr ◽  
Principal Component ◽  
Component Analysis ◽  
Receiver Operating Curve ◽  
Web Based ◽  
Data Analyses ◽  
Receiver Operating

AbstractBackgroundWeb-based data analysis and visualization tools are mostly designed for specific purposes, such as data from whole transcriptome RNA sequencing or single-cell RNA sequencing. However, limited efforts have been made to develop tools designed for data of common laboratory data for non-computational scientists. The importance of such web-based tool is stressed by the current increased samples capacity of conventional laboratory tools such as quantitative PCR, flow cytometry or ELISA.ResultsWe provide a web-based application FaDA, developed with the R Shiny package providing users to perform statistical group comparisons, including parametric and non-parametric tests, with multiple testing corrections suitable for most of the standard wet-lab analyses. FaDA provides data visualization such as heatmap, principal component analysis (PCA) and receiver operating curve (ROC). Calculations are performed through the R language.ConclusionsFaDA application provides a free and intuitive interface allowing biologists without bioinformatic skills to easily and quickly perform common lab data analyses. The application is freely accessible at https://shiny-bird.univ-nantes.fr/app/FadaAbbreviationsAUC: Area Under the Curve; FaDA: Fast Data Analysis; GEO: Gene Expression Omnibus; ELISA: enzyme-linked immunosorbent assay; PCA: Principal Component Analysis; qPCR: quantitative PCR; ROC: Receiver Operating Curve.

scholarly journals MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps

2015 ◽  
Author(s):  
Bohdan B. Khomtchouk ◽  
James R. Hennessy ◽  
Claes Wahlestedt
Keyword(s):  
Web Application ◽  
Differential Expression Analysis ◽  
Dynamic Network ◽  
Principal Component ◽  
Rna Seq ◽  
Software Suite ◽  
Software Analysis ◽  
Link Type ◽  
R Shiny ◽  
User Friendly

AbstractWe propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network analysis.MicroScope is hosted online as an R Shiny web application based on the D3 JavaScript library: http://microscopebioinformatics.org/. The methods are implemented in R, and are available as part of the MicroScope project at: https://github.com/Bohdan-Khomtchouk/Microscope.

scholarly journals Visualizing the Costs and Benefits of Correcting P-Values for Multiple Hypothesis Testing in Omics Data

2021 ◽  
Author(s):  
Steven R. Shuken ◽  
Margaret W. McNerney
Keyword(s):  
Hypothesis Testing ◽  
Web Application ◽  
Multiple Testing ◽  
Test Group ◽  
Multiple Hypothesis Testing ◽  
P Value ◽  
Critical Element ◽  
Costs And Benefits ◽  
Multiple Hypothesis ◽  
R Shiny

AbstractThe multiple hypothesis testing problem is inherent in high-throughput quantitative genomic, transcriptomic, proteomic, and other “omic” screens. The correction of p-values for multiple testing is a critical element of quantitative omic data analysis, yet many researchers are unfamiliar with the sensitivity costs and false discovery rate (FDR) benefits of p-value correction. We developed models of quantitative omic experiments, modeled the costs and benefits of p-value correction, and visualized the results with color-coded volcano plots. We developed an R Shiny web application for further exploration of these models which we call the Simulator of P-value Multiple Hypothesis Correction (SIMPLYCORRECT). We modeled experiments in which no analytes were truly differential between the control and test group (all null hypotheses true), all analytes were differential, or a mixture of differential and non-differential analytes were present. We corrected p-values using the Benjamini-Hochberg (BH), Bonferroni, and permutation FDR methods and compared the costs and benefits of each. By manipulating variables in the models, we demonstrated that increasing sample size or decreasing variability can reduce or eliminate the sensitivity cost of p-value correction and that permutation FDR correction can yield more hits than BH-adjusted and even unadjusted p-values in strongly differential data. SIMPLYCORRECT can serve as a tool in education and research to show how p-value adjustment and various parameters affect the results of quantitative omics experiments.

scholarly journals gwaRs: an R shiny web application for visualizing genome-wide association studies data

2020 ◽  
Author(s):  
Lethukuthula L Nkambule
Keyword(s):  
Web Application ◽  
Association Studies ◽  
Principal Component ◽  
Gwas Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Web Browser ◽  
Link Type ◽  
Genome Wide ◽  
R Shiny

AbstractSummaryAlthough there is an exponential increase and extensive availability of genome-wide association studies data, the visualization of this data remains difficult for non-specialist users. Current software and packages for visualizing GWAS data are intended for specialists and have been developed to accomplish specific functions, favouring functionality over user experience. To facilitate this, we have developed an R shiny web application, gwaRs, that allows any general user to visualize GWAS data efficiently and effortlessly. The gwaRs web-browser interface allows users to visualize GWAS data using SNP-density, quantile-quantile, Manhattan, and Principal Component Analysis plots.AvailabilityThe gwaRs web application is publicly hosted at https://gwasviz.shinyapps.io/gwaRs/ and R source code is released under the GNU General Public License and freely available at GitHub: https://github.com/LindoNkambule/[email protected]

