HMP Bodysites Case Study

For background information on the mixMC, multilevel or sPLS-DA methods, refer to the MixMC Method Page, Multilevel Page or sPLS-DA Method Page.

The R script used for all the analysis in this case study is available here.

More information on Plots

For a more in depth explanation of how to use and interpret the plots seen, refer to the following pages:

• plotIndiv() – Sample Plot
• plotLoadings() – Loading Plot
• plotVar() – Correlation Circle Plot
• cim() – Cluster Image Maps

More information

More details on microbiome preprocessing steps.

References

1. Filzmoser, P., Hron, K. and Reimann, C., 2009. Principal component analysis for compositional data with outliers. Environmetrics, 20(6), pp.621-632.
2. Lê Cao KA, Costello ME, Lakis VA, Bartolo F, Chua XY, et al. (2016) MixMC: A Multivariate Statistical Framework to Gain Insight into Microbial Communities. PLOS ONE 11(8): e0160169. doi: 10.1371/journal.pone.0160169
3. Lê Cao, K.A., Boitard, S. and Besse, P., 2011. Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems. BMC bioinformatics, 12(1), p.1.
4. Rohart F, Gautier B, Singh A, Lê Cao K-A (2017). mixOmics: an R package for ‘omics feature selection and multiple data integration.