Development of OTU Analysis in NutriGen
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1 Development of OTU Analysis in NutriGen Integrating OTU data with other NutriGen Data Mateen Shaikh and Joseph Beyene McMaster University December Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
2 TOC Background The Data s Context Investigations Differential Abundance Tests Permutation Various Linear Models Candidates Exemplifying Results Statistical issues Next Steps... In this framework Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
3 Background The Data s Context 250 infants contributed microbiome samples from CHILD (processed) 180 infants contributed microbiome samples from START (processing) Methods developed from the START samples Continuing from the work already complete by Mike Surette s Lab (JS and MS) Picking up at the OTU table Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
4 Background Investigations Goals Determine relationships between the microbiome and Changes in breastfeeding Mother s GDM Diet Other health outcomes (adiposity, asthma, etc.) Introduction of (types of) foods Integration with other large data types (genotype, methylation, expression) Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
5 Background Investigations Sample from CHILD SA10 SA11 SA12 SA13 SA14 SA15 SA16 SA17 SA18 SA > mean(otutable==0) [1] Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
6 Differential Abundance Tests Permutation Permutation Tests Simple for a few categorical variables Prefer a quantile-based measure, because of heavy positive skew, but choosing a quantile (like the median) can be problematic Fairly conservative but provides p-values nonetheless Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
7 Differential Abundance Tests Permutation GDM otu# otu pval 17 Bacteroidaceae; g Bacteroides ostridiales; f Lachnospiraceae ostridiales; f Lachnospiraceae ostridiales; f Lachnospiraceae Lachnospiraceae; g Lachnospira acteriaceae; g Bifidobacterium ostridiales; f Lachnospiraceae ococcaceae; g Faecalibacterium Lachnospiraceae; g Lachnospira ostridiales; f Lachnospiraceae ostridiales; f Lachnospiraceae ostridiales; f Lachnospiraceae acteriaceae; g Bifidobacterium ctinomycetaceae; g Actinomyces acteriaceae; g Bifidobacterium ostridiales; f Lachnospiraceae acteriaceae; g Bifidobacterium ostridiales; f Lachnospiraceae teriales; f Bifidobacteriaceae acteriaceae; g Bifidobacterium c Clostridia; o Clostridiales omonadaceae; g Parabacteroides ococcaceae; g Faecalibacterium inobacteria; o Actinomycetales ostridiales; f Lachnospiraceae ococcaceae; g Faecalibacterium eriales; f Alcaligenaceae; g ostridiales; f Lachnospiraceae Root; p Firmicutes acteriaceae; g Bifidobacterium Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
8 Differential Abundance Tests Permutation Still Breast Feeding otu# otu pval 21 Veillonellaceae; g Veillonella <2e ostridiales; f Veillonellaceae <2e acteriaceae; g Bifidobacterium c Clostridia; o Clostridiales acteriaceae; g Bifidobacterium erobacteriaceae; g Escherichia nterococcaceae; g Enterococcus Veillonellaceae; g Veillonella teriales; f Enterobacteriaceae acteriaceae; g Bifidobacterium Veillonellaceae; g Dialister ococcaceae; g Faecalibacterium ococcaceae; g Faecalibacterium acteriaceae; g Bifidobacterium acteriaceae; g Bifidobacterium ococcaceae; g Faecalibacterium acteriaceae; g Bifidobacterium nterococcaceae; g Enterococcus ococcaceae; g Faecalibacterium c Clostridia; o Clostridiales s; f Micrococcaceae; g Rothia ostridiales; f Ruminococcaceae Bacteroidaceae; g Bacteroides ucomicrobiaceae; g Akkermansia eptococcaceae; g Streptococcus Lachnospiraceae; g Lachnospira Bacteroidaceae; g Bacteroides ostridiales; f Lachnospiraceae f Lachnospiraceae; g Blautia achnospiraceae; g Ruminococcus Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
9 Differential Abundance Tests Permutation Delivery (V/CS) otu# otu pval 186 Root; p Firmicutes Bacteroidaceae; g Bacteroides Bacteroidaceae; g Bacteroides ostridiales; f Lachnospiraceae Ruminococcaceae; g Clostridium Bacteroidaceae; g Bacteroides c Clostridia; o Clostridiales Bacteroidaceae; g Bacteroides Bacteroidaceae; g Bacteroides c Clostridia; o Clostridiales Clostridiaceae; g Clostridium es; f Erysipelotrichaceae; g ; f Clostridiaceae; g Sarcina tinobacteria; c Actinobacteria acteriaceae; g Bifidobacterium riobacteriaceae; g Collinsella f Lachnospiraceae; g Blautia Veillonellaceae; g Veillonella ostridiales; f Lachnospiraceae f Lachnospiraceae; g Blautia achnospiraceae; g Ruminococcus eptococcaceae; g Streptococcus acteriaceae; g Bifidobacterium ococcaceae; g Faecalibacterium lostridiales; f Clostridiaceae lostridiales; f Clostridiaceae acteriaceae; g Bifidobacterium erobacteriaceae; g Escherichia acteriaceae; g Bifidobacterium acteriaceae; g Bifidobacterium Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
