Abstract

The observation that similar sets of transcription factor motifs are sometimes found in not so simlar cellular phenotypes suggests that gene epxression maybe a function of specific combinatorial arrangement(s) of the motifs within the regulatory segments of DNA. Deciphering the relationship between regulatory sequences and gene expression necessitates exploring complex sequence structures beyond individual motifs. CARTMAN (Co-occurrence Analysis of Repeating Transcription-factor Motifs And Networks) is a computational tool designed to discover and quantify motif co-occurrences within regulatory sequences. It facilitates downstream differential analysis of multi-motif complexes across distinct experimental conditions. Unlike high-complexity machine learning approaches that often produce inferred measures, CARTMAN delivers direct and interpretable metrics with minimal computational overhead and requires only basic user expertise. Building upon outputs from tools like HOMER and FIMO, CARTMAN represents a natural progression to basic motif discovery tools.

Citation

If you use CARTMAN in your work, please reference it as follows:

Saisan, P., & Glass, C. (2024). CARTMAN: Co-occurrence analysis of repeating transcription-factor motifs and networks (Version 0.1) [Computer software]. GitHub. https://github.com/psaisan/CARTMAN

BibTeX Entry

@misc{saisan2024cartman,
  author       = {Saisan, P. and Glass, C.},
  title        = {CARTMAN: Co-occurrence Analysis of Repeating Transcription-factor Motifs And Networks},
  year         = {2024},
  publisher    = {GitHub},
  howpublished = {\url{https://github.com/psaisan/CARTMAN}},
  version      = {0.1},
}

Installation

Prerequisites

• Python 3.7+
• HOMER Suite: Ensure that HOMER is installed and accessible in your system's PATH.

Steps

1. Clone the Repository

   git clone https://github.com/psaisan/CARTMAN.git
   cd CARTMAN
   

Example Notebook

View the CARTMAN Example Notebook

Data Source

The data used in this example is from a 2020 study, Seidman et al, looking at epigenomic changes in the immune system cells (Kupffer) as they undergo a diet induced transformation.

1. Peak file1: Regulatory DNA regions active in HEALTHY Kupffer cells

KCH_H3K_FC2_1000_w200.txt

2. Peak file2: Regulatory DNA regions active in MASH transformed Kupffer cells

KCN_H3K_FC2_1000_w200.txt

3. Target motif list file: Subset of HOMER identified motifs found in HEALTHY and MASH Kupffer cells

KCH_VS_KCN_w400_L70.motifs

Full datase on GEO: GSE128338