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Agarwala, R.

Publications and source records attributed to Agarwala, R..

2 recordsLinked to original sources

Finding Candida auris in public metagenomic repositories

Candida auris is a newly emerged multidrug-resistant fungus capable of causing invasive infections with high mortality. Despite intense efforts to understand how this pathogen rapidly emerged and spread worldwide, its environmental reservoirs are poorly understood. Here, we present a collaborative effort between the U.S. Centers for Disease Control and Prevention, the National Center for Biotechnology Information, and GridRepublic (a volunteer computing platform) to identify C. auris sequences in publicly available metagenomic datasets. We developed the MetaNISH pipeline that uses SRPRISM to align sequences to a set of reference genomes and computes a score for each reference genome. We used MetaNISH to scan [~]300,000 SRA metagenomic runs from 2010 onwards and identified five datasets containing C. auris reads. Finally, GridRepublic has implemented a prospective C. auris molecular monitoring system using MetaNISH and volunteer computing.

bioinformatics↗

Indexing and searching petabyte-scale nucleotide resources

Searching vast and rapidly growing sets of nucleotide content in data resources, such as runs in Sequence Read Archive and assemblies for whole genome shotgun sequencing projects in GenBank, is currently impractical in any reasonable amount of time or resources available to most researchers. We present Pebblescout, a tool that navigates such content by providing indexing and search capabilities. Indexing uses dense sampling of the sequences in the resource. Search finds subjects that have short sequence matches to a user query with well-defined guarantees. Reported subjects are ranked using a score that considers the informativeness of the matches. Six databases that index over 3.5 petabases were created and used to illustrate the functionality of Pebblescout. Here we show that Pebblescout provides new research opportunities and a data-driven way for finding relevant subsets of large nucleotide resources for analysis, some of which are missed when relying only on sample metadata or tools using pre-defined reference sequences. For two computationally intensive published studies, we show that Pebblescout rejects a significant number of runs analyzed without changing the conclusions of these studies and finds additional relevant runs. A pilot web service for interactively searching the six databases is freely available at https://pebblescout.ncbi.nlm.nih.gov/

bioinformatics↗