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Research at DIMACS summer REU 2015 with Dr. Kevin Chen
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README.md
add_feature_v1.ipynb
add_feature_v2.ipynb
binary.py
binary_p300.py
exp.R
integrate_all.ipynb
logit.ipynb
p300.R
p300.ipynb
quicksect.py
svm.ipynb
tss.R
tss.ipynb

README.md

Repository Description

This repository contains the work I did for the DIMACS REU. See my webpage here for more information on the project.

Files Description

Data Integration

For Spectacle Input (Spectacle code can be found here)

  • binary.py - given multiple files (one per chromosome), adds additional feature (eRNA) to each file
  • binary_p300.py - same as binary.py but adds additional feature of p300 overlap

For SVM/Logit Input

  • integrate_all.ipynb - integrates chromatin marks, eRNA, p300, and tfbs into one file (extension of add_feature_v1); to add more features, use add_feature_v2
  • add_feature_v1.ipynb - given multiple files (one per chromosome), adds additional feature (p300) with output in one file for all chromosomes
  • add_feature_v2.ipynb - given one file (containing all chromosomes), adds additional feature (tfbs) to the file

Data Analysis

  • exp.R - conducts exploratory analysis of eRNA data with enhancer predictions and outputs eRNA data in condensed form
  • tss.ipynb - finds distances to nearest transcription start site for each state (labeled in Spectacle)
  • tss.R - plots output of tss.ipynb
  • p300.ipynb - finds overlap with p300 for each state (labeled in Spectacle)
  • p300.R - plots output of p300.ipynb

Machine Learning Models

  • svm.ipynb - runs support vector machine
  • logit.ipynb - runs logistic regression

Modules

  • quicksect.py - interval search with tree (imported from here)
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