We will first install pip as follow :

sudo easy_install pip

Alternative : Linux users may prefer

 apt-get install python-pip 

Now we will install suds via pip:

sudo pip install suds

Alternative :Linux users may prefer

apt-get install python-suds

1. Install pip with these instructions . Note from Stackoverflow: pip.exe will be placed inside your Python installation's Scripts folder, which is likely not on your path (fix that by running C:\PythonXX\Tools\Scripts\win_add2path.py. Download get-pip.py, being careful to save it as a .py file rather than .txt.
2. Now we will install suds via pip:

    pip install suds

Schmidt, Wilson and Ballester published a ChIP-seq experiment on liver tissue to identify binding regions for the transcription factor CEBPa (PMID:20378774) in five different species (human, mouse, dog, short-tailed opossum and chicken). This data set is publicly available through arrayexpess (E-TABM-722).
As done by the authors, CEBPa binding regions (peaks) were called using SWEMBL with parameter R=0.05, merged reads from two biological replicates and their corresponding input controls. For this tutorial we will analyze CEBPa binding pattern in dog, peaks can be downloaded from here.

1. Save this Python script fetch-sequences_soap.py on your computer
2. Run the script a first time to get the help by typing

   python fetch-sequences_soap.py -h

   
   
   Which files do you need, according to the help of the program ?
   

   [Show tip]

   usage: fetch-sequences_soap.py  -b BED_FILE -g GENOME_NAME

   You need a coordinate file (peaks) in BED format.
3. Now run the script to retrieve the sequences corresponding to the CEBPa peak coordinates. Save this file on your machine and adapt the file path of the command to the files as needed for your computer. The genome is the dog CanFam2 assembly

python fetch-sequences_soap.py -b do61+do79_cfam_CEBPA_liver.bed.SWEMBL.3.3.bed -g canFam2



4. You should obtain the results from fetch-sequences. Note that this analysis did not run on your computer, but used the computing power of the remote RSAT server.

1. Save this Python script matrix_scan_soap.py on your computer
2. Run the script a first time to get the help by typing

   python matrix_scan_soap.py -h

   
   
   Which files do you need, according to the help of the program ?
   

   [Show tip]

   usage: matrix_scan_soap.py [-h] -s SEQUENCE_FILE -m MATRIX_FILE -u P-VALUE

   You need a sequence file in FASTA format and a matrix file in TRANSFAC format.
3. Now run the script to scan the CEBPa peak sequences with the first discovered motif (session1, oligos_6nt_mkv4_m1). Adapt the file path to the files as needed for your computer.

python matrix_scan_soap.py -s 1_do61+do79_cfam_CEBPA_liver.SWEMBL.3.3_peaks.fasta -m peak-motifs_oligos_6nt_mkv4_m1.tf -u 0.0001 > cebpa_oligos_6nt_mkv4_m1_10-4.ft



4. You should obtain the results from matrix-scan within the file cebpa_oligos_6nt_mkv4_m1_10-4.ft. Note that this analysis did not run on your computer, but used the computing power of the remote RSAT server.