ConSReg

Condition-specific regulations

Getting Started

1. Installation

1.1 Required packages

1.1.1 Python

• python = 2.7
• numpy >= 1.9.0
• scipy >= 1.1.0
• pandas == 0.21.1
• joblib >= 0.12.5
• rpy2==2.8.6
• networkx >= 2
• sklearn >= 0.18.1
• intervaltree == 2.1.0

1.1.2 R

• ChIPSeeker == 1.16.1
• CoReg == 1.0.1
• gglasso == 1.4
• RRF == 1.9
• R >= 3.5.1

1.2 Python installation

ConSReg can be installed using pip:

pip install --user ConSReg

1.3 R installation

ConSReg requires several R packages: ChIPseeker, CoReg, gglasso and RRF.

To install ChIPSeeker from bioconductor, type the following commands in R environment:

source("https://bioconductor.org/biocLite.R")
biocLite("ChIPseeker")

Please refer to the instructions described here for more details.

To install CoReg pakcage from GitHub, type the following commands in R environment:

install.packages("devtools")
library(devtools)
install_github("LiLabAtVT/CoReg")

Please refer to the GitHub page of CoReg project for more details: link

To install gglasso package from CRAN, type the following commands in R environment:

install.pacakges("gglasso")

Please refer to the link here for more details.

To install RRF package from CRAN, type the following commands in R environment:

install.pacakges("RRF")

Please refer to the link here for more details.

2. Sample datasets

Sample datasets can be found in data folder.

3. Analysis

We provide code for analyzing the sample datasets in two jupyter notebooks located in the root folder of this project: bulk_analysis.ipynb (for bulk RNA-seq data) and single_cell_analysis.ipynb (for single cell RNA-seq data).

4. Publication

ConSReg is currently in review at Genome Research. We will soon provide a pre-print version of our manuscript.

Qi Song, Jiyoung Lee, Shamima Akter, Ruth Grene, Song Li. Accurate prediction of condition-specific regulatory maps in Arabidopsis using integrated genomic data (in review)