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An Exploratory Analysis of the DADA2 and uBiome Pipelines

Myers, John Vincent
http://rave.ohiolink.edu/etdc/view?acc_num=osu1555603546669156

Abstract Details

2019, Master of Science, Ohio State University, Public Health.
The gut microbe is the collective of all microbes living in the human digestive tract, and assist their hosts by aiding in digestion, compound synthesis, and immune function. Changes in the microbiome profile can be associated with disease, so analyzing the microbiome via high-throughput sequencing could prove useful in disease detection and prevention. However, one pipeline used to characterize the microbiome can result in a different profile than another pipeline. In this exploratory analysis, the proprietary uBiome pipeline is compared against the open-source DADA2 pipeline using diversity indices. It was hypothesized that the diversity measures between pipelines would correlate highly but not be identical, that covariates that are predictive of a given diversity index in one pipeline would be predictive in the other pipeline, and that within-couple correlations would be similar between pipelines. The data came from a study on cohabiting couples in which fecal and blood samples were collected two times points, with two to four months in between visits. The company uBiome sequenced the sample by targeting the 16S rRNA gene. Seven diversity indices were calculated for each individual for each pipeline, and were used to compare outcomes between pipelines. Correlations between pipelines were explored using Pearson correlations and scatterplots. Linear mixed modeling was used to assess the predictive potential of covariates such as age, sex, and BMI, specifying random intercepts for couples and visit number. Covariates predictive of differences between pipelines were also explored with generalized estimation equations. Within-couple correlations were assessed by calculating intracluster correlations, and confidence intervals were found these correlations by performing a logit transformation, calculating the confidence intervals, and converting out of the logit scale. The correlations between pipelines were generally high, but some diversity indices were more strongly correlated than others. There were not any covariates in the study that were predictive of diversity indices in both the uBiome and DADA2 pipelines. Age was a predictor of differences between pipelines for several diversity indices, but there wasn’t a covariate that was predictive of differences in all pipelines. Within-couple correlations were not similar between pipelines, and uBiome’s pipeline resulted in consistently higher intracluster correlation estimates than the DADA2 pipeline.
Rebecca Andridge (Advisor)
Chi Song (Committee Member)
39 p.
Biostatistics; Public Health

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Citations

  • Myers, J. V. (2019). An Exploratory Analysis of the DADA2 and uBiome Pipelines [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555603546669156

    APA Style (7th edition)

  • Myers, John. An Exploratory Analysis of the DADA2 and uBiome Pipelines. 2019. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1555603546669156.

    MLA Style (8th edition)

  • Myers, John. "An Exploratory Analysis of the DADA2 and uBiome Pipelines." Master's thesis, Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555603546669156

    Chicago Manual of Style (17th edition)

osu1555603546669156
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This open access ETD is published by The Ohio State University and OhioLINK.