Read about ChIPmunk versions below.
Read about it below.
use 'mask' to mask already identified motifs in your sequences and 'filter' to filter out the whole sequences with already identified motifs

What it does

(di)ChIPmunk detects over-represented non-overlapping motifs in fasta sequences.

Which ChipMunk should you choose : Mononucleotides Vs Dinucleotides

In terms of the consensus sequence, in general you should get very similar results from the mono- and dinucleotide versions.

Type of the sequence set

Simple : for simple mutil-fasta to be searched in a double-strand DNA mode (the most common choice):

> header1
> header2

You can omit fasta headers since ChIPMunk would simply skip them.

Peak : for peak data with the positional prefences profile (often provided in wiggle-files, .wig). The profile of each sequence should be places in the fasta-header like:

> 1.0 2.0 3.0 2.0 1.5 2.0
> 1.0 2.0 3.0 2.0 1.5

See "Peak multi-fasta generator" in the tool pannel, if you wish to generate peak data.

NOTE that When base coverage information is available, it is highly recommaned to use peak data. This is extremely important for ChIPMunk performance.

Cite ChIPMunk

If you want to cite ChIPMunk in your research please refer to [1] for the basic mononucleotide version and to [2] for the dinucleotide version :

[1] Deep and wide digging for binding motifs in ChIP-Seq data. Kulakovskiy IV, Boeva VA, Favorov AV,Makeev VJ. Bioinformatics. 2010 Oct 15;26(20):2622-3. doi: 10.1093/bioinformatics/btq488. Epub 2010 Aug24.

[2] From binding motifs in ChIP-Seq data to improved models of transcription factor binding sites.Kulakovskiy I, Levitsky V, Oshchepkov D, Bryzgalov L, Vorontsov I, Makeev V. J Bioinform Comput Biol.2013 Feb;11(1):1340004. doi: 10.1142/S0219720013400040. Epub 2013 Jan 16.