IDseq—An open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring

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 that 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.

Impaired immune signaling and changes in the lung microbiome precede secondary bacterial pneumonia in COVID-19

“…RNA from tracheal aspirates was sequenced as described above. Respiratory microbiome sequences were quality-filtered, human reads removed, and assembled using open-source IDseq pipeline (39, 40) , which performs reference based taxonomic alignment at both the nucleotide and amino acid level against sequences in the National Center for Biotechnology Information (NCBI) nucleotide (NT) and non-redundant (NR) databases, followed by assembly of the reads matching each taxon detected. Taxonomic alignments underwent background correction for environmental contaminants (see below), viruses were excluded, and data was then aggregated to the genus level before calculating diversity metrics.…”

A Primer on the Analysis of High-Throughput Sequencing Data for Detection of Plant Viruses

“… Not specifically made for virus detection. ID-Seq Online metagenomic analysis tool , accessed on 13 April 2021 [ 152 ] Easy-to-use visual interface of results. Quick analysis not requiring any knowledge in bioinformatics and data analysis.…”

Host-Microbe Metagenomics: a Lens To Refocus Our Perspective on Infectious and Inflammatory Diseases

“…Despite the potential for host/microbe mNGS to advance our understanding of infectious and inflammatory diseases, use has been limited by both the cost of sequencing and the computational infrastructure needed for computationally intensive bioinformatics analysis. Advancements in cloud-based open source pipelines such as the IDseq pipeline ( 20 ) have democratized access to, and analysis of, mNGS data. Now anyone in the world with Internet connectivity can access the expanding repositories of publicly accessible host and microbial sequencing data to study their disease of interest.…”