ANALYZING AND IMPROVING WEB APPLICATION QUALITY USING DESIGN PATTERNS

2012 ◽  
Vol 2 (2) ◽  
pp. 112-116
Author(s):  
Shikha Bhatia ◽  
Mr. Harshpreet Singh
Keyword(s):  
Web Application ◽  
Design Pattern ◽  
Design Patterns ◽  
Web Applications ◽  
Past Research ◽  
Software Systems ◽  
Interactive Software ◽  
Web Based ◽  
Software Application ◽  
Execution Speed

With the mounting demand of web applications, a number of issues allied to its quality have came in existence. In the meadow of web applications, it is very thorny to develop high quality web applications. A design pattern is a general repeatable solution to a generally stirring problem in software design. It should be noted that design pattern is not a finished product that can be directly transformed into source code. Rather design pattern is a depiction or template that describes how to find solution of a problem that can be used in many different situations. Past research has shown that design patterns greatly improved the execution speed of a software application. Design pattern are classified as creational design patterns, structural design pattern, behavioral design pattern, etc. MVC design pattern is very productive for architecting interactive software systems and web applications. This design pattern is partition-independent, because it is expressed in terms of an interactive application running in a single address space. We will design and analyze an algorithm by using MVC approach to improve the performance of web based application. The objective of our study will be to reduce one of the major object oriented features i.e. coupling between model and view segments of web based application. The implementation for the same will be done in by using .NET framework.

eMap: A Web Application for Identifying and Visualizing Electron or Hole Hopping Pathways in Proteins

2019 ◽  
Author(s):  
Ruslan N. Tazhigulov ◽  
James R. Gayvert ◽  
Melissa Wei ◽  
Ksenia B. Bravaya
Keyword(s):  
Web Application ◽  
Shortest Paths ◽  
Coarse Grained ◽  
Decay Parameter ◽  
Electron Hole ◽  
Web Based ◽  
Aromatic Amino Acid Residue ◽  
Pathways Model ◽  
Visualization Tools ◽  
Effective Decay

<p>eMap is a web-based platform for identifying and visualizing electron or hole transfer pathways in proteins based on their crystal structures. The underlying model can be viewed as a coarse-grained version of the Pathways model, where each tunneling step between hopping sites represented by electron transfer active (ETA) moieties is described with one effective decay parameter that describes protein-mediated tunneling. ETA moieties include aromatic amino acid residue side chains and aromatic fragments of cofactors that are automatically detected, and, in addition, electron/hole residing sites that can be specified by the users. The software searches for the shortest paths connecting the user-specified electron/hole source to either all surface-exposed ETA residues or to the user-specified target. The identified pathways are ranked based on their length. The pathways are visualized in 2D as a graph, in which each node represents an ETA site, and in 3D using available protein visualization tools. Here, we present the capability and user interface of eMap 1.0, which is available at https://emap.bu.edu.</p>

scholarly journals An Interactive Web Application for the Statistical Analysis of Continuous Glucose Monitoring Data in Epidemiological Studies

2021 ◽  
pp. 193229682098557
Author(s):  
Alysha M. De Livera ◽  
Jonathan E. Shaw ◽  
Neale Cohen ◽  
Anne Reutens ◽  
Agus Salim
Keyword(s):  
Continuous Glucose Monitoring ◽  
Web Application ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Epidemiological Studies ◽  
Interactive Software ◽  
Web Based ◽  
Software Applications ◽  
Visualization Of Data ◽  
User Friendly

Motivation: Continuous glucose monitoring (CGM) systems are an essential part of novel technology in diabetes management and care. CGM studies have become increasingly popular among researchers, healthcare professionals, and people with diabetes due to the large amount of useful information that can be collected using CGM systems. The analysis of the data from these studies for research purposes, however, remains a challenge due to the characteristics and large volume of the data. Results: Currently, there are no publicly available interactive software applications that can perform statistical analyses and visualization of data from CGM studies. With the rapidly increasing popularity of CGM studies, such an application is becoming necessary for anyone who works with these large CGM datasets, in particular for those with little background in programming or statistics. CGMStatsAnalyser is a publicly available, user-friendly, web-based application, which can be used to interactively visualize, summarize, and statistically analyze voluminous and complex CGM datasets together with the subject characteristics with ease.

scholarly journals Investigating microcrystalline cellulose crystallinity using Raman spectroscopy

Cellulose ◽  
2021 ◽  
Author(s):  
Ana Luiza P. Queiroz ◽  
Brian M. Kerins ◽  
Jayprakash Yadav ◽  
Fatma Farag ◽  
Waleed Faisal ◽  
...  
Keyword(s):  
Raman Spectra ◽  
Microcrystalline Cellulose ◽  
Web Application ◽  
Principal Component ◽  
Raw Material ◽  
Least Squares Regression ◽  
Analysis Model ◽  
General Reference ◽  
Material Source ◽  
Univariate Model

