Modern simulation utilities for genetic analysis

Abstract Background Statistical geneticists employ simulation to estimate the power of proposed studies, test new analysis tools, and evaluate properties of causal models. Although there are existing trait simulators, there is ample room for modernization. For example, most phenotype simulators are limited to Gaussian traits or traits transformable to normality, while ignoring qualitative traits and realistic, non-normal trait distributions. Also, modern computer languages, such as Julia, that accommodate parallelization and cloud-based computing are now mainstream but rarely used in older applications. To meet the challenges of contemporary big studies, it is important for geneticists to adopt new computational tools. Results We present , an open-source Julia package that makes it trivial to quickly simulate phenotypes under a variety of genetic architectures. This package is integrated into our OpenMendel suite for easy downstream analyses. Julia was purpose-built for scientific programming and provides tremendous speed and memory efficiency, easy access to multi-CPU and GPU hardware, and to distributed and cloud-based parallelization. is designed to encourage flexible trait simulation, including via the standard devices of applied statistics, generalized linear models (GLMs) and generalized linear mixed models (GLMMs). also accommodates many study designs: unrelateds, sibships, pedigrees, or a mixture of all three. (Of course, for data with pedigrees or cryptic relationships, the simulation process must include the genetic dependencies among the individuals.) We consider an assortment of trait models and study designs to illustrate integrated simulation and analysis pipelines. Step-by-step instructions for these analyses are available in our electronic Jupyter notebooks on Github. These interactive notebooks are ideal for reproducible research. Conclusion The package has three main advantages. (1) It leverages the computational efficiency and ease of use of Julia to provide extremely fast, straightforward simulation of even the most complex genetic models, including GLMs and GLMMs. (2) It can be operated entirely within, but is not limited to, the integrated analysis pipeline of OpenMendel. And finally (3), by allowing a wider range of more realistic phenotype models, brings power calculations and diagnostic tools closer to what investigators might see in real-world analyses.

Download Full-text

Direct-RT-qPCR Detection of SARS-CoV-2 without RNA Extraction as Part of a COVID-19 Testing Strategy: From Sample to Result in One Hour

Diagnostics ◽

10.3390/diagnostics10080605 ◽

2020 ◽

Vol 10 (8) ◽

pp. 605 ◽

Cited By ~ 3

Author(s):

Eva Kriegova ◽

Regina Fillerova ◽

Petr Kvapil

Keyword(s):

High Throughput Screening ◽

High Speed ◽

Limit Of Detection ◽

Point Of Care ◽

Rna Extraction ◽

Rna Isolation ◽

High Sensitivity ◽

Ease Of Use ◽

Diagnostic Tools ◽

Heat Inactivation

Due to the lack of protective immunity in the general population and the absence of effective antivirals and vaccines, the Coronavirus disease 2019 (COVID-19) pandemic continues in some countries, with local epicentres emerging in others. Due to the great demand for effective COVID-19 testing programmes to control the spread of the disease, we have suggested such a testing programme that includes a rapid RT-qPCR approach without RNA extraction. The Direct-One-Step-RT-qPCR (DIOS-RT-qPCR) assay detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in less than one hour while maintaining the high sensitivity and specificity required of diagnostic tools. This optimised protocol allows for the direct use of swab transfer media (14 μL) without the need for RNA extraction, achieving comparable sensitivity to the standard method that requires the time-consuming and costly step of RNA isolation. The limit of detection for DIOS-RT-qPCR was lower than seven copies/reaction, which translates to 550 virus copies/mL of swab. The speed, ease of use and low price of this assay make it suitable for high-throughput screening programmes. The use of fast enzymes allows RT-qPCR to be performed under standard laboratory conditions within one hour, making it a potential point-of-care solution on high-speed cycling instruments. This protocol also implements the heat inactivation of SARS-CoV-2 (75 °C for 10 min), which renders samples non-infectious, enabling testing in BSL-2 facilities. Moreover, we discuss the critical steps involved in developing tests for the rapid detection of COVID-19. Implementing rapid, easy, cost-effective methods can help control the worldwide spread of the COVID-19 infection.

