scholarly journals Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets

2019 ◽  
Vol 10 ◽  
Author(s):  
Pablo Ivan Pereira Ramos ◽  
Luis Willian Pacheco Arge ◽  
Nicholas Costa Barroso Lima ◽  
Kiyoshi F. Fukutani ◽  
Artur Trancoso L. de Queiroz
Keyword(s):  
High Throughput ◽  
Network Approaches ◽  
User Friendly

scholarly journals TRIAGE: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from high-throughput assays

2020 ◽  
Author(s):  
Samuel Katz ◽  
Jian Song ◽  
Kyle P. Webb ◽  
Nicolas W. Lounsbury ◽  
Clare E. Bryant ◽  
...  
Keyword(s):  
High Throughput ◽  
Ad Hoc ◽  
Web Based ◽  
Trade Offs ◽  
Genome Wide ◽  
Efficient Gene ◽  
Iterative Analysis ◽  
Network Approaches ◽  
User Friendly ◽  
Analysis Platform

ABSTRACTComprehensive and efficient gene hit selection from high throughput assays remains a critical bottleneck in realizing the potential of genome-scale studies in biology. Widely used methods such as setting of cutoffs, prioritizing pathway enrichments, or incorporating predicted network interactions offer divergent solutions yet are associated with critical analytical trade-offs, and are often combined in an ad hoc manner. The specific limitations of these individual approaches, the lack of a systematic way by which to integrate their rankings, and the inaccessibility of complex computational approaches to many researchers, has contributed to unexpected variability and limited overlap in the reported results from comparable genome-wide studies. Using a set of three highly studied genome-wide datasets for HIV host factors that have been broadly cited for their limited number of shared candidates, we characterize the specific complementary contributions of commonly used analysis approaches and find an optimal framework by which to integrate these methods. We describe Throughput Ranking by Iterative Analysis of Genomic Enrichment (TRIAGE), an integrated, iterative approach which uses pathway and network statistical methods and publicly available databases to optimize gene prioritization. TRIAGE is accessible as a secure, rapid, user-friendly web-based application (https://triage.niaid.nih.gov).Graphical Abstract

scholarly journals High-Throughput Analysis of Selected Urinary Hydroxy Polycyclic Aromatic Hydrocarbons by an Innovative Automated Solid-Phase Microextraction

Molecules ◽  
2018 ◽  
Vol 23 (8) ◽  
pp. 1869 ◽  
Author(s):  
Stefano Dugheri ◽  
Alessandro Bonari ◽  
Matteo Gentili ◽  
Giovanni Cappelli ◽  
Ilenia Pompilio ◽  
...  
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
High Throughput ◽  
Aromatic Hydrocarbons ◽  
High Throughput Screening ◽  
Solid Phase Microextraction ◽  
Solid Phase ◽  
User Friendliness ◽  
High Throughput Analysis ◽  
Polycyclic Aromatic ◽  
User Friendly

High-throughput screening of samples is the strategy of choice to detect occupational exposure biomarkers, yet it requires a user-friendly apparatus that gives relatively prompt results while ensuring high degrees of selectivity, precision, accuracy and automation, particularly in the preparation process. Miniaturization has attracted much attention in analytical chemistry and has driven solvent and sample savings as easier automation, the latter thanks to the introduction on the market of the three axis autosampler. In light of the above, this contribution describes a novel user-friendly solid-phase microextraction (SPME) off- and on-line platform coupled with gas chromatography and triple quadrupole-mass spectrometry to determine urinary metabolites of polycyclic aromatic hydrocarbons 1- and 2-hydroxy-naphthalene, 9-hydroxy-phenanthrene, 1-hydroxy-pyrene, 3- and 9-hydroxy-benzoantracene, and 3-hydroxy-benzo[a]pyrene. In this new procedure, chromatography’s sensitivity is combined with the user-friendliness of N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide on-fiber SPME derivatization using direct immersion sampling; moreover, specific isotope-labelled internal standards provide quantitative accuracy. The detection limits for the seven OH-PAHs ranged from 0.25 to 4.52 ng/L. Intra-(from 2.5 to 3.0%) and inter-session (from 2.4 to 3.9%) repeatability was also evaluated. This method serves to identify suitable risk-control strategies for occupational hygiene conservation programs.

scholarly journals SSFinder: High Throughput CRISPR-Cas Target Sites Prediction Tool

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Santosh Kumar Upadhyay ◽  
Shailesh Sharma
Keyword(s):  
Operating Systems ◽  
High Throughput ◽  
Genomic Data ◽  
Prediction Tool ◽  
High Demand ◽  
Specific Target ◽  
Target Sites ◽  
High Throughput Detection ◽  
User Friendly

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) system facilitates targeted genome editing in organisms. Despite high demand of this system, finding a reliable tool for the determination of specific target sites in large genomic data remained challenging. Here, we report SSFinder, a python script to perform high throughput detection of specific target sites in large nucleotide datasets. The SSFinder is a user-friendly tool, compatible with Windows, Mac OS, and Linux operating systems, and freely available online.

