Shiny-SoSV: A web-based performance calculator for somatic structural variant detection

Mapping Intimacies ◽

10.1101/668723 ◽

2019 ◽

Author(s):

Tingting Gong ◽

Vanessa M Hayes ◽

Eva KF Chan

Keyword(s):

Study Design ◽

Additive Model ◽

Whole Genome Sequencing Data ◽

Sequencing Data ◽

Web Based ◽

Generalised Additive Model ◽

Structural Variant ◽

Variant Detection ◽

User Friendly ◽

The Impact

AbstractSomatic structural variants are an important contributor to cancer development and evolution. Accurate detection of these complex variants from whole genome sequencing data is influenced by a multitude of parameters. However, there are currently no tools for guiding study design nor are there applications that could predict the performance of somatic structural variant detection. To address this gap, we developed Shiny-SoSV, a user-friendly web-based calculator for determining the impact of common variables on the sensitivity and precision of somatic structural variant detection, including choice of variant detection tool, sequencing depth of coverage, variant allele fraction, and variant breakpoint resolution. Using simulation studies, we determined singular and combinatoric effects of these variables, modelled the results using a generalised additive model, allowing structural variant detection performance to be predicted for any combination of predictors. Shiny-SoSV provides an interactive and visual platform for users to easily compare individual and combined impact of different parameters. It predicts the performance of a proposed study design, on somatic structural variant detection, prior to the commencement of benchwork. Shiny-SoSV is freely available at https://hcpcg.shinyapps.io/Shiny-SoSV with accompanying user’s guide and example use-cases.

Download Full-text

The Role of Web Based Accounting Online System 2.0 as the Company's Income and Expense Management

Aptisi Transactions on Management (ATM) ◽

10.33050/atm.v1i1.655 ◽

2017 ◽

Vol 1 (1) ◽

pp. 44-49

Author(s):

Nur Azizah ◽

Dedeh Supriyanti ◽

Siti Fairuz Aminah Mustapha ◽

Holly Yang

Keyword(s):

Financial Management ◽

Accounting System ◽

Bank Account ◽

Web Based ◽

Online System ◽

Version 2.0 ◽

User Friendly ◽

The Impact ◽

A Company

In a company, the process of income and expense of money must have a profit-generating goal base. The success of financial management within the company, can be monitored from the ability of the financial management in managing the finances and utilize all the opportunities that exist with as much as possible with the aim to control the company's cash (cash flow) and the impact of generating profits in accordance with expectations. With a web-based online accounting system version 2.0, companies can be given the ease to manage money in and out of the company's cash. It has a user friendly system with navigation that makes it easy for the financial management to use it. Starting from the creation of a company's cash account used as a cash account and corporate bank account on the system, deletion or filing of cash accounts, up to the transfer invoice creation feature, receive and send money. Thus, this system is very effective and efficient in the management of income and corporate cash disbursements. Keywords:Accounting Online System, Financial Management, Cash and Bank

Download Full-text

Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants

Journal of Personalized Medicine ◽

10.3390/jpm11020131 ◽

2021 ◽

Vol 11 (2) ◽

pp. 131

Author(s):

Laura B. Scheinfeldt ◽

Andrew Brangan ◽

Dara M. Kusic ◽

Sudhir Kumar ◽

Neda Gharani

Keyword(s):

In Silico ◽

Drug Efficacy ◽

Common Variant ◽

Genomic Research ◽

Whole Genome Sequencing Data ◽

Mendelian Disease ◽

Allele Frequency Distribution ◽

Sequencing Data ◽

Patient Race ◽

The Impact

Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new ‘common treatment, common variant’ perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX’s in silico predictions.

Download Full-text

The Impact of the Internet in Twenty-First Century Addictions

Internet and Technology Addiction ◽

10.4018/978-1-5225-8900-6.ch025 ◽

2019 ◽

pp. 436-454

Author(s):

Shilpa Suresh Bisen ◽

Yogesh Deshpande

Keyword(s):

Psychiatric Disorders ◽

Illicit Drugs ◽

Cost Effective ◽

First Century ◽

Online Gambling ◽

The Internet ◽

Web Based ◽

Positive Side ◽

User Friendly ◽

The Impact

In the era of digital technology, the internet has its significant role in sprouting vulnerability toward the different form of addictions and psychiatric disorders as well as providing the platform to manage them effectively. The internet provides ready access to illicit drugs, nonprescription medications which facilitate a sale of controlled substances over the Internet without a valid prescription which contributed to the rise of several forms of addictions. Studies have linked the severity of Problematic Internet Use to increase chances of substance Use disorder. Utilization of internet for longer durations serves as a booster for behavioral addictions like online gambling. Web based interventions on the positive side provides a cost effective, readily accessible and user-friendly platform to reach out majority of patients to help them in seeking treatment of Addictions and various psychiatric disorders. The aim of this chapter is to discuss the contribution of the internet in a positive and negative way to develop as well as resolve Psychiatric disorder.

