RITA: Rapid Identification of High-Confidence Taxonomic Assignments for Metagenomic Data

2015 ◽  
pp. 613-618
Author(s):  
Norman J. MacDonald ◽  
Donovan H. Parks ◽  
Robert G. Beiko
2012 ◽  
Vol 40 (14) ◽  
pp. e111-e111 ◽  
Author(s):  
Norman J. MacDonald ◽  
Donovan H. Parks ◽  
Robert G. Beiko

Author(s):  
Hayden Smith ◽  
Francesco Dal Grande ◽  
Lucia Muggia ◽  
Rachel Keuler ◽  
Pradeep K. Divakar ◽  
...  

AbstractLichens have traditionally been considered the symbiotic phenotype from the interactions of a single fungal partner and one or few photosynthetic partners. However, the lichen symbiosis has been shown to be far more complex and may include a wide range of other interacting organisms, including non-photosynthetic bacteria, accessory fungi, and algae. In this study, we analyzed metagenomic shotgun sequences to better characterize lichen mycobiomes. Specifically, we inferred the range of fungi associated within lichen thalli from five groups of lichens – horsehair lichens (mycobiont=Bryoria spp.), shadow lichens (taxa in Physciaceae), rock posies (Rhizoplaca spp.), rock tripes (Umbilicaria spp.), and green rock shields (Xanthoparmelia spp.). Metagenomic reads from the multi-copy nuclear ribosomal internal transcribed spacer region, the standard DNA barcode region for fungi, were extracted, clustered, and used to infer taxonomic assignments. Our data revealed diverse lichen-associated mycobiomes, and closely related mycobionts tended to have more similar mycobiomes. Many of the members of the lichen-associated mycobiomes identified here have not previously been found in association with lichens. We found little evidence supporting the ubiquitous presence of Cystobasidiales yeasts in macrolichens, although reads representing this putative symbiotic partner were found in samples of horsehair lichens, albeit in low abundance. Our study further highlights the ecosystem-like features of lichens, with partners and interactions far from being completely understood. Future research is needed to more fully and accurately characterize lichen mycobiomes and how these fungi interact with the major lichen components – the photo- and mycobionts.


2017 ◽  
Author(s):  
Saima Sultana Tithi ◽  
Roderick V. Jensen ◽  
Liqing Zhang

AbstractIdentifying viruses and phages in a metagenomics sample has important implication in improving human health, preventing viral outbreaks, and developing personalized medicine. With the rapid increase in data files generated by next generation sequencing, existing tools for identifying and annotating viruses and phages in metagenomics samples suffer from expensive running time. In this paper, we developed a stand-alone pipeline, FastViromeExplorer, for rapid identification and abundance quantification of viruses and phages in big metagenomic data. Both real and simulated data validated FastViromeExplorer as a reliable tool to accurately identify viruses and their abundances in large data, as well as in a time efficient manner.


2020 ◽  
Author(s):  
Guocai Yao ◽  
Wenliang Zhang ◽  
Minglei Yang ◽  
Huan Yang ◽  
Jianbo Wang ◽  
...  

AbstractMicrobes play important roles in human health and disease. The interaction between microbes and hosts is a reciprocal relationship, which remains largely under-explored. Current computational resources lack manually and consistently curated data to connect metagenomic data to pathogenic microbes, microbial core genes, and disease phenotypes. We developed the MicroPhenoDB database by manually curating and consistently integrating microbe-disease association data. MicroPhenoDB provides 5677 non-redundant associations between 1781 microbes and 542 human disease phenotypes across more than 22 human body sites. MicroPhenoDB also provides 696,934 relationships between 27,277 unique clade-specific core genes and 685 microbes. Disease phenotypes are classified and described using the Experimental Factor Ontology (EFO). A refined score model was developed to prioritize the associations based on evidential metrics. The sequence search option in MicroPhenoDB enables rapid identification of existing pathogenic microbes in samples without running the usual metagenomic data processing and assembly. MicroPhenoDB offers data browsing, searching and visualization through user-friendly web interfaces and web service application programming interfaces. MicroPhenoDB is the first database platform to detail the relationships between pathogenic microbes, core genes, and disease phenotypes. It will accelerate metagenomic data analysis and assist studies in decoding microbes related to human diseases. MicroPhenoDB is available through http://www.liwzlab.cn/microphenodb and http://lilab2.sysu.edu.cn/microphenodb.


2017 ◽  
Author(s):  
David C. Danko ◽  
Dmitry Meleshko ◽  
Daniela Bezdan ◽  
Christopher Mason ◽  
Iman Hajirasouliha

AbstractEmerging Linked-Read technologies (aka Read-Cloud or barcoded short-reads) have revived interest in standard short-read technology as a viable way to understand large-scale structure in genomes and metagenomes. Linked-Read technologies, such as the 10X Chromium system, use a microfluidic system and a set of specially designed 3’ barcodes (aka UIDs) to tag short DNA reads which were originally sourced from the same long fragment of DNA; subsequently, these specially barcoded reads are sequenced on standard short read platforms. This approach results in interesting compromises. Each long fragment of DNA is covered only sparsely by short reads, no information about the relative ordering of reads from the same fragment is preserved, and typically each 3’ barcode matches reads from 2-20 long fragments of DNA. However, compared to long read platforms like those produced by Pacific Biosciences and Oxford Nanopore the cost per base to sequence is far lower, far less input DNA is required, and the per base error rate is that of Illumina short-reads.The use of Linked-Reads presents a new set of algorithmic challenges. In this paper, we formally describe one particular issue common to all applications of Linked-Read technology: the deconvolution of reads with a single 3’ barcode into clusters that correspond to a single long fragment of DNA. We introduce Minerva, A graph-based algorithm that approximately solves the barcode deconvolution problem for metagenomic data (where reference genomes may be incomplete or unavailable). Additionally, we develop two demonstrations where the deconvolution of barcoded reads improves downstream results: improving the specificity of taxonomic assignments, and by improving clustering of related sequences. To the best of our knowledge, we are the first to address the problem of barcode deconvolution in metagenomics.


VASA ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 35-46
Author(s):  
Stephen Hofmeister ◽  
Matthew B. Thomas ◽  
Joseph Paulisin ◽  
Nicolas J. Mouawad

Abstract. The management of vascular emergencies is dependent on rapid identification and confirmation of the diagnosis with concurrent patient stabilization prior to immediate transfer to the operating suite. A variety of technological advances in diagnostic imaging as well as the advent of minimally invasive endovascular interventions have shifted the contemporary treatment algorithms of such pathologies. This review provides a comprehensive discussion on the current state and future trends in the management of ruptured abdominal aortic aneurysms as well as acute aortic dissections.


2010 ◽  
Author(s):  
Laura Mickes ◽  
Vivian Hwe ◽  
John T. Wixted
Keyword(s):  

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