A Comparison of Two DNA Metagenomic Bioinformatic Pipelines While Evaluating the Microbial Diversity in Feces of Tanzanian Small Holder Dairy Cattle.
Analysis of shotgun metagenomic data generated from next generation sequencing platforms can be done through a variety of bioinformatic pipelines. These pipelines employ different sets of sophisticated bioinformatics algorithms which may affect the results of this analysis. In this study, we compare...
| Published in: | BioMed Research International pp. 1 - 13 |
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| Main Authors: | , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
4/23/2020
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=142929034&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 142929034 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 4/23/2020 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 142929034 142929034 142929034 10.1155/2020/2348560 142929034 ppf: 1 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Comparison of Two DNA Metagenomic Bioinformatic Pipelines While Evaluating the Microbial Diversity in Feces of Tanzanian Small Holder Dairy Cattle. aug: au: Kibegwa, Felix M. Bett, Rawlynce C. Gachuiri, Charles K. Stomeo, Francesca Mujibi, Fidalis D. affil: Department of Animal Production, University of Nairobi, Kenya sug: subj: Sequence Analysis Methods DNA Analysis Bioinformatics Feces Microbiology Gut Microbiota Analysis Animal Studies Tanzania Cattle Phylogenetics Bacteria Analysis Bacteroides Analysis Algorithms ab: Analysis of shotgun metagenomic data generated from next generation sequencing platforms can be done through a variety of bioinformatic pipelines. These pipelines employ different sets of sophisticated bioinformatics algorithms which may affect the results of this analysis. In this study, we compared two commonly used pipelines for shotgun metagenomic analysis: MG-RAST and Kraken 2, in terms of taxonomic classification, diversity analysis, and usability using their primarily default parameters. Overall, the two pipelines detected similar abundance distributions in the three most abundant taxa Proteobacteria, Firmicutes, and Bacteroidetes. Within bacterial domain, 497 genera were identified by both pipelines, while an additional 694 and 98 genera were solely identified by Kraken 2 and MG-RAST, respectively. 933 species were detected by the two algorithms. Kraken 2 solely detected 3550 species, while MG-RAST identified 557 species uniquely. For archaea, Kraken 2 generated 105 and 236 genera and species, respectively, while MG-RAST detected 60 genera and 88 species. 54 genera and 72 species were commonly detected by the two methods. Kraken 2 had a quicker analysis time (~4 hours) while MG-RAST took approximately 2 days per sample. This study revealed that Kraken 2 and MG-RAST generate comparable results and that a reliable high-level overview of sample is generated irrespective of the pipeline selected. However, Kraken 2 generated a more accurate taxonomic identification given the higher number of "Unclassified" reads in MG-RAST. The observed variations at the genus level show that a main restriction is using different databases for classification of the metagenomic data. The results of this research indicate that a more inclusive and representative classification of microbiomes may be achieved through creation of the combined pipelines. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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