Download Full-text

Quantitative Performance Analysis of the SPEC OMPM2001 Benchmarks

Scientific Programming ◽

10.1155/2003/401032 ◽

2003 ◽

Vol 11 (2) ◽

pp. 105-124 ◽

Cited By ~ 12

Author(s):

Vishal Aslot ◽

Rudolf Eigenmann

Keyword(s):

Shared Memory ◽

Parallel Computers ◽

Quantitative Model ◽

Modern Architecture ◽

Easy Access ◽

Multiprocessor Systems ◽

Modern Computer ◽

Multiple Processors ◽

Quantitative Performance ◽

Shared Memory Multiprocessor

The state of modern computer systems has evolved to allow easy access to multiprocessor systems by supporting multiple processors on a single physical package. As the multiprocessor hardware evolves, new ways of programming it are also developed. Some inventions may merely be adopting and standardizing the older paradigms. One such evolving standard for programming shared-memory parallel computers is the OpenMP API. The Standard Performance Evaluation Corporation (SPEC) has created a suite of parallel programs called SPEC OMP to compare and evaluate modern shared-memory multiprocessor systems using the OpenMP standard. We have studied these benchmarks in detail to understand their performance on a modern architecture. In this paper, we present detailed measurements of the benchmarks. We organize, summarize, and display our measurements using a Quantitative Model. We present a detailed discussion and derivation of the model. Also, we discuss the important loops in the SPEC OMPM2001 benchmarks and the reasons for less than ideal speedup on our platform.

Download Full-text

Applications of a Decomposed Analysis Procedure for Area-Array Packages

Journal of Electronic Packaging ◽

10.1115/1.1339197 ◽

2000 ◽

Vol 123 (2) ◽

pp. 132-140

Author(s):

Terrace B. Thompson ◽

Ganesh Subbarayan

Keyword(s):

Mechanical Energy ◽

Three Dimensional ◽

Optimization Procedure ◽

Computer Code ◽

Analysis Procedure ◽

Object Oriented Programming ◽

Electronic Packages ◽

Computer Languages ◽

Modern Computer ◽

Independent Analysis

The goals of the present paper are to apply the recently developed decomposed analysis procedure using a computer code developed in this study. The decomposed technique enables one to determine the equilibrium configuration of electronic packages with significant computational efficiency at a reasonable accuracy. Further, it allows the independent analysis of the subsystems enabling “reusable” modules in a manner analogous to the object-oriented programming paradigm of modern computer languages. The code described here uses a nonlinear optimization procedure that ensures the approximate satisfaction of the balance of mechanical energy. The developed procedure is demonstrated on a variety of two- and three-dimensional hypothetical and “real-world” electronic packages. It is shown that with the use of the decomposed solution methodology, for a 225 I/O PBGA package, a speedup of nearly seven times is achieved at an accuracy loss in displacements of approximately 5.5 percent. It is also shown that the calculated peak shear displacements agree very well with experimental measurements made using laser moire´ interferometry. Since the analysis procedure is independent of the number of solder interconnects, significantly larger time savings are expected for larger packages.

Download Full-text

NanoGalaxy: Nanopore long-read sequencing data analysis in Galaxy

GigaScience ◽

10.1093/gigascience/giaa105 ◽

2020 ◽

Vol 9 (10) ◽

Cited By ~ 1

Author(s):

Willem de Koning ◽

Milad Miladi ◽

Saskia Hiltemann ◽

Astrid Heikema ◽

John P Hays ◽

...

