Work

Effects from structure of Metabarcode Sequences on Lossy Analysis of Microbiome Data

Year: 2018

Type: conference-paper

Abstract: The advent of next-generation barcode sequencing has allowed for more high-throughput determination of which species live within an area. Relationships, which are a computed distance, are determined by inferred occupancy of the species in one location relative to another. Here we establish that two analysis methods, namely the established Operational Taxonomic Unit approach and a method commonly found in alignment, kmers, are affected by latent effects within real data. We then analyze these latent effects using simulated data and show that the presence of Single Nucleotide Polymorphisms (i.e., SNPs) within the data and the number of sequences obtained from each species affect inferred correlations.

Source: IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

DOI: 10.1109/bibm.2018.8621143

Authors: David C. Molik, Michael E. Pfrender, Scott J. Emrich

Institutions: University of Notre Dame, University of Tennessee at Knoxville

Language: English

Topic: Genomics and Phylogenetic Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W2911396734

FWCI: 1.053

Cites: 33

Cited by: 1

Related to: 10