10 Various Linear Models Candidates Poisson regression for count variables Issues with model assumptions and fit Some strategies to mitigate these Handles more complex relationships (non-binary independent variables) p-values can be misleadingly low! Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
11 Various Linear Models Candidates Zeroes GLM Hurdle Zero-Inflated Overdispersion Poisson Negative Binomial All models use canonical link When variable is binary, results are comparable to permutation tests Run into problems fitting the more flexible models Issue with quality of fit on all models (assumption violations, some gross) Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
12 Various Linear Models Candidates Model Selection Quantitatively Two criteria (and problems): Choose between models (different methods) Quality of model (what if all available models fit poorly) For the first, various principle-of-parsimony heuristics are applicable For the second, deviance might work Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
13 Various Linear Models Exemplifying Results Frequency Frequency Frequency p values from poisson regression p values Log deviance ratios from poisson regression Log deviance ratios Deviance based areas from poisson regression otu# otu pval 1 ostridiales; f Lachnospiraceae < 2.22e-16 2 f Lachnospiraceae; g Blautia < 2.22e-16 3 achnospiraceae; g Ruminococcus < 2.22e-16 4 acteriaceae; g Bifidobacterium < 2.22e-16 5 eptococcaceae; g Streptococcus < 2.22e-16 6 acteriaceae; g Bifidobacterium < 2.22e-16 8 lostridiales; f Clostridiaceae < 2.22e-16 9 lostridiales; f Clostridiaceae < 2.22e acteriaceae; g Bifidobacterium < 2.22e erobacteriaceae; g Escherichia < 2.22e acteriaceae; g Bifidobacterium < 2.22e ostridiales; f Lachnospiraceae < 2.22e ostridiales; f Lachnospiraceae < 2.22e riobacteriaceae; g Collinsella < 2.22e Bacteroidaceae; g Bacteroides < 2.22e Lachnospiraceae; g Lachnospira < 2.22e ococcaceae; g Faecalibacterium < 2.22e Veillonellaceae; g Veillonella < 2.22e ucomicrobiaceae; g Akkermansia < 2.22e Bacteroidaceae; g Bacteroides < 2.22e omonadaceae; g Parabacteroides < 2.22e ostridiales; f Lachnospiraceae < 2.22e ostridiales; f Lachnospiraceae < 2.22e acteriaceae; g Bifidobacterium < 2.22e Bacteroidaceae; g Bacteroides < 2.22e treptococcaceae; g Lactococcus < 2.22e ipelotrichaceae; g Clostridium < 2.22e es; f Erysipelotrichaceae; g < 2.22e uminococcaceae; g Ruminococcus < 2.22e bacillales; f Streptococcaceae < 2.22e-16 Tail areas Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
14 Various Linear Models Exemplifying Results Frequency Frequency Frequency p values from NB regression p values Log deviance ratios from NB regression Log deviance ratios Deviance based areas from NB regression otu# otu pval 116 cteriales; f Coriobacteriaceae < 2.22e obacteriaceae; g Adlercreutzia < 2.22e ostridiales; f Lachnospiraceae < 2.22e lonellaceae; g Acidaminococcus < 2.22e tobacillaceae; g Lactobacillus < 2.22e Veillonellaceae; g Dialister < 2.22e Coriobacteriaceae; g Slackia < 2.22e tinobacteria; c Actinobacteria < 2.22e cteriales; f Coriobacteriaceae < 2.22e Moraxellaceae; g Acinetobacter e ostridiales; f Lachnospiraceae e teriales; f Enterobacteriaceae e ipelotrichaceae; g Clostridium e tobacillaceae; g Lactobacillus e uminococcaceae; g Ruminococcus e Veillonellaceae; g Megasphaera e tinobacteria; c Actinobacteria e Root; p Firmicutes e Clostridiaceae; g Clostridium e-09 8 lostridiales; f Clostridiaceae e c Clostridia; o Clostridiales e ostridiales; f Veillonellaceae e c Clostridia; o Clostridiales e ostridiales; f Lachnospiraceae e f Lachnospiraceae; g Blautia e ostridiales; f Lachnospiraceae e Prevotellaceae; g Prevotella e omonadaceae; g Parabacteroides e es; f Erysipelotrichaceae; g e tobacillaceae; g Lactobacillus e-07 Tail areas Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
15 Various Linear Models Statistical issues Traditional diagnostics would make the NB and its variants appealing Concerning distributional issues with OTUs Example of a significant OTU: NB(µ = 21.39, θ = ) bf bf Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
16 Various Linear Models Statistical issues Picking significant OTUs is highly characteristic of individual methods (inflated false positives) Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
17 Next Steps... In this framework Poorly fitting models may benefit regression from finite mixtures of poisson/nb to split the extremes (group starvation is an issue) Adjustments by cohort when START arrives For variables with ordinality, apply model selection among the well-fitting models components. Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
18 Fin Mateen and Joseph (McMaster) Development of OTU Analysis in NutriGen December / 18
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