GEView (Gene Expression View) Tool for Intuitive and High Accessible Visualization of Expression Data for Non-Programmer Biologists

2020 ◽  
pp. 580-592
Author(s):  
Libi Hertzberg ◽  
Assif Yitzhaky ◽  
Metsada Pasmanik-Chor
Keyword(s):  
Gene Expression ◽  
Quality Control ◽  
User Interface ◽  
High Throughput ◽  
Graphical User Interface ◽  
Differential Expression Analysis ◽  
Biological Data ◽  
Expression Data ◽  
Batch Correction ◽  
User Friendly

This article describes how the last decade has been characterized by the production of huge amounts of different types of biological data. Following that, a flood of bioinformatics tools have been published. However, many of these tools are commercial, or require computational skills. In addition, not all tools provide intuitive and highly accessible visualization of the results. The authors have developed GEView (Gene Expression View), which is a free, user-friendly tool harboring several existing algorithms and statistical methods for the analysis of high-throughput gene, microRNA or protein expression data. It can be used to perform basic analysis such as quality control, outlier detection, batch correction and differential expression analysis, through a single intuitive graphical user interface. GEView is unique in its simplicity and highly accessible visualization it provides. Together with its basic and intuitive functionality it allows Bio-Medical scientists with no computational skills to independently analyze and visualize high-throughput data produced in their own labs.

M6A2Target: a comprehensive database for targets of m6A writers, erasers and readers

2020 ◽  
Author(s):  
Shuang Deng ◽  
Hongwan Zhang ◽  
Kaiyu Zhu ◽  
Xingyang Li ◽  
Ying Ye ◽  
...  
Keyword(s):  
High Throughput ◽  
Target Gene ◽  
Target Genes ◽  
Biological Processes ◽  
Public Repository ◽  
Reversible Process ◽  
Comprehensive Database ◽  
Dynamic Modification ◽  
Gene Database ◽  
User Friendly

Abstract N6-methyladenosine (m6A) is the most abundant posttranscriptional modification in mammalian mRNA molecules and has a crucial function in the regulation of many fundamental biological processes. The m6A modification is a dynamic and reversible process regulated by a series of writers, erasers and readers (WERs). Different WERs might have different functions, and even the same WER might function differently in different conditions, which are mostly due to different downstream genes being targeted by the WERs. Therefore, identification of the targets of WERs is particularly important for elucidating this dynamic modification. However, there is still no public repository to host the known targets of WERs. Therefore, we developed the m6A WER target gene database (m6A2Target) to provide a comprehensive resource of the targets of m6A WERs. M6A2Target provides a user-friendly interface to present WER targets in two different modules: ‘Validated Targets’, referred to as WER targets identified from low-throughput studies, and ‘Potential Targets’, including WER targets analyzed from high-throughput studies. Compared to other existing m6A-associated databases, m6A2Target is the first specific resource for m6A WER target genes. M6A2Target is freely accessible at http://m6a2target.canceromics.org.

scholarly journals Instrumental setup for high-throughput small- and wide-angle solution scattering at the X33 beamline of EMBL Hamburg

2012 ◽  
Vol 45 (3) ◽  
pp. 489-495 ◽  
Author(s):  
Clement E. Blanchet ◽  
Alexey V. Zozulya ◽  
Alexey G. Kikhney ◽  
Daniel Franke ◽  
Peter V. Konarev ◽  
...  
Keyword(s):  
High Throughput ◽  
Digital Camera ◽  
Sample Volume ◽  
Wide Angle ◽  
Pixel Detector ◽  
Fully Integrated ◽  
X Ray Scattering ◽  
Angle Scattering ◽  
Rapid Switching ◽  
User Friendly

A setup is presented for automated high-throughput measurements of small-angle X-ray scattering (SAXS) from macromolecular solutions on the bending-magnet beamline X33 of EMBL at the storage ring DORIS-III (DESY, Hamburg). A new multi-cell compartment allows for rapid switching between in-vacuum and in-air operation, for digital camera assisted control of cell filling and for colour sample illumination. The beamline is equipped with a Pilatus 1 M-W pixel detector for SAXS and a Pilatus 300 k-W for wide-angle scattering (WAXS), and results from the use of the Pilatus detectors for scattering studies are reported. The setup provides a broad resolution range from 100 to 0.36 nm without the necessity of changing the sample-to-detector distance. A new optimized robotic sample changer is installed, permitting rapid and reliable automated sample loading and cell cleaning with a required sample volume of 40 µl. All the devices are fully integrated into the beamline control software system, ensuring fully automated and user-friendly operation (attended, unattended and remote) with a throughput of up to 15 measurements per hour.

