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
- 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
- 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