Download Full-text

Seven novel glucose-6-phosphate dehydrogenase (G6PD) deficiency variants identified in the Qatari population

Human Genomics ◽

10.1186/s40246-021-00358-9 ◽

2021 ◽

Vol 15 (1) ◽

Author(s):

Shaza Malik ◽

Roan Zaied ◽

Najeeb Syed ◽

Puthen Jithesh ◽

Mashael Al-Shafai

Keyword(s):

Protein Function ◽

World Health ◽

Whole Genome Sequencing Data ◽

The Novel ◽

Class Iii ◽

Sequencing Data ◽

Novel Variants ◽

The World ◽

Glucose 6 Phosphate Dehydrogenase ◽

The Impact

Abstract Background Glucose-6-phosphate dehydrogenase deficiency (G6PDD) is the most common red cell enzymopathy in the world. In Qatar, the incidence of G6PDD is estimated at around 5%; however, no study has investigated the genetic basis of G6PDD in the Qatari population yet. Methods In this study, we analyzed whole-genome sequencing data generated by the Qatar Genome Programme for 6045 Qatar Biobank participants, to identify G6PDD variants in the Qatari population. In addition, we assessed the impact of the novel variants identified on protein function both in silico and by measuring G6PD enzymatic activity in the subjects carrying them. Results We identified 375 variants in/near G6PD gene, of which 20 were high-impact and 16 were moderate-impact variants. Of these, 14 were known G6PDD-causing variants. The most frequent G6PD-causing variants found in the Qatari population were p.Ser188Phe (G6PD Mediterranean), p.Asn126Asp (G6PD A +), p.Val68Met (G6PD Asahi), p.Ala335Thr (G6PD Chatham), and p.Ile48Thr (G6PD Aures) with allele frequencies of 0.0563, 0.0194, 0.00785, 0.0050, and 0.00380, respectively. Furthermore, we have identified seven novel G6PD variants, all of which were confirmed as G6PD-causing variants and classified as class III variants based on the World Health Organization’s classification scheme. Conclusions This is the first study investigating the molecular basis of G6PDD in Qatar, and it provides novel insights about G6PDD pathogenesis and highlights the importance of studying such understudied population.

Download Full-text

Drug offence detection during the COVID-19 lockdown: a spatiotemporal study of change in a street-level drug market

10.31235/osf.io/2x53n ◽

2021 ◽

Author(s):

Jason Leslie Payne ◽

Cameron Thomas Langfield

Keyword(s):

Additive Model ◽

Drug Market ◽

Future Research ◽

Generalised Additive Model ◽

Train Station ◽

Street Level ◽

Drug Offence ◽

Crime Types ◽

The Impact ◽

North And South

The COVID-19 pandemic and the subsequent introduction of strict government orders to `stay-at-home' has led to a significant decline in most crime types--except, notably, illicit drug detections. However, the impact of these restrictions on open-air, or street-level, drug markets has been neglected in the study of COVID-19. In this paper, we use data from the state of Queensland, Australia, to explore how COVID-19 restrictions may have impacted the open-air drug market of Fortitude Valley in Brisbane. Using a spatiotemporal generalised additive model (GAM), we find that drug detections did not change in the Fortitude Valley region (despite significant increases across the whole state) but that this finding masked considerable reductions in and around the Fortitude Valley train station as well as in the vicinity Brunswick Street mall. It seems that any COVID-19-related decrease appears to have been offset by increases elsewhere, particularly to the streets north and south west of the main street market. These results highlight the limitations of city-wide aggregate analyses of crime during the pandemic and highlights the need for future research, including with qualitative and ethnographic methods to better understand the lived experiences of drug sellers/users and the law enforcement officers who policed these areas.

Download Full-text

The impact of rare variation on gene expression across tissues

10.1101/074443 ◽

2016 ◽

Cited By ~ 10

Author(s):

Xin Li ◽

Yungil Kim ◽

Emily K. Tsang ◽

Joe R. Davis ◽

Farhan N. Damani ◽

...

