Commit fab6fdfa authored by Christian Arnold's avatar Christian Arnold
Browse files update

parent 46454588
......@@ -2,47 +2,23 @@
Genome-wide quantification of differential transcription factor activity: diffTF
Thank you for the interest in diffTF! If you have questions or comments, feel free to contact us. We will be happy to answer any questions related to this project as well as questions related to the software implementation.
Transcription factor (TF) activity constitutes an important readout of cellular signalling pathways and thus for assessing regulatory differences across conditions. However, current technologies lack the ability to simultaneously assessing activity changes for multiple TFs and surprisingly little is known about whether a TF acts as repressor or activator. To this end, we introduce the widely applicable genome-wide method diffTF to assess differential TF binding activity and classifying TFs as activator or repressor by integrating any type of genome-wide chromatin with RNA-Seq data and in-silico predicted TF binding sites
[A detailed Documentation is available here](
[A detailed Documentation is available here](
Installation and Quick Start
The following quick start briefly summarizes the necessary steps to use our pipeline:
1. Install the necessary tools (Snakemake, samtools, bedtools, and Subread). We recommend installing them via conda, in which case the installation is as easy as
``conda install -c bioconda snakemake bedtools samtools subread``
If conda is not yet installed, follow the [installation instructions]( If you want to install the tools manually and outside of the conda framework, see the following instructions for each of the tools: [snakemake](, [samtools](, [bedtools](, [Subread](
2. Clone the Git repository:
``git clone``
3. To run the example analysis for 50 TF, simply perform the following steps:
* Change into the *example/input* directory within the Git repository
``cd diffTF/example/input``
* Download the data via the download script
* To test if the setup is correct, start a dryrun via the first helper script
* Once the dryrun is successful, start the analysis via the second helper script
4. To run your own analysis, modify the files config.json and sampleData.tsv. See the instructions in Section 3 in the [Documentation]( for more details.
5. If your analysis finished successfully, take a look into the *FINAL_OUTPUT* folder within your specified output directory, which contains the summary tables and visualization of your analysis. If you received an error, take a look into Section 4 in the [Documentation]( to troubleshoot.
[Please see the Documentation for easy Installation and Quick Start instructions.](
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment