Sentence examples for bacterial community data from inspiring English sources

The nonparametric nature of these ecological analysis methods is highly suitable for human bacterial community data, which are frequently zero-rich, highly-skewed, and non-normal and remains non-normally distributed post-data transformation.

Next we analyzed the genus-level bacterial community data using principal components analysis (PCA, Figure 3A) to create a community ordination and examine which elements of the community have the strongest influence in the variation between subjects.

Concerning the bacterial community data analysis, the associations among the community composition (height data of OTUs) were explored firstly using Principal Component Analyses (PCA).

Secondly, the relationship between the observed bacterial community composition (height data of OTUs) and the experimental factors (membrane type and experimental condition (adhesion versus biofilm)); adhesion versus biofilm versus Ringer)) was explored by means of Redundancy Analysis (RDA).

The SPSS IBMM Corp), Fast UniFrac (http://bmf2.colorado.edu/fastunifrac/) and QIIME (http://qiime.sourceforge.net/) software were used to analyze sequence data, bacterial community distribution and the principal component.

In our study, based on ANOSIM β diversity, the overall bacterial diversity of leaves and roots of EV and ir AOC genotypes was not significantly different, and we did not find a consistent clustering based on genotype (Fig. 1A ) by qualitative data, and the bacterial community composition was highly heterogeneous among replicate plants based on qualitative and quantitative data.

To assess the significance correlation between environmental data with the bacterial community composition obtained by DGGE, a Mantel test was performed (R packageade4, mantel.rtest, 999 iterations [ 37]).

The bacterial community was much more diverse than the fungal community (data not shown).

Bacterial 16S rRNA gene sequences were also detected by the V3-V5 primer set and inconsistent results in the bacterial diversity and the abundance patterns of bacterial community were observed between V1-V3 and V3-V5 data sets.

The minimum stress solution from this was used to produce the nMDS plots in which each data point represents the bacterial community found in one sample.

The data was used to analyze bacterial community variations and their correlation with body weight.