Beta POC code for https://github.com/chengl7/IniMotif
*Alex Kearsey *Dr Lu Cheng *Joel Southgate *Anna Price *WebLogo source code
Python scripts for extracting TF motif from SELEXseq data.
The recommended way to setup your computer for running Inimotif is to install the official distribution of Python 3.7. You can download the official Python 3.7 distribution here. Once you've installed Python, open the terminal/prompt and enter the following command:
pip install -r requirements.txt
This will install the required python packages that Inimotif needs to run. Note that Inimotif may work for versions of Python 3 prior to 3.7, but this is untested. For Mac you may need to update Tcl/Tk to use the GUI for versions of Python prior to 3.7.2. See here for more information.
Alternatively, you can also run Inimotif using Anaconda. To setup a conda environment and install the requirements:
conda create -y --name inimotif python==3.7
conda install -fyq --name inimotif -c conda-forge --file requirements.txt
conda activate inimotif
You can download Inimotif here. Open the HTMLmaker.py in python3 and enter data into the pop up window.
- On Mac/Linux
$ python3 HTMLmaker.py- On Windows
> python3 HTMLmaker.pyPress the "Enter" button and exit the GUI window. If the GUI does not show, there will be command line input prompts.
Figures are saved in a folder with the name of the analysis identidier and split into subfolders for the logos, hamming distance, position bias, and kmer frequency.
Analysis identifier - The output name for the results page and the folder that the figures are organised in
Path to directory - The path to the directory the data files are
Number of runs - How many files are being analysed
Reverse compliment - Should the kmers have their reverse compliment also counted
Logo format - What should the Y-axis be (bits or frequency) for the logos generated
Min k - Minimum length of kmers that should be counted
Max k - Maximum length of kmers that should be counted
Experiment type - Specify what experiment type has the data files come from
Multiple rounds in the same file - Are multiple rounds from the experiment contained in the same file (NB the 5' and 3' barcodes must be specified to distinguish between the runs)
Known barcode - If the 5' and 3' barcodes are known, they can be entered and removed from kmer counting (this is due to giving a false reading if counted)
Start round - What round/run number does the analysis start from (with large numbers of rounds in eg. a SELEX experiment, excluding the first few rounds can be faster for analysis)
Number of motifs - How many motifs should be calculated (generation of more than 1 motif will remove kmers used for previous logos for their generation)
Allowed hamming distance - At what hamming distance value (compared to the consensus kmer) should kmers be used for the making of the position weight matrix