SEMplMe

Implementation of the SEMplMe algorithm to integrate SEMpl with methylation data

Sierra S Nishizaki and Alan P Boyle, SEMplMe: A tool for integrating DNA methylation effects in transcription factor binding affinity predictions, BiorXiv 2020.

We have made all of the SEMs generated as part of this work available here.

System Requirements

Hardware Requirements

Generation of a SEM requires variable RAM and disk storage based on the size of the initial PWM being considered. For minimal performance, we recommend a computer with the following specs:

RAM: 64+ GB
CPU: 8+ cores, 3.4+ GHz/core

The runtime on this minimal system is approximately 38 CPU hours. Compile time is approximately 35 seconds.

Software Requirements

The package development version is tested on Linux operating systems. In order to compile properly, you will need a version of GCC that includes the C++11 standard (versions newer than 5.0). The developmental version of the package has been tested on the following systems:

Linux: Ubuntu 18.04
Packages: libcurl4-dev

Installation

Clone a copy of the SEMplMe repository and submodules. This contains a copy of the SEMpl application that also has to be built. For any issues with building and running SEMpl, please see the SEMpl repository: https://github.com/Boyle-Lab/SEMpl. The build instructions for SEMpl are also below:

git clone --recurse-submodules https://github.com/Boyle-Lab/SEMplMe.git

Build external libraries:

cd SEMplMe/lib/libBigWig
make
cd ..
make
mv */*.so .
cd ..

Symlink to bowtie index location (use your own index location):

ln -s /data/genomes/hg38/bowtie_index/ data

Build SEMpl

make

SEMplMe functions on SEMpl output, please run SEMpl before attempting to use SEMplMe outside of the demo. Example:

./iterativeSEM -PWM examples/MA0114.1.pwm -merge_file examples/wgEncodeOpenChromDnaseHepg2Pk.narrowPeak -big_wig examples/wgEncodeHaibTfbsHepg2Hnf4asc8987V0416101RawRep1.bigWig -TF_name HNF4A -genome data/hg19 -output results/HNF4A

For more information on SEMpl please go to https://github.com/Boyle-Lab/SEMpl

SEMplMe Usage Information

Required Options:
 --TF_name TF name
 --WGBS path to WGBS data

 (1) <TF_name>.me.sem -- has the numerical values of the SNP Effect Matrix with methylation
 (2) <TF_name>_semplot.me.pdf -- graphical representation of the SNP Effect Matrix with methylation 
                               Bed and signal files from intermediate steps can also be kept  (.me)

SEMplMe Demo

SEMplMe requires whole genome bisulfite sequencing (WGBS) data, which can be downloaded from ENCODE. Of note, SEMplMe uses WGBS data in .wig format. Preconverted .bigwig to .wig files are available for download from dropbox. The following example will build the SEM with methylation for HNF4a in HepG2 cells given the example data including a precomputed example SEMpl output

cd examples

wget "https://www.dropbox.com/s/ila7tq11w6o7nke/ENCFF073DUG.wig.tar.gz"

tar -xvf ENCFF073DUG.wig.tar.gz

cd ..

perl ./generateSignalMethylTable.pl --TF_name HNF4A --WGBS examples/ENCFF073DUG.wig

Expected SEMplMe output

We include a small demo of SEMplMe for HNF4A in HepG2 cells. The expected output is:

Integrating methylation...Done
Creating SEM...Done
Creating R plot................................................................\
.............................................Done

WGBS datasets

Available in .wig format for download from dropbox

HepG2:
wget "https://www.dropbox.com/s/ila7tq11w6o7nke/ENCFF073DUG.wig.tar.gz"

K562:
wget "https://www.dropbox.com/s/lc8ltup91j1jb8j/ENCFF872YSC.wig.tar.gz"

GM12878:
wget "https://www.dropbox.com/s/zhqk6xyxoe0kqa1/ENCFF796NFQ.wig.tar.gz"

IMR-90:
wget "https://www.dropbox.com/s/fjd9hgqeo1pdjj9/ENCFF433WIE.wig.tar.gz"

H1-hESC:
wget "https://www.dropbox.com/s/wlhs8omjn70ajh7/ENCFF770YJW.wig.tar.gz"

GM23248:
wget "https://www.dropbox.com/s/k8ir44dn21e1lgo/ENCFF390POK.wig.tar.gz"