bulkAnalyseR: An accessible, interactive pipeline for analysing and sharing bulk sequencing results

Motivation: Bulk sequencing experiments are essential for exploring a wide range of biological questions. To bring data analysis closer to its interpretation, and facilitate both interactive, exploratory tasks and the sharing of easily accessible information, we present bulkAnalyseR, an R package that offers a seamless, customisable solution for most bulk RNAseq datasets. Results: In bulkAnalyseR, we integrate state-of-the-art approaches, without relying on extensive computational support. We replace static summary images with interactive panels to further strengthen the usability and interpretability of data. The package enables standard analyses on bulk sequencing output, using an expression matrix as the starting point (with the added flexibility of choosing subsets of samples). In an interactive web-based interface, steps such as quality checking, noise detection, inference of differential expression and expression patterns, and biological interpretation (enrichment analyses and identification of regulatory interactions), can be customised, easing the exploration and testing of hypotheses. Availability: bulkAnalyseR is available on GitHub, along with extensive documentation and usage examples (https://github.com/Core-Bioinformatics/bulkAnalyseR).

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Proposals on Kaplan–Meier plots in medical research and a survey of stakeholder views: KMunicate

BMJ Open ◽

10.1136/bmjopen-2019-030215 ◽

2019 ◽

Vol 9 (9) ◽

pp. e030215 ◽

Cited By ~ 4

Author(s):

Tim P Morris ◽

Christopher I Jarvis ◽

William Cragg ◽

Patrick P J Phillips ◽

Babak Choodari-Oskooei ◽

...

Keyword(s):

Outcome Measures ◽

Event Data ◽

Time To Event ◽

Web Based ◽

Time To Event Data ◽

Kaplan Meier ◽

Starting Point ◽

Wide Range ◽

International Participation ◽

Over Time

ObjectivesTo examine reactions to the proposed improvements to standard Kaplan–Meier plots, the standard way to present time-to-event data, and to understand which (if any) facilitated better depiction of (1) the state of patients over time, and (2) uncertainty over time in the estimates of survival.DesignA survey of stakeholders’ opinions on the proposals.SettingA web-based survey, open to international participation, for those with an interest in visualisation of time-to-event data.Participants1174 people participated in the survey over a 6-week period. Participation was global (although primarily Europe and North America) and represented a wide range of researchers (primarily statisticians and clinicians).Main outcome measuresTwo outcome measures were of principal importance: (1) participants’ opinions of each proposal compared with a ‘standard’ Kaplan–Meier plot; and (2) participants’ overall ranking of the proposals (including the standard).ResultsMost proposals were more popular than the standard Kaplan–Meier plot. The most popular proposals in the two categories, respectively, were an extended table beneath the plot depicting the numbers at risk, censored and having experienced an event at periodic timepoints, and CIs around each Kaplan–Meier curve.ConclusionsThis study produced a high response number, reflecting the importance of graphics for time-to-event data. Those producing and publishing Kaplan–Meier plots—both authors and journals—should, as a starting point, consider using the combination of the two favoured proposals.

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Meteo Browser South Tyrol: A Shiny App to download the meteorological time series from the Open Data Catalogue of the Province of Bolzano/Bozen - Italy

Research Ideas and Outcomes ◽

10.3897/rio.5.e35894 ◽

2019 ◽

Vol 5 ◽

Author(s):

Giulio Genova ◽

Mattia Rossi ◽

Georg Niedrist ◽

Stefano Della Chiesa

Keyword(s):

Time Series ◽

Open Data ◽

R Package ◽

Private Companies ◽

Web Based ◽

South Tyrol ◽

Wide Range ◽

Shiny App ◽

On Line ◽

User Friendly

Meteo Browser South Tyrol is a user-friendly web-based application that helps to visualize and download the hydro-meteorological time series freely available in South Tyrol, Italy. It is designed for a wide range of users, from common citizens to students as well as researchers, private companies and the public administration. Meteo Browser South Tyrol is a Shiny App inside an R package and can be used on a local machine or accessed on-line. Drop down menus allow the user to select hydro-meteorological station and measurements. A simple map shows where the monitoring stations are, the latest measurements available, and lets the user subset the selected stations geographically by drawing a polygon.

