2019
DOI: 10.21203/rs.2.15922/v1
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A Comparison of Two DNA Metagenomic Bioinformatic Pipelines while evaluating the Microbial Diversity in feces of Tanzanian small holder dairy cattle

Abstract: Background: 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. Furthermore, no conventional assessment technique for estimating the precision of each pipeline exists and few studies have been carried out to compare the characteristics, benefits and disadvantages of each pipeline. In this st… Show more

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Cited by 2 publications
(2 citation statements)
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“…The developers of Kraken tested the original Kraken1 program against a simulated Hi-seq metagenome and found that precision at genus level, defined as the proportion of correctly classified reads from all the classification attempts, was 99.2% [64]. Although this precision is high, and Kraken and Kraken2 have been found by other authors to be precise and accurate and in line with other metagenomic pipelines [65,66], the low numbers of total AOD-associated bacterial reads classified may put our results within the potential margin of error for false positives. The trends we detected in the species level comparisons should therefore be verified, for example using qPCR studies on the oak phyllosphere.…”
Section: Discussionmentioning
confidence: 87%
“…The developers of Kraken tested the original Kraken1 program against a simulated Hi-seq metagenome and found that precision at genus level, defined as the proportion of correctly classified reads from all the classification attempts, was 99.2% [64]. Although this precision is high, and Kraken and Kraken2 have been found by other authors to be precise and accurate and in line with other metagenomic pipelines [65,66], the low numbers of total AOD-associated bacterial reads classified may put our results within the potential margin of error for false positives. The trends we detected in the species level comparisons should therefore be verified, for example using qPCR studies on the oak phyllosphere.…”
Section: Discussionmentioning
confidence: 87%
“…This technology allows for longer read lengths, faster turn-around time, more reads per unit cost, and reduced error rates (21). These advantages of NGS has led to its substantial use in metagenomic studies (22)(23)(24)(25)(26).…”
Section: Introductionmentioning
confidence: 99%