MetaFunc: taxonomic and functional analyses of high throughput sequencing for microbiomes. (12th January 2023)

• Record Type: Journal Article
• Authors: Sulit, Arielle Kae; Kolisnik, Tyler; Frizelle, Frank Antony; Purcell, Rachel; Schmeier, Sebastian
• Is Part Of: Gut microbiome. Volume 4(2023)
• Publication Date: 2023-01-12
• Subjects: Metatranscriptomics -- microbiome -- functional annotation -- host correlation; Intestines -- Microbiology -- Periodicals; Intestines -- Diseases -- Periodicals; Intestines -- Diseases; Intestines -- Microbiology; Electronic journals; Periodicals; 612.3601579
• DOI: 10.1017/gmb.2022.12
• Languages: English
• ISSNs: 2632-2897

Abstract

Abstract: The identification of functional processes taking place in microbiome communities augment traditional microbiome taxonomic studies, giving a more complete picture of interactions taking place within the community. While there are applications that perform functional annotation on metagenomes or metatranscriptomes, very few of these are able to link taxonomic identity to function or are limited by their input types or databases used. Here we present MetaFunc, a workflow which takes RNA sequences as input reads, and from these (1) identifies species present in the microbiome sample and (2) provides gene ontology annotations associated with the species identified. In addition, MetaFunc allows for host gene analysis, mapping the reads to a host genome, and separating these reads, prior to microbiome analyses. Differential abundance analysis for microbe taxonomies, and differential gene expression analysis and gene set enrichment analysis may then be carried out through the pipeline. A final correlation analysis between microbial species and host genes can also be performed. Finally, MetaFunc builds an R shiny application that allows users to view and interact with the microbiome results. In this paper, we showed how MetaFunc can be applied to metatranscriptomic datasets of colorectal cancer.