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nosoi: a stochastic agent-based transmission chain simulation framework in R

10.1101/2020.03.03.973107 ◽

2020 ◽

Author(s):

Sebastian Lequime ◽

Paul Bastide ◽

Simon Dellicour ◽

Philippe Lemey ◽

Guy Baele

Keyword(s):

Infectious Agent ◽

R Package ◽

Time Step ◽

Agent Based ◽

Transmission Chain ◽

Reconstruction Methods ◽

Extensive Documentation ◽

Wide Range ◽

Single Host ◽

Comprehensive Framework

The transmission process of an infectious agent creates a connected chain of hosts linked by transmission events, known as a transmission chain. Reconstructing transmission chains remains a challenging endeavor, except in rare cases characterized by intense surveillance and epidemiological inquiry. Inference frameworks attempt to estimate or approximate these transmission chains but the accuracy and validity of such methods generally lack formal assessment on datasets for which the actual transmission chain was observed. We here introduce nosoi, an open-source R package that offers a complete, tunable, and expandable agent-based framework to simulate transmission chains under a wide range of epidemiological scenarios for single-host and dual-host epidemics. nosoi is accessible through GitHub and CRAN, and is accompanied by extensive documentation, providing help and practical examples to assist users in setting up their own simulations. Once infected, each host or agent can undergo a series of events during each time step, such as moving (between locations) or transmitting the infection, all of these being driven by user-specified rules or data, such as travel patterns between locations. nosoi is able to generate a multitude of epidemic scenarios, that can – for example – be used to validate a wide range of reconstruction methods, including epidemic modeling and phylodynamic analyses. nosoi also offers a comprehensive framework to leverage empirically acquired data, allowing the user to explore how variations in parameters can affect epidemic potential. Aside from research questions, nosoi can provide lecturers with a complete teaching tool to offer students a handson exploration of the dynamics of epidemiological processes and the factors that impact it. Because the package does not rely on mathematical formalism but uses a more intuitive algorithmic approach, even extensive changes of the entire model can be easily and quickly implemented.

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scDD: A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

10.1101/035501 ◽

2015 ◽

Cited By ~ 4

Author(s):

Keegan D. Korthauer ◽

Li-Fang Chu ◽

Michael A. Newton ◽

Yuan Li ◽

James Thomson ◽

...

Keyword(s):

Single Cell ◽

Expression Patterns ◽

Mean Shift ◽

R Package ◽

Study Data ◽

Cellular Heterogeneity ◽

Modeling Framework ◽

Wide Range ◽

Higher Power ◽

Novel Method

AbstractThe ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. Although understanding such heterogeneity is of primary interest in a number of studies, for convenience, statistical methods often treat cellular heterogeneity as a nuisance factor. We present a novel method to characterize differences in expression in the presence of distinct expression states within and among biological conditions. Using simulated and case study data, we demonstrate that the modeling framework is able to detect differential expression patterns of interest under a wide range of settings. Compared to existing approaches, scDD has higher power to detect subtle differences in gene expression distributions that are more complex than a mean shift, and is able to characterize those differences. The freely available R package scDD implements the approach.

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Discovery of Antibacterial Agents Inhibiting the Energy-Coupling Factor (ECF) Transporters by Structure-Based Virtual Screening

10.26434/chemrxiv.11728710 ◽

2020 ◽

Author(s):

Eleonora Diamanti ◽

Inda Setyawati ◽

Spyridon Bousis ◽

leticia mojas ◽

lotteke Swier ◽

...

