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...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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Hindawi Limited
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/110648 |
| _version_ | 1855540260584292352 |
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| author | Kibegwa, F.M. Bett, R.C. Gachuiri, C.K. Stomeo, Francesca Mujibi, F.D.N. |
| author_browse | Bett, R.C. Gachuiri, C.K. Kibegwa, F.M. Mujibi, F.D.N. Stomeo, Francesca |
| author_facet | Kibegwa, F.M. Bett, R.C. Gachuiri, C.K. Stomeo, Francesca Mujibi, F.D.N. |
| author_sort | Kibegwa, F.M. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. |
| format | Journal Article |
| id | CGSpace110648 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Hindawi Limited |
| publisherStr | Hindawi Limited |
| record_format | dspace |
| spelling | CGSpace1106482024-08-27T10:37:11Z A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle Kibegwa, F.M. Bett, R.C. Gachuiri, C.K. Stomeo, Francesca Mujibi, F.D.N. genomics dairy cattle livestock dairying 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. 2020-04-23 2020-12-27T14:25:53Z 2020-12-27T14:25:53Z Journal Article https://hdl.handle.net/10568/110648 en Open Access Hindawi Limited Kibegwa, F.M., Bett, R.C., Gachuiri, C.K., Stomeo, F. and Mujibi, F.D. 2020. A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle. BioMed Research International |
| spellingShingle | genomics dairy cattle livestock dairying Kibegwa, F.M. Bett, R.C. Gachuiri, C.K. Stomeo, Francesca Mujibi, F.D.N. A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle |
| title | A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle |
| title_full | A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle |
| title_fullStr | A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle |
| title_full_unstemmed | A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle |
| title_short | A comparison of two DNA metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of Tanzanian small holder dairy cattle |
| title_sort | comparison of two dna metagenomic bioinformatic pipelines while evaluating the microbial diversity in feces of tanzanian small holder dairy cattle |
| topic | genomics dairy cattle livestock dairying |
| url | https://hdl.handle.net/10568/110648 |
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