Keyword(s):

Gene Expression ◽

Rare Variants ◽

Disease Risk ◽

Whole Genome Sequencing Data ◽

Personal Genome ◽

Sequencing Data ◽

Potential Health ◽

Rare Variation ◽

Functional Variants ◽

The Impact

AbstractRare genetic variants are abundant in humans yet their functional effects are often unknown and challenging to predict. The Genotype-Tissue Expression (GTEx) project provides a unique opportunity to identify the functional impact of rare variants through combined analyses of whole genomes and multi-tissue RNA-sequencing data. Here, we identify gene expression outliers, or individuals with extreme expression levels, across 44 human tissues, and characterize the contribution of rare variation to these large changes in expression. We find 58% of underexpression and 28% of overexpression outliers have underlying rare variants compared with 9% of non-outliers. Large expression effects are enriched for proximal loss-of-function, splicing, and structural variants, particularly variants near the TSS and at evolutionarily conserved sites. Known disease genes have expression outliers, underscoring that rare variants can contribute to genetic disease risk. To prioritize functional rare regulatory variants, we develop RIVER, a Bayesian approach that integrates RNA and whole genome sequencing data from the same individual. RIVER predicts functional variants significantly better than models using genomic annotations alone, and is an extensible tool for personal genome interpretation. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues with potential health consequences, and provide an integrative method for interpreting rare variants in individual genomes.

Download Full-text

MutantHuntWGS: A Pipeline for Identifying Saccharomyces cerevisiae Mutations

G3 Genes|Genome|Genetics ◽

10.1534/g3.120.401396 ◽

2020 ◽

Vol 10 (9) ◽

pp. 3009-3014 ◽

Cited By ~ 1

Author(s):

Mitchell A Ellison ◽

Jennifer L Walker ◽

Patrick J Ropp ◽

Jacob D Durrant ◽

Karen M Arndt

Keyword(s):

Saccharomyces Cerevisiae ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Sequence Alignments ◽

Causal Variants ◽

User Friendly ◽

Analyze Data

Abstract MutantHuntWGS is a user-friendly pipeline for analyzing Saccharomyces cerevisiae whole-genome sequencing data. It uses available open-source programs to: (1) perform sequence alignments for paired and single-end reads, (2) call variants, and (3) predict variant effect and severity. MutantHuntWGS outputs a shortlist of variants while also enabling access to all intermediate files. To demonstrate its utility, we use MutantHuntWGS to assess multiple published datasets; in all cases, it detects the same causal variants reported in the literature. To encourage broad adoption and promote reproducibility, we distribute a containerized version of the MutantHuntWGS pipeline that allows users to install and analyze data with only two commands. The MutantHuntWGS software and documentation can be downloaded free of charge from https://github.com/mae92/MutantHuntWGS.

Download Full-text

Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection

International Journal of Molecular Sciences ◽

10.3390/ijms21155585 ◽

2020 ◽

Vol 21 (15) ◽

pp. 5585

Author(s):

Mathieu Gand ◽

Kevin Vanneste ◽

Isabelle Thomas ◽

Steven Van Gucht ◽

Arnaud Capron ◽

...

Keyword(s):

In Silico ◽

Protein S ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Viral Genomes ◽

Genome Data ◽

Gene Coding ◽

Control And Prevention ◽

The Impact

The current COronaVIrus Disease 2019 (COVID-19) pandemic started in December 2019. COVID-19 cases are confirmed by the detection of SARS-CoV-2 RNA in biological samples by RT-qPCR. However, limited numbers of SARS-CoV-2 genomes were available when the first RT-qPCR methods were developed in January 2020 for initial in silico specificity evaluation and to verify whether the targeted loci are highly conserved. Now that more whole genome data have become available, we used the bioinformatics tool SCREENED and a total of 4755 publicly available SARS-CoV-2 genomes, downloaded at two different time points, to evaluate the specificity of 12 RT-qPCR tests (consisting of a total of 30 primers and probe sets) used for SARS-CoV-2 detection and the impact of the virus’ genetic evolution on four of them. The exclusivity of these methods was also assessed using the human reference genome and 2624 closely related other respiratory viral genomes. The specificity of the assays was generally good and stable over time. An exception is the first method developed by the China Center for Disease Control and prevention (CDC), which exhibits three primer mismatches present in 358 SARS-CoV-2 genomes sequenced mainly in Europe from February 2020 onwards. The best results were obtained for the assay of Chan et al. (2020) targeting the gene coding for the spiking protein (S). This demonstrates that our user-friendly strategy can be used for a first in silico specificity evaluation of future RT-qPCR tests, as well as verifying that the former methods are still capable of detecting circulating SARS-CoV-2 variants.

Download Full-text