scholarly journals COPAR: A ChIP-Seq Optimal Peak Analyzer

2017 ◽  
Vol 2017 ◽  
pp. 1-4
Author(s):  
Binhua Tang ◽  
Xihan Wang ◽  
Victor X. Jin
Keyword(s):  
High Throughput ◽  
Genomic Feature ◽  
Data Sets ◽  
Sequencing Data ◽  
Genomic Features ◽  
Peak Alignment ◽  
Chip Sequencing ◽  
Quality Check ◽  
User Friendly ◽  
High Throughput Experiments

Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for ChIP-sequencing profiles. We developed open-sourced COPAR, a user-friendly package, to statistically investigate, quantify, and visualize the optimal peak alignment and inherent genomic features using ChIP-seq data from NGS experiments. It provides a versatile perspective for biologists to perform quality-check for high-throughput experiments and optimize their experiment design. The package COPAR can process mapped ChIP-seq read file in BED format and output statistically sound results for multiple high-throughput experiments. Together with three public ChIP-seq data sets verified with the developed package, we have deposited COPAR on GitHub under a GNU GPL license.

scholarly journals A hybrid open-top light-sheet microscope for multi-scale imaging of cleared tissues

2021 ◽  
Author(s):  
Adam Glaser ◽  
Kevin Bishop ◽  
Lindsey Barner ◽  
Etsuo Susaki ◽  
Shimpei Kubota ◽  
...  
Keyword(s):  
Hybrid System ◽  
High Throughput ◽  
Light Sheet ◽  
Refractive Indices ◽  
Volumetric Imaging ◽  
Tissue Clearing ◽  
Sample Geometry ◽  
Multi Scale ◽  
Light Sheet Microscopy ◽  
User Friendly

Abstract Light-sheet microscopy has emerged as the preferred means for high-throughput volumetric imaging of cleared tissues. However, there is a need for a user-friendly system that can address imaging applications with varied requirements in terms of resolution (mesoscopic to sub-micrometer), sample geometry (size, shape, and number), and compatibility with tissue-clearing protocols and sample holders of various refractive indices. We present a ‘hybrid’ system that combines a novel non-orthogonal dual-objective and conventional (orthogonal) open-top light-sheet architecture for versatile multi-scale volumetric imaging.

scholarly journals MicrobeAnnotator: a user-friendly, comprehensive functional annotation pipeline for microbial genomes

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Carlos A. Ruiz-Perez ◽  
Roth E. Conrad ◽  
Konstantinos T. Konstantinidis
Keyword(s):  
High Throughput ◽  
Functional Annotation ◽  
High Throughput Sequencing ◽  
Gene Annotation ◽  
Single Cells ◽  
Computationally Efficient ◽  
High Throughput Analysis ◽  
Microbial Genomes ◽  
Reference Protein ◽  
User Friendly

Abstract Background High-throughput sequencing has increased the number of available microbial genomes recovered from isolates, single cells, and metagenomes. Accordingly, fast and comprehensive functional gene annotation pipelines are needed to analyze and compare these genomes. Although several approaches exist for genome annotation, these are typically not designed for easy incorporation into analysis pipelines, do not combine results from different annotation databases or offer easy-to-use summaries of metabolic reconstructions, and typically require large amounts of computing power for high-throughput analysis not available to the average user. Results Here, we introduce MicrobeAnnotator, a fully automated, easy-to-use pipeline for the comprehensive functional annotation of microbial genomes that combines results from several reference protein databases and returns the matching annotations together with key metadata such as the interlinked identifiers of matching reference proteins from multiple databases [KEGG Orthology (KO), Enzyme Commission (E.C.), Gene Ontology (GO), Pfam, and InterPro]. Further, the functional annotations are summarized into Kyoto Encyclopedia of Genes and Genomes (KEGG) modules as part of a graphical output (heatmap) that allows the user to quickly detect differences among (multiple) query genomes and cluster the genomes based on their metabolic similarity. MicrobeAnnotator is implemented in Python 3 and is freely available under an open-source Artistic License 2.0 from https://github.com/cruizperez/MicrobeAnnotator. Conclusions We demonstrated the capabilities of MicrobeAnnotator by annotating 100 Escherichia coli and 78 environmental Candidate Phyla Radiation (CPR) bacterial genomes and comparing the results to those of other popular tools. We showed that the use of multiple annotation databases allows MicrobeAnnotator to recover more annotations per genome compared to faster tools that use reduced databases and is computationally efficient for use in personal computers. The output of MicrobeAnnotator can be easily incorporated into other analysis pipelines while the results of other annotation tools can be seemingly incorporated into MicrobeAnnotator to generate summary plots.

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