Approaches for integrating heterogeneous RNA-seq data reveal cross-talk between microbes and genes in asthmatic patients

Autor: Daniel Spakowicz, Shaoke Lou, Brian Barron, Jose L. Gomez, Tianxiao Li, Qing Liu, Nicole Grant, Xiting Yan, Rebecca Hoyd, George Weinstock, Geoffrey L. Chupp, Mark Gerstein
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Genome Biology, Vol 21, Iss 1, Pp 1-22 (2020)
Druh dokumentu: article
ISSN: 1474-760X
DOI: 10.1186/s13059-020-02033-z
Popis: Abstract Sputum induction is a non-invasive method to evaluate the airway environment, particularly for asthma. RNA sequencing (RNA-seq) of sputum samples can be challenging to interpret due to the complex and heterogeneous mixtures of human cells and exogenous (microbial) material. In this study, we develop a pipeline that integrates dimensionality reduction and statistical modeling to grapple with the heterogeneity. LDA(Latent Dirichlet allocation)-link connects microbes to genes using reduced-dimensionality LDA topics. We validate our method with single-cell RNA-seq and microscopy and then apply it to the sputum of asthmatic patients to find known and novel relationships between microbes and genes.
Databáze: Directory of Open Access Journals
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