Process Description

Loess Normalization

The Loess Normalization process normalizes data across arrays using a loess smoothing model. You can use the average across arrays and channels as the baseline for normalization or you can specify one array and channel to be used as the baseline.

Note: If you want to perform within-array loess normalization for two-channel arrays, run the Ratio Analysis process, instead.

What do I need?

Two data sets are required to run this process.

The first data set, 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 second data set is the Experimental Design Data Set (EDDS). This required data set tells how the experiment was performed, providing information about the columns in the input data set. Note that one column in the EDDS must be named ColumnName and the values contained in this column must exactly match the column names in the input data set.

The drosophilaaging_exp.sas7bdat EDDS, is shown below. Note that the ColumnName column lists the column names in the input data set. The Array column corresponds to an index variable. Note the variables describing experimental conditions.

A third, optional data set is the Baseline Reference Data Set. A baseline reference data set is generally used when you have a large set of reference arrays and you would like to add a few new arrays to an existing distribution. This data set should be in the tall format and contain both a baseline reference column and columns to merge with the input data set.

The drosophilaaging.sas7bdat and drosophilaaging_exp.sas7bdat data sets are included in the Sample Data folder.

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

Output/Results

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