Visualizing reference databases

Previous studies on Lamb wave touchscreen (LWT) were carried out based on the assumption that the unknown touch had the consistent parameters with acoustic fingerprints in the reference database. The adaptability of LWT to the variations in touch force and touch area was investigated in this study for the first time. The automatic collection of the databases of acoustic fingerprints was realized with an experimental prototype of LWT employing three pairs of transmitter–receivers. The self-adaptive updated weight coefficient of the used transmitter–receiver pairs was employed to successfully improve the accuracy of the localization model established based on a learning method. The performance of the improved method in locating single- and two-touch actions with the reference database of different parameters was carefully evaluated. The robustness of the LWT to the variation of the touch force varied with the touch area. Moreover, it was feasible to locate touch actions of large area with reference databases of small touch areas as long as the unknown touch and the reference databases met the condition of equivalent averaged stress.

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metaXplor: an interactive viral and microbial metagenomic data manager

GigaScience ◽

10.1093/gigascience/giab001 ◽

2021 ◽

Vol 10 (2) ◽

Author(s):

Guilhem Sempéré ◽

Adrien Pétel ◽

Magsen Abbé ◽

Pierre Lefeuvre ◽

Philippe Roumagnac ◽

...

Keyword(s):

Heterogeneous Data ◽

Metagenomic Data ◽

Online Data ◽

Data Repositories ◽

Ongoing Research ◽

Efficient Management ◽

Public Data ◽

Reference Databases ◽

Interactive Data ◽

User Friendly

Abstract Background Efficiently managing large, heterogeneous data in a structured yet flexible way is a challenge to research laboratories working with genomic data. Specifically regarding both shotgun- and metabarcoding-based metagenomics, while online reference databases and user-friendly tools exist for running various types of analyses (e.g., Qiime, Mothur, Megan, IMG/VR, Anvi'o, Qiita, MetaVir), scientists lack comprehensive software for easily building scalable, searchable, online data repositories on which they can rely during their ongoing research. Results metaXplor is a scalable, distributable, fully web-interfaced application for managing, sharing, and exploring metagenomic data. Being based on a flexible NoSQL data model, it has few constraints regarding dataset contents and thus proves useful for handling outputs from both shotgun and metabarcoding techniques. By supporting incremental data feeding and providing means to combine filters on all imported fields, it allows for exhaustive content browsing, as well as rapid narrowing to find specific records. The application also features various interactive data visualization tools, ways to query contents by BLASTing external sequences, and an integrated pipeline to enrich assignments with phylogenetic placements. The project home page provides the URL of a live instance allowing users to test the system on public data. Conclusion metaXplor allows efficient management and exploration of metagenomic data. Its availability as a set of Docker containers, making it easy to deploy on academic servers, on the cloud, or even on personal computers, will facilitate its adoption.

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CSMD: a computational subtraction-based microbiome discovery pipeline for species-level characterization of clinical metagenomic samples

Bioinformatics ◽

10.1093/bioinformatics/btz790 ◽

2019 ◽

Author(s):

Yu Liu ◽

Paul W Bible ◽

Bin Zou ◽

Qiaoxing Liang ◽

Cong Dong ◽

...

Keyword(s):

Species Level ◽

Supplementary Information ◽

Clinical Samples ◽

Plasma Dna ◽

Bioinformatics Pipeline ◽

Microbial Identification ◽

Reference Databases ◽

Microbial Dna ◽

Higher Sensitivity

Abstract Motivation Microbiome analyses of clinical samples with low microbial biomass are challenging because of the very small quantities of microbial DNA relative to the human host, ubiquitous contaminating DNA in sequencing experiments and the large and rapidly growing microbial reference databases. Results We present computational subtraction-based microbiome discovery (CSMD), a bioinformatics pipeline specifically developed to generate accurate species-level microbiome profiles for clinical samples with low microbial loads. CSMD applies strategies for the maximal elimination of host sequences with minimal loss of microbial signal and effectively detects microorganisms present in the sample with minimal false positives using a stepwise convergent solution. CSMD was benchmarked in a comparative evaluation with other classic tools on previously published well-characterized datasets. It showed higher sensitivity and specificity in host sequence removal and higher specificity in microbial identification, which led to more accurate abundance estimation. All these features are integrated into a free and easy-to-use tool. Additionally, CSMD applied to cell-free plasma DNA showed that microbial diversity within these samples is substantially broader than previously believed. Availability and implementation CSMD is freely available at https://github.com/liuyu8721/csmd. Supplementary information Supplementary data are available at Bioinformatics online.

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Comparative Evaluation of Local and International Reference Databases for Forearm Densitometry: Different Impacts on Diagnostic Decisions

Journal of Clinical Densitometry ◽

10.1016/j.jocd.2006.06.004 ◽

2006 ◽

Vol 9 (4) ◽

pp. 445-453 ◽

Cited By ~ 3

Author(s):

Szilvia Mészáros ◽

Péter Berkő ◽

György Genti ◽

Éva Hosszú ◽

Béla Keszthelyi ◽

...

Keyword(s):

Comparative Evaluation ◽

International Reference ◽

Reference Databases

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Graph-based sequence annotation using a data integration approach

Journal of Integrative Bioinformatics ◽

10.1515/jib-2008-94 ◽

2008 ◽

Vol 5 (2) ◽

Cited By ~ 1

Author(s):

Robert Pesch ◽

Artem Lysenko ◽

Matthew Hindle ◽

Keywan Hassani-Pak ◽

Ralf Thiele ◽

...

Keyword(s):

Data Integration ◽

Gene Function ◽

High Throughput Sequencing ◽

Prediction Method ◽

Function Prediction ◽

Function Annotation ◽

Automated Annotation ◽

Data Integration System ◽

Reference Databases ◽

Function Assignment

SummaryThe automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara- Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation.The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.

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Teleradiology: results of a questionnaire of German radiologists

Journal of Telemedicine and Telecare ◽

10.1258/1357633981931524 ◽

1998 ◽

Vol 4 (1_suppl) ◽

pp. 69-71 ◽

Cited By ~ 3

Author(s):

R Bolte ◽

M Walz ◽

K J Lehmann ◽

T Hothorn ◽

C Brill ◽

...

Keyword(s):

Image Quality ◽

Data Security ◽

Response Rate ◽

System Stability ◽

Technical Quality ◽

Expert Consultation ◽

Reference Databases ◽

Educational Applications

A questionnaire was sent by mail to 4400 radiologists (i.e. to at least 1000 radiological institutions). The response rate was about 5%. The results showed that 47% of respondents felt well informed about teleradiology, 49% not enough and 3% not at all. Image and report transfer as well as interfaces to reference databases, educational applications, technical quality surveillance and product support (maintenance) were considered to be increasingly important areas. Smaller institutions (1–3 doctors) judged expert consultation as more important than bigger institutions. Standardization, system stability and data security were demanded as well as guidelines, for example concerning the linking of report and image, correct documentation and required image quality. Technically most demands can be fulfilled today but this technology is not yet commonly included in teleradiology systems.

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Accurate Reconstruction of Microbial Strains from Metagenomic Sequencing Using Representative Reference Genomes

10.1101/215707 ◽

2017 ◽

Cited By ~ 2

Author(s):

Zhemin Zhou ◽

Nina Luhmann ◽

Nabil-Fareed Alikhan ◽

Christopher Quince ◽

Mark Achtman

Keyword(s):

Evaluation Studies ◽

Species Level ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Reference Databases ◽

Microbial Strains ◽

Taxonomic Assignments ◽

Taxonomic Groups ◽

Reference Genomes ◽

Recent Evaluation

AbstractExploring the genetic diversity of microbes within the environment through metagenomic sequencing first requires classifying these reads into taxonomic groups. Current methods compare these sequencing data with existing biased and limited reference databases. Several recent evaluation studies demonstrate that current methods either lack sufficient sensitivity for species-level assignments or suffer from false positives, overestimating the number of species in the metagenome. Both are especially problematic for the identification of low-abundance microbial species, e. g. detecting pathogens in ancient metagenomic samples. We present a new method, SPARSE, which improves taxonomic assignments of metagenomic reads. SPARSE balances existing biased reference databases by grouping reference genomes into similarity-based hierarchical clusters, implemented as an efficient incremental data structure. SPARSE assigns reads to these clusters using a probabilistic model, which specifically penalizes non-specific mappings of reads from unknown sources and hence reduces false-positive assignments. Our evaluation on simulated datasets from two recent evaluation studies demonstrated the improved precision of SPARSE in comparison to other methods for species-level classification. In a third simulation, our method successfully differentiated multiple co-existing Escherichia coli strains from the same sample. In real archaeological datasets, SPARSE identified ancient pathogens with ≤ 0.02% abundance, consistent with published findings that required additional sequencing data. In these datasets, other methods either missed targeted pathogens or reported non-existent ones. SPARSE and all evaluation scripts are available at https://github.com/zheminzhou/SPARSE.

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Overcoming limitations to environmental DNA studies: A coastal temperate reference sequence database for multiple chloroplast gene regions generated in a single assay.

10.22541/au.163252330.05592688/v1 ◽

2021 ◽

Author(s):

Nicole Foster ◽

Kor-jent Dijk ◽

Ed Biffin ◽

Jennifer Young ◽

Vicki Thomson ◽

...

Keyword(s):

Dna Sequences ◽

Dna Barcode ◽

Environmental Dna ◽

Reference Sequence ◽

Reference Database ◽

Chloroplast Gene ◽

Coastal Plants ◽

Reference Databases ◽

Targeted Capture ◽

Comprehensive Reference

A proliferation in environmental DNA (eDNA) research has increased the reliance on reference sequence databases to assign unknown DNA sequences to known taxa. Without comprehensive reference databases, DNA extracted from environmental samples cannot be correctly assigned to taxa, limiting the use of this genetic information to identify organisms in unknown sample mixtures. For animals, standard metabarcoding practices involve amplification of the mitochondrial Cytochrome-c oxidase subunit 1 (CO1) region, which is a universally amplifyable region across majority of animal taxa. This region, however, does not work well as a DNA barcode for plants and fungi, and there is no similar universal single barcode locus that has the same species resolution. Therefore, generating reference sequences has been more difficult and several loci have been suggested to be used in parallel to get to species identification. For this reason, we developed a multi-gene targeted capture approach to generate reference DNA sequences for plant taxa across 20 target chloroplast gene regions in a single assay. We successfully compiled a reference database for 93 temperate coastal plants including seagrasses, mangroves, and saltmarshes/samphire’s. We demonstrate the importance of a comprehensive reference database to prevent species going undetected in eDNA studies. We also investigate how using multiple chloroplast gene regions impacts the ability to discriminate between taxa.

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