TSS Normalisation

mixMC: TSS Normalisation

Here we use the Human Microbiome Most Diverse 16S data set as a worked example for TSS Normalisation which follows prefiltering in data analysis using mixMC.

Normalisation

The normalisation steps outlined in the example below describe the normalisation process of filtered microbiome sequencing data counts using TSS normalisation.

TSS Normalisation

Total Sum Scaling(TSS) normalises count data by dividing variable read count by the total number of read counts in each individual sample.

# each variable read count is divided by the total no. of read counts
TSS.divide = function(x){
 x/sum(x)
}
# function is applied to each row
data.TSS = t(apply(data.filter, 1, TSS.divide))
## Error in t(apply(data.filter, 1, TSS.divide)): error in evaluating the argument 'x' in selecting a method for function 't': Error in apply(data.filter, 1, TSS.divide) : 
##   object 'data.filter' not found

Transformation

If normalisation = 'TSS', then a ILR transformation follows to account for compositional data inside the pca.R function. The components and loading vectors are back transformed inside the function to a CLR space.