Factor Analysis Normalization

The Factor Analysis Normalization process normalizes data by subtracting the first set of principal components approximations from the raw data.

Note : You should exercise caution when using this method, as it directly removes the largest sources of variability in the data without regard to their experimental meaning.

What do I need?

One data set is required to run this process.

The Input Data Set contains all of the numeric data to be analyzed. This data set must be in the tall format where each sample corresponds to one row and each column corresponds to a separate experimental condition or array.

The drosophilaaging.sas7bdat data set, shown below, is a normalized data set derived from the Drosophila Aging experiment described in Sample Case Studies . It has 49 columns and 100 rows corresponding to 49 arrays and 100 individual probes , respectively.

The drosophilaaging.sas7bdat data set is included in the Sample Data folder.

For detailed information about the files and data sets used or created by JMP Life Sciences software, see Files and Data Sets .

Output/Results

Refer to the Factor Analysis Normalization output documentation for detailed descriptions of the output of this process.