About: IDseq – An Open Source Cloud-based Pipeline and Analysis Service for Metagenomic Pathogen Detection and Monitoring

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About: IDseq – An Open Source Cloud-based Pipeline and Analysis Service for Metagenomic Pathogen Detection and Monitoring Goto Sponge NotDistinct Permalink

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Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	IDseq – An Open Source Cloud-based Pipeline and Analysis Service for Metagenomic Pathogen Detection and Monitoring
Creator	Dimitrov, Boris Egger, Rebecca Juan, Yun-Fang Kalantar, Katrina Sheu, Jonathan Wang, James De Bourcy, Charles Derisi, Joseph Tato, Cristina Ahyong, Vida Bohl, Jennifer Chea, Sophana Lay, Sreyngim Manning, Jessica Mariano, Maria Zhang, Mark Carvalho, Tiago Dingle, Greg Han, Julie Holmes, Olivia King, Ryan Kislyuk, Andrey Reynoso, Lucia Rissato Cruz, David Tang, Jennifer Zhong, Emily
Source	BioRxiv
abstract	Background Metagenomic next generation sequencing (mNGS) has enabled the rapid, unbiased detection and identification of microbes without pathogen-specific reagents, culturing, or a priori knowledge of the microbial landscape. mNGS data analysis requires a series of computationally intensive processing steps to accurately determine the microbial composition of a sample. Existing mNGS data analysis tools typically require bioinformatics expertise and access to local server-class hardware resources. For many research laboratories, this presents an obstacle, especially in resource limited environments. Findings We present IDseq, an open source cloud-based metagenomics pipeline and service for global pathogen detection and monitoring (https://idseq.net). The IDseq Portal accepts raw mNGS data, performs host and quality filtration steps, then executes an assembly-based alignment pipeline which results in the assignment of reads and contigs to taxonomic categories. The taxonomic relative abundances are reported and visualized in an easy-to-use web application to facilitate data interpretation and hypothesis generation. Furthermore, IDseq supports environmental background model generation and automatic internal spike-in control recognition, providing statistics which are critical for data interpretation. IDseq was designed with the specific intent of detecting novel pathogens. Here, we benchmark novel virus detection capability using both synthetically evolved viral sequences, and real-world samples, including IDseq analysis of a nasopharyngeal swab sample acquired and processed locally in Cambodia from a tourist from Wuhan, China, infected with the recently emergent SARS-CoV-2. Conclusion The IDseq Portal reduces the barrier to entry for mNGS data analysis and enables bench scientists, clinicians, and bioinformaticians to gain insight from mNGS datasets for both known and novel pathogens.
has issue date	2020-04-18(xsd:dateTime)
bibo:doi	10.1101/2020.04.07.030551
has license	biorxiv
sha1sum (hex)	710bfb8052f2c32456a6a05f8e21b69a2d65e6e8
schema:url	https://doi.org/10.1101/2020.04.07.030551
resource representing a document's title	IDseq – An Open Source Cloud-based Pipeline and Analysis Service for Metagenomic Pathogen Detection and Monitoring
schema:publication	bioRxiv
resource representing a document's body	covid:710bfb8052f2c32456a6a05f8e21b69a2d65e6e8#body_text
is schema:about of	named entity 'raw' named entity 'reagents' named entity 'Portal' named entity 'SARS-CoV-2' named entity 'processing' named entity 'reads' named entity 'microbes' named entity 'SOURCE' named entity 'SPECIFIC' named entity 'USE' named entity 'CAPABILITY' named entity 'BIOINFORMATICS' named entity 'STATISTICS' named entity 'FINDINGS' named entity 'PROVIDING' named entity 'PATHOGEN DETECTION' named entity 'DETECTION' named entity 'WORLD' named entity 'CULTURING' named entity 'data analysis' named entity 'Portal' named entity 'barrier' named entity 'local' named entity 'computationally' named entity 'relative' named entity 'filtration' named entity 'internal' named entity 'enabled' named entity 'benchmark' named entity 'chromosome' named entity 'encephalitis' named entity '1.6' named entity 'Klebsiella aerogenes' named entity 'sequencing reads' named entity 'contig' named entity 'diagnostic accuracy' named entity 'taxonomic' named entity 'Bowtie2' named entity 'presents' named entity 'global' named entity 'pathogens' named entity 'China' named entity 'specific intent' named entity 'taxonomic' named entity 'culturing' named entity 'bench' named entity 'China' named entity 'data analysis tools' named entity 'Metagenomic' named entity 'pathogen' named entity 'web application' named entity 'Pipeline' named entity 'model' named entity 'infected' named entity 'amino acid sequence identity' named entity 'database' named entity 'data analysis' named entity 'bacterial pathogens' named entity 'EV-D68'

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