Total Functional Score of Enhancer Elements Identifies Lineage-Specific Enhancers that Drive Differentiation of Pancreatic Cells

This directory contains the scripts for identification of TFs maintaining multipotency of endodermal stem cells during differentiation into pancreatic lineages ,using TFSEE.

Dependencies

This code requires python 2.7+ to run.

The pythons scripts require the following python packages:

• biopython-1.70
• pandas-0.20.1
• numpy-1.12.1
• scikit-learn-0.18.1
• matplotlib-2.0.2
• seaborn-0.8.1
• scipy-0.19.0

Install the dependencies.

pip install -r requirements.txt

Pipeline Description

This pipeline uses data from the following analysis to be used as input.

1. De novo identification of enhancers using GRO-seq and groHMM

2. Normalize Enhancer Expression using GRO-seq: For each cell line, quantify the GRO-seq reads, RPKM, that fall within a 1 kb region around the center of the overlap for paired enhancer transcripts or from the 5′ end of unpaired enhancer transcripts

3. Normalize Enhancer Expression using ChIP-seq: For each cell line, quantify the ChIP-seq reads, RPKM, from H3K4me1, H3K27ac, and input for each enhancer within the universe of GRO-seq-defined enhancers

4. Motif Predictions: De novo motif analyses on a 1 kb region of expressed enhancers for each cell line using MEME and matched to known motifs using TOMTOM and JASPAR

5. Normalize Transcription Factor Expression using RNA-seq: For each cell line, quantify the RNA-seq reads, FPKM, for each transcription factor that is a binding target for the motifs

6. Calculate TFSEE score to determining cell-type specific enhancer activity, generating:

• unsupervised hierarchical clustering
• tSNE representation
• boxplot representations
• rank order TF plots

Scripts

• Compute TFSEE to identify cognate transcription factors are under 'analysis'

• TFSEE using GRO-seq:
  • GRO_seq_TFSEE:
    • matrix_analysis.py: TFSEE score integration
    • rank_order.py: Rank order TF's clusters
• TFSEE using histone modifications ChIP-seq:
  • GRO_seq_TFSEE:
    • matrix_analysis.py: TFSEE score integration
    • rank_order.py: Rank order TF's clusters