Keyword(s):

Virtual Screening ◽

Antibacterial Agents ◽

Antimicrobial Agents ◽

Energy Coupling ◽

Coupling Factor ◽

Design Synthesis ◽

Screening Design ◽

Starting Point ◽

Wide Range ◽

Vitamin Uptake

Here, we report on the virtual screening, design, synthesis and structure–activity relationships (SARs) of the first class of selective, antibacterial agents against the energy-coupling factor (ECF) transporters. The ECF transporters are a family of transmembrane proteins involved in the uptake of vitamins in a wide range of bacteria. Inhibition of the activity of these proteins could reduce the viability of pathogens that depend on vitamin uptake. Because of their central role in the metabolism of bacteria and their absence in humans, ECF transporters are novel potential antimicrobial targets to tackle infection. The hit compound’s metabolic and plasma stability, the potency (20, MIC Streptococcus pneumoniae = 2 µg/mL), the absence of cytotoxicity and a lack of resistance development under the conditions tested here suggest that this scaffold may represent a promising starting point for the development of novel antimicrobial agents with an unprecedented mechanism of action.<br>

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Investigating the Efficacy and Cost-Effectiveness of a Web-based Self-help Program for People With Adjustment Problems After an Accident (SelFIT): Protocol for a Randomized Controlled Trial (Preprint)

10.2196/preprints.21200 ◽

2020 ◽

Author(s):

Julia Hegy ◽

Noemi Anja Brog ◽

Thomas Berger ◽

Hansjoerg Znoj

Keyword(s):

Health Care ◽

Psychological Distress ◽

Cost Effectiveness ◽

Well Being ◽

User Friendliness ◽

Adjustment Problems ◽

Health Care Consumption ◽

Web Based ◽

Self Help ◽

Wide Range

BACKGROUND Accidents and the resulting injuries are one of the world’s biggest health care issues often causing long-term effects on psychological and physical health. With regard to psychological consequences, accidents can cause a wide range of burdens including adjustment problems. Although adjustment problems are among the most frequent mental health problems, there are few specific interventions available. The newly developed program SelFIT aims to remedy this situation by offering a low-threshold web-based self-help intervention for psychological distress after an accident. OBJECTIVE The overall aim is to evaluate the efficacy and cost-effectiveness of the SelFIT program plus care as usual (CAU) compared to only care as usual. Furthermore, the program’s user friendliness, acceptance and adherence are assessed. We expect that the use of SelFIT is associated with a greater reduction in psychological distress, greater improvement in mental and physical well-being, and greater cost-effectiveness compared to CAU. METHODS Adults (n=240) showing adjustment problems due to an accident they experienced between 2 weeks and 2 years before entering the study will be randomized. Participants in the intervention group receive direct access to SelFIT. The control group receives access to the program after 12 weeks. There are 6 measurement points for both groups (baseline as well as after 4, 8, 12, 24 and 36 weeks). The main outcome is a reduction in anxiety, depression and stress symptoms that indicate adjustment problems. Secondary outcomes include well-being, optimism, embitterment, self-esteem, self-efficacy, emotion regulation, pain, costs of health care consumption and productivity loss as well as the program’s adherence, acceptance and user-friendliness. RESULTS Recruitment started in December 2019 and is ongoing. CONCLUSIONS To the best of our knowledge, this is the first study examining a web-based self-help program designed to treat adjustment problems resulting from an accident. If effective, the program could complement the still limited offer of secondary and tertiary psychological prevention after an accident. CLINICALTRIAL ClinicalTrials.gov NCT03785912; https://clinicaltrials.gov/ct2/show/NCT03785912?cond=NCT03785912&draw=2&rank=1

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NoRCE: non-coding RNA sets cis enrichment tool

BMC Bioinformatics ◽

10.1186/s12859-021-04112-9 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Gulden Olgun ◽

Afshan Nabi ◽

Oznur Tastan

Keyword(s):

