# DESeq2 Filter

This is an R based filter so will only be available if you have configured R in the SeqMonk preferences and installed the pre-requisite packages

This filter can be used for differential count analysis. It is normally used in RNA-Seq workflows, but can actually be applied to many different experiment types where the underlying data is a set of read counts.

The filter allows you to select two or more replicate sets with at least two data stores in each and will identify probes whose representation in the two sets differs significantly. If exactly two replicate sets are selected then the standard DESeq workflow using a Wald test is performed. For more than 2 groups the DESeq Liklihood Ratio Test is used to identify differences between any groups.

For this filter to run correctly your data must fulfil two criteria

1. Your quantitation must be raw, uncorrected read counts. If you're using the RNA-Seq filter then you must select the "Generate Raw Counts" option. For other probe types you must use the read count quantitation with no normalisation or log transformation applied
2. You must use either all probes, or a representative subset of probes which are not biased by the differences between the two replicate sets your tring to compare

## Options

- You need to two Replicate Sets to compare from the list on the left.
- You need to select a p-value cutoff for the filter
- You can select whether multiple testing correction should be applied to your results. For your p-values to be valid you must leave this box checked
- You can choose whether the program applies independent filtering based on coverage to try to maximise the number of hits you get. Ticking this box may give you more hits, but at the cost of them being slightly more biased by coverage