AbstractMicrocrystalline cellulose (MCC) is a semi-crystalline material with inherent variable crystallinity due to raw material source and variable manufacturing conditions. MCC crystallinity variability can result in downstream process variability. The aim of this study was to develop models to determine MCC crystallinity index (%CI) from Raman spectra of 30 commercial batches using Raman probes with spot sizes of 100 µm (MR probe) and 6 mm (PhAT probe). A principal component analysis model separated Raman spectra of the same samples captured using the different probes. The %CI was determined using a previously reported univariate model based on the ratio of the peaks at 380 and 1096 cm−1. The univariate model was adjusted for each probe. The %CI was also predicted from spectral data from each probe using partial least squares regression models (where Raman spectra and univariate %CI were the dependent and independent variables, respectively). Both models showed adequate predictive power. For these models a general reference amorphous spectrum was proposed for each instrument. The development of the PLS model substantially reduced the analysis time as it eliminates the need for spectral deconvolution. A web application containing all the models was developed. Graphic abstract

scholarly journals Preventive Measures for Cross Site Request Forgery Attacks on Web-based Applications

2018 ◽  
Vol 7 (4.15) ◽  
pp. 130
Author(s):  
Emil Semastin ◽  
Sami Azam ◽  
Bharanidharan Shanmugam ◽  
Krishnan Kannoorpatti ◽  
Mirjam Jonokman ◽  
...  
Keyword(s):  
Web Application ◽  
Web Applications ◽  
Operating Cycle ◽  
Web Application Security ◽  
Web Based ◽  
Business World ◽  
Application Security ◽  
Server Side ◽  
Combined Solution ◽  
Cross Site Request Forgery

Today’s contemporary business world has incorporated Web Services and Web Applications in its core of operating cycle nowadays and security plays a major role in the amalgamation of such services and applications with the business needs worldwide. OWASP (Open Web Application Security Project) states that the effectiveness of security mechanisms in a Web Application can be estimated by evaluating the degree of vulnerability against any of the nominated top ten vulnerabilities, nominated by the OWASP. This paper sheds light on a number of existing tools that can be used to test for the CSRF vulnerability. The main objective of the research is to identify the available solutions to prevent CSRF attacks. By analyzing the techniques employed in each of the solutions, the optimal tool can be identified. Tests against the exploitation of the vulnerabilities were conducted after implementing the solutions into the web application to check the efficacy of each of the solutions. The research also proposes a combined solution that integrates the passing of an unpredictable token through a hidden field and validating it on the server side with the passing of token through URL.  

Abstract TP274: Orosomucoid-1 Protein Increases Following Ischemic Stroke in the Brain and Periphery

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Hetal Mistry ◽  
Madeline Levy ◽  
Meaghan Roy-O'Reilly ◽  
Louise McCullough
Keyword(s):  
Sex Differences ◽  
Ischemic Stroke ◽  
Rna Sequencing ◽  
Multiple Testing ◽  
Enzyme Linked Immunosorbent Assay ◽  
Mrna Levels ◽  
Stroke Patients ◽  
Post Stroke ◽  
Protein Levels ◽  
The Brain

Background and Purpose: Orosomucoid-1 (ORM-1) is an abundant protein with important roles in inflammation and immunosuppression. We utilized RNA sequencing to measure mRNA levels in human ischemic stroke patients, with confirmation by serum ORM-1 protein measurements. A mouse model of ischemic stroke was then used to examine post-stroke changes in ORM-1 within the brain itself. Hypothesis: We tested the hypothesis that ORM-1 levels increase following ischemic stroke, with sex differences in protein dynamics over time. Methods: RNA sequencing was performed on whole blood from ischemic stroke patients (n=23) and controls (n=12), with Benjamini-Hochberg correction for multiple testing. Enzyme-linked immunosorbent assay was performed on serum from ischemic stroke patients (n=28) and controls (n=8), with analysis by T-test. For brain analysis, mice (n=14) were subjected to a 90-minute middle cerebral artery occlusion (MCAO) surgery and sacrificed 6 or 24 hours after stroke. Control mice underwent parallel “sham” surgery without occlusion. Western blotting was used to detect ORM-1 protein levels in whole brain, with analysis by two-way ANOVA. Results: RNA sequencing showed a 2.8-fold increase in human ORM-1 at 24 hours post-stroke (q=.0029), an increase also seen in serum ORM-1 protein levels (p=.011). Western blot analysis of mouse brain revealed that glycosylated (p=0.0003) and naive (p=0.0333) forms of ORM-1 were higher in female mice compared to males 6 hours post-stroke. Interestingly, ORM-1 levels were higher in the brains of stroke mice at 6 hours (p=.0483), while at 24 hours ORM-1 levels in stroke mice were lower than their sham counterparts (p=.0212). In both human and mouse data, no sex differences were seen in ORM-1 levels in the brain or periphery at 24 hours post-stroke. Conclusion: In conclusion, ORM-1 is a sexually dimorphic protein involved in the early (<24 hour) response to ischemic stroke. This research serves as an initial step in determining the mechanism of ORM-1 in the ischemic stroke response and its potential as a future therapeutic target for both sexes.

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