# Relative Quantitation

Relative quantitation normalises your data by adjusting it relative to the values in another data store. This process is commonly used to remove one source of variation (an input sample for example) from another sample (a ChIP sample for example).

## Options

The main options for this method are the pairings of references and targets. The options panel shows a list of all samples which could act as reference on the left and the set of targets which can be corrected on the right. Replicate sets are not shown since these are not themselves quantitated, but simply show the average quantiation of the data stores they contain. To pair up a reference with a sample first select the reference you want to use from the list on the left. Then you can select one or more samples in the table on the right by ticking the appropriate check boxes. You can then press "Apply to Selection" to assign that reference to those targets. Selecting a second reference for a target will remove the first selection. Assigning a reference with no reference selected will clear any previous assignment for the selected samples.

Other options you have for this module are:

1. How you want to do the relative quantitation (subtract, log subtract, divide or log divide). Please note that if 'divide' or 'log divide' are selected, a minimum reference value threshold of 0.001 will be applied, this is to avoid infinite values where the reference value is either very small or zero. If your enrichment could be either positive or negative you should take a log ratio so that the positive and negative scales are treated the same.