Keyword(s):

Genome Assembly ◽

Bioinformatics Analysis ◽

De Novo ◽

Sequence Data ◽

Ease Of Use ◽

Easy Access ◽

Complex Data ◽

Sequencing Data ◽

Long Read ◽

Sequencing Platforms

Abstract Background Long-read sequencing can be applied to generate very long contigs and even completely assembled genomes at relatively low cost and with minimal sample preparation. As a result, long-read sequencing platforms are becoming more popular. In this respect, the Oxford Nanopore Technologies–based long-read sequencing “nanopore" platform is becoming a widely used tool with a broad range of applications and end-users. However, the need to explore and manipulate the complex data generated by long-read sequencing platforms necessitates accompanying specialized bioinformatics platforms and tools to process the long-read data correctly. Importantly, such tools should additionally help democratize bioinformatics analysis by enabling easy access and ease-of-use solutions for researchers. Results The Galaxy platform provides a user-friendly interface to computational command line–based tools, handles the software dependencies, and provides refined workflows. The users do not have to possess programming experience or extended computer skills. The interface enables researchers to perform powerful bioinformatics analysis, including the assembly and analysis of short- or long-read sequence data. The newly developed “NanoGalaxy" is a Galaxy-based toolkit for analysing long-read sequencing data, which is suitable for diverse applications, including de novo genome assembly from genomic, metagenomic, and plasmid sequence reads. Conclusions A range of best-practice tools and workflows for long-read sequence genome assembly has been integrated into a NanoGalaxy platform to facilitate easy access and use of bioinformatics tools for researchers. NanoGalaxy is freely available at the European Galaxy server https://nanopore.usegalaxy.eu with supporting self-learning training material available at https://training.galaxyproject.org.

Download Full-text

Accessible and reproducible mass spectrometry imaging data analysis in Galaxy

10.1101/628719 ◽

2019 ◽

Author(s):

Melanie Christine Föll ◽

Lennart Moritz ◽

Thomas Wollmann ◽

Maren Nicole Stillger ◽

Niklas Vockert ◽

...

Keyword(s):

Mass Spectrometry ◽

Data Analysis ◽

Mass Spectrometry Imaging ◽

Ease Of Use ◽

Reproducible Research ◽

Data Sets ◽

Imaging Data ◽

Available N ◽

The Galaxy ◽

Analysis Platform

AbstractBackgroundMass spectrometry imaging is increasingly used in biological and translational research as it has the ability to determine the spatial distribution of hundreds of analytes in a sample. Being at the interface of proteomics/metabolomics and imaging, the acquired data sets are large and complex and often analyzed with proprietary software or in-house scripts, which hinder reproducibility. Open source software solutions that enable reproducible data analysis often require programming skills and are therefore not accessible to many MSI researchers.FindingsWe have integrated 18 dedicated mass spectrometry imaging tools into the Galaxy framework to allow accessible, reproducible, and transparent data analysis. Our tools are based on Cardinal, MALDIquant, and scikit-image and enable all major MSI analysis steps such as quality control, visualization, preprocessing, statistical analysis, and image co-registration. Further, we created hands-on training material for use cases in proteomics and metabolomics. To demonstrate the utility of our tools, we re-analyzed a publicly available N-linked glycan imaging dataset. By providing the entire analysis history online, we highlight how the Galaxy framework fosters transparent and reproducible research.ConclusionThe Galaxy framework has emerged as a powerful analysis platform for the analysis of MSI data with ease of use and access together with high levels of reproducibility and transparency.

Download Full-text

A global omics data sharing and analytics marketplace: Case study of a rapid data COVID-19 pandemic response platform

10.1101/2020.09.28.20203257 ◽

2020 ◽

Author(s):

Ibrahim Farah ◽

Giada Lalli ◽

Darrol Baker ◽

Axel Schumacher

Keyword(s):

