deletions | additions       diff --git a/Methods.md b/Methods.md  index 5930742..1eb553a 100644  --- a/Methods.md  +++ b/Methods.md 
...
#Sample #Methods  ##Sample  Collection #Survey ##Survey  of Microbial Community Composition #Statistical ##Statistical  Analyses Unless otherwise noted, all statistical analyses were performed using python scripts implemented in QIIME v. 1.8.0, and all python scripts referenced here are QIIME scripts. The IPython notebook file used for all QIIME analyses is available HERE. To explore the differences in overall microbial community composition across the 15 meals, both the phylogenetic weighted UniFrac distances (REF) and the taxonomic Bray-Curtis dissimilarities (REF) were calculated using the beta\_diversity\_through\_plots.py script. To test for the significance of dietary pattern on the overall microbial community composition, we used a permutational multivariate ANOVA as implemented in the compare\_categories.py script. To test for significant differences in taxonomic richness across dietary patterns, we used the non-parametric Kruskal-Wallis test with the FDR (false discovery rate) correction as implemented in compare\_alpha\_diversity.py. To test for the significant variation in frequency of individual OTUs across dietary patterns, we used the Kruskal-Wallis test with the FDR correction as implemented in the group_significance.py script. To test for significant correlation between the relative abundance of a single taxonomic group and meal metadata categories at 5 taxonomic levels (phylum-genus,) Pearson correlation coefficients were calculated and tested for statistical significance using Stata