RAP - Motif finding from protein binding microarray dataRAP (short for Rank, Align, PWM) is a software for inferring binding site motifs from protein binding microarrays (PBMs). RAP takes as input a PBM file (a list of DNA probe sequences with their binding sintensity) and outputs the binding site of the TF as a potision weight matrix. Further details on the functionality of RAP are available in the paper listed below.RAP was developed by Yaron Orenstein with Eran Mick in Ron Shamir's Computational Genomics group at Tel Aviv University. |
This distribution is our officially supported executable for RAP. This binary is completely self-contained and should work out of the box without any issues. The package includes a small test dataset.
The software is freely available under the GNU Lesser General Public License, version 3, or any later version at your choice.
RAP is a research tool, still in the development stage. Hence, it is not presented as error-free, accurate, complete, useful, suitable for any specific application or free from any infringement of any rights. The Software is licensed AS IS, entirely at the user's own risk.
java -jar RAP.jar <param_file> <PBM_file> <output_file>
Detailed description of parameters in file param.docx.
param_pbm.txt is an example parameters file.
PBM file can be downloaded from UNIPROBE database (http://the_brain.bwh.harvard.edu/uniprobe/).
Example run:
java -jar RAP.jar param_pbm.txt Arid3a_3875.1_v1_deBruijn.txt Arid3a_3875.1_v1.pwm
A: 0.183147132396698 0.22810086607933044 0.11032721400260925 0.8135622143745422 0.9158732891082764 . . . C: 0.2849732041358948 0.14351284503936768 0.32613304257392883 0.028032639995217323 0.017520010471343994 . . . G: 0.26065367460250854 0.10847616195678711 0.21236343681812286 0.11921338737010956 0.04402954876422882 . . . T: 0.2712264955043793 0.5199114084243774 0.35117655992507935 0.03919265791773796 0.022574998438358307 . . .Each line is of the form
nucleotide: [tab] probability_pos_1 [tab] probability_pos_2 [tab] . . .
RAP: Accurate and fast motif finding based on protein binding microarray data,
Yaron Orenstein, Eran Mick, Ron Shamir.
Journal of Computational Biology. May 2013, 20(5): 375-382.