Data Sharing ◽

Biomarker Discovery ◽

Disease Outbreaks ◽

Ease Of Use ◽

Diagnostic Tools ◽

Data Sets ◽

Omics Data ◽

Host Interactions ◽

Healthcare Data ◽

Global Pandemic

AbstractUnder public health emergencies, particularly an early epidemic, it is fundamental that genetic and other healthcare data is shared across borders in both a timely and accurate manner before the outbreak of a global pandemic. However, although the COVID-19 pandemic has created a tidal wave of data, most patient data is siloed, not easily accessible, and due to low sample size, largely not actionable. Based on the precision medicine platform Shivom, a novel and secure data sharing and data analytics marketplace, we developed a versatile pandemic preparedness platform that allows healthcare professionals to rapidly share and analyze genetic data. The platform solves several problems of the global medical and research community, such as siloed data, cross-border data sharing, lack of state-of-the-art analytic tools, GDPR-compliance, and ease-of-use. The platform serves as a central marketplace of ‘discoverability’. The platform combines patient genomic & omics data sets, a marketplace for AI & bioinformatics algorithms, new diagnostic tools, and data-sharing capabilities to advance virus epidemiology and biomarker discovery. The bioinformatics marketplace contains some preinstalled COVID-19 pipelines to analyze virus- and host genomes without the need for bioinformatics expertise. The platform will be the quickest way to rapidly gain insight into the association between virus-host interactions and COVID-19 in various populations which can have a significant impact on managing the current pandemic and potential future disease outbreaks.

Download Full-text

Automation Overcoming Crippling

International Journal of Advanced Research in Science, Communication and Technology ◽

10.48175/ijarsct-1600 ◽

2021 ◽

pp. 82-86

Author(s):

Mohit Solanki ◽

Muskan ◽

Heena ◽

Muskan Mehta ◽

Bhuvnesh Chaturvedi

Keyword(s):

Signal Transmission ◽

Smart Phone ◽

Ease Of Use ◽

Remote Access ◽

Easy Access ◽

Automation System ◽

Home Automation ◽

Android Os ◽

Home Automation System ◽

And Control

The main purpose of this paper is to improve the automation system at home using the Arduino keyboard with Bluetooth controlled by any Android OS smart phone. Technology and electronics have become commonplace in the last year of technology. In this paper, we present the design and implementation of the Home Automation System in conjunction with Home Housing and the best features of home automation with remote access. In this research project part of the smart home technology, Bluetooth on a smart phone is used, so it is cheap and usable. The app includes four main features: an Arduino keyboard, a Bluetooth signal transmission module, a music speaker and an Android-powered smartphone to control devices. By using the smart phone app, we can control household items and provide security to deter people. The idea of paper is to control household items to avoid the risk of electric shock and ease of use for people with disabilities who have easy access and control of household items by staying in a certain place.

Download Full-text

Crossing the Line to Electronic Medical Records in Subsaharian Africa: An Obstetric and Neonatal Information System with Perinatal Indicators Dashboard

Journal of Health Science Research ◽

10.18311/jhsr/2017/15932 ◽

2017 ◽

Vol 2 (1) ◽

pp. 14 ◽

Cited By ~ 1

Author(s):

M. Gueye ◽

Md Ndiaye Gueye ◽

M. Mbaye ◽

M. Abdoulaye ◽

A. Diouf ◽

...

Keyword(s):

Information System ◽

Medical Record ◽

Electronic Medical Record ◽

Ad Hoc ◽

Hospital Admissions ◽

Health Centre ◽

Neonatal Care ◽

Ease Of Use ◽

Easy Access ◽

Level Ii

Objectives: This study reports our experience in the use of a perinatal electronic medical record, E_Perinatal, by giving examples of its potential for the analysis of clinical data and the involvement of the indicators produced in the improvement of Emergency Obstetric and Neonatal Care in Africa. Methodology: This is a study that was conducted in the scenario of a Level II Health Centre in Senegal. The methodology of the study followed the following steps: an inventory of the use of electronic tools in labour wards in Senegal, an exploratory survey of the scenario of obstetric and neonatal care, simultaneous elaboration of an electronic medical record in obstetrics and neonatology and selection of obstetric and neonatal care indicators to automatically generated and implement the information system. The recording was retrospective and continuous from January 2015 to December 2016. Results: This database automates the storage of obstetric data, including antenatal care, obstetric ultrasound, hospital admissions, prescribing, etc., providing easy access to patient data from anywhere in the hospital, produce timely reports and graphs to refer to clinician correspondents, store and electronically transfer birth data to authorities, and store data for ad hoc queries and search statistics. Conclusion: E_Perinatal has demonstrated in a scenario of an intermediate health facility its usefulness and ease of use. Scaling up in a developing country will help to better understand the real problems and help to reduce maternal and neonatal mortality.