Expression Patterns ◽

Target Prediction ◽

Enrichment Analysis ◽

Fruit Fly ◽

Relevant Information ◽

R Package ◽

Data Repository ◽

Biologically Relevant ◽

Gene Sets ◽

Data Files

Abstract Background While some non-coding RNAs (ncRNAs) are assigned critical regulatory roles, most remain functionally uncharacterized. This presents a challenge whenever an interesting set of ncRNAs needs to be analyzed in a functional context. Transcripts located close-by on the genome are often regulated together. This genomic proximity on the sequence can hint at a functional association. Results We present a tool, NoRCE, that performs cis enrichment analysis for a given set of ncRNAs. Enrichment is carried out using the functional annotations of the coding genes located proximal to the input ncRNAs. Other biologically relevant information such as topologically associating domain (TAD) boundaries, co-expression patterns, and miRNA target prediction information can be incorporated to conduct a richer enrichment analysis. To this end, NoRCE includes several relevant datasets as part of its data repository, including cell-line specific TAD boundaries, functional gene sets, and expression data for coding & ncRNAs specific to cancer. Additionally, the users can utilize custom data files in their investigation. Enrichment results can be retrieved in a tabular format or visualized in several different ways. NoRCE is currently available for the following species: human, mouse, rat, zebrafish, fruit fly, worm, and yeast. Conclusions NoRCE is a platform-independent, user-friendly, comprehensive R package that can be used to gain insight into the functional importance of a list of ncRNAs of any type. The tool offers flexibility to conduct the users’ preferred set of analyses by designing their own pipeline of analysis. NoRCE is available in Bioconductor and https://github.com/guldenolgun/NoRCE.

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Epidemiological modeling in StochSS Live!

Bioinformatics ◽

10.1093/bioinformatics/btab061 ◽

2021 ◽

Author(s):

Richard Jiang ◽

Bruno Jacob ◽

Matthew Geiger ◽

Sean Matthew ◽

Bryan Rumsey ◽

...

Keyword(s):

Stochastic Model ◽

Epidemiological Model ◽

Supplementary Information ◽

Supplementary Data ◽

Web Based ◽

Epidemiological Modeling ◽

Modeling Simulation ◽

Wide Range ◽

Biochemical Systems

Abstract Summary We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results. Availability and implementation StochSS Live! is freely available at https://live.stochss.org/ Supplementary information Supplementary data are available at Bioinformatics online.

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BloodGen3Module: Blood transcriptional module repertoire analysis and visualization using R

Bioinformatics ◽

10.1093/bioinformatics/btab121 ◽

2021 ◽

Author(s):

Darawan Rinchai ◽

Jessica Roelands ◽

Mohammed Toufiq ◽

Wouter Hendrickx ◽

Matthew C Altman ◽

...

Keyword(s):

Transcript Abundance ◽

R Package ◽

Supplementary Information ◽

Illustrative Case ◽

Bioinformatic Tools ◽

Transcriptional Module ◽

Wide Range ◽

Downstream Analysis ◽

Computing Module ◽

Parallel Workflow

Abstract Motivation We previously described the construction and characterization of generic and reusable blood transcriptional module repertoires. More recently we released a third iteration (“BloodGen3” module repertoire) that comprises 382 functionally annotated gene sets (modules) and encompasses 14,168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires. Results We have developed and describe here a R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states. Availability The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module Supplementary information Supplementary data are available at Bioinformatics online.

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Consumer Neuroscience Techniques in Advertising Research: A Bibliometric Citation Analysis

Sustainability ◽

10.3390/su13031589 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1589

Author(s):

Juan Sánchez-Fernández ◽

Luis-Alberto Casado-Aranda ◽

Ana-Belén Bastidas-Manzano

Keyword(s):

Self Report ◽

Future Research ◽

Complex Nature ◽

Clear Understanding ◽

Continuous Growth ◽

Main Research ◽

Consumer Neuroscience ◽

Starting Point ◽

Wide Range ◽

Performance Analysis Tools

The limitations of self-report techniques (i.e., questionnaires or surveys) in measuring consumer response to advertising stimuli have necessitated more objective and accurate tools from the fields of neuroscience and psychology for the study of consumer behavior, resulting in the creation of consumer neuroscience. This recent marketing sub-field stems from a wide range of disciplines and applies multiple types of techniques to diverse advertising subdomains (e.g., advertising constructs, media elements, or prediction strategies). Due to its complex nature and continuous growth, this area of research calls for a clear understanding of its evolution, current scope, and potential domains in the field of advertising. Thus, this current research is among the first to apply a bibliometric approach to clarify the main research streams analyzing advertising persuasion using neuroimaging. Particularly, this paper combines a comprehensive review with performance analysis tools of 203 papers published between 1986 and 2019 in outlets indexed by the ISI Web of Science database. Our findings describe the research tools, journals, and themes that are worth considering in future research. The current study also provides an agenda for future research and therefore constitutes a starting point for advertising academics and professionals intending to use neuroimaging techniques.

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