Download Full-text

Global Research on Coronaviruses: An R Package

Journal of Medical Internet Research ◽

10.2196/19615 ◽

2020 ◽

Vol 22 (8) ◽

pp. e19615

Author(s):

Thierry Warin

Keyword(s):

Scientific Information ◽

R Package ◽

Open Science ◽

Research Network ◽

Reproducible Research ◽

Easy Access ◽

Multidisciplinary Research ◽

Data Set ◽

R Language ◽

Similarity Indices

Background In these trying times, we developed an R package about bibliographic references on coronaviruses. Working with reproducible research principles based on open science, disseminating scientific information, providing easy access to scientific production on this particular issue, and offering a rapid integration in researchers’ workflows may help save time in this race against the virus, notably in terms of public health. Objective The goal is to simplify the workflow of interested researchers, with multidisciplinary research in mind. With more than 60,500 medical bibliographic references at the time of publication, this package is among the largest about coronaviruses. Methods This package could be of interest to epidemiologists, researchers in scientometrics, biostatisticians, as well as data scientists broadly defined. This package collects references from PubMed and organizes the data in a data frame. We then built functions to sort through this collection of references. Researchers can also integrate the data into their pipeline and implement them in R within their code libraries. Results We provide a short use case in this paper based on a bibliometric analysis of the references made available by this package. Classification techniques can also be used to go through the large volume of references and allow researchers to save time on this part of their research. Network analysis can be used to filter the data set. Text mining techniques can also help researchers calculate similarity indices and help them focus on the parts of the literature that are relevant for their research. Conclusions This package aims at accelerating research on coronaviruses. Epidemiologists can integrate this package into their workflow. It is also possible to add a machine learning layer on top of this package to model the latest advances in research about coronaviruses, as we update this package daily. It is also the only one of this size, to the best of our knowledge, to be built in the R language.

Download Full-text

Evaluation of the diagnostic accuracy of a new point-of-care rapid test for SARS-CoV-2 virus detection

10.21203/rs.3.rs-100047/v1 ◽

2020 ◽

Author(s):

Leonardo Miscio ◽

Antonio Olivieri ◽

Francesco Labonia ◽

Gianfranco De Feo ◽

Paolo Chiodini ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Real Time ◽

Real Time Pcr ◽

Point Of Care ◽

Virus Detection ◽

Rapid Test ◽

Reference Method ◽

Standard Of Care ◽

Easy Access ◽

Diagnostic Tools

Abstract Background: The easy access to a quick diagnosis of coronavirus disease 2019 (COVID-19) is a key point to improve the management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to contain its spread. Up to now, laboratory real-time PCR is the standard of care, but requires a fully equipped laboratory and significant infrastructure. Consequently, new diagnostic tools are required. Methods: In the present work, the diagnostic accuracy of the point-of-care rapid test "bKIT Virus Finder COVID-19" (Hyris Ltd) is evaluated by a retrospective and a prospective analysis on SARS CoV-2 samples previously assessed with an FDA “authorized for the emergency use - EUA” reference method. Descriptive statistics were used for the present study.Results: Results obtained with the Hyris Kit are the same as that of standard laboratory-based real time PCR methods for all the analyzed samples. In addition, the Hyris Kit provides the test results in less than 2 hours, a significantly shorter time compared to the reference methods, without the need of a fully equipped laboratory. Conclusions: To conclude, the Hyris kit represents a promising tool to improve the health surveillance and to increase the capacity of SARS-CoV-2 testing.

Download Full-text