Data

Enhancer Identification

This manuscript was published by Genome Biology on September 27, 2016. Click here to download the PDF at Genome Biology.

 

Raw Data

Raw sequencing data for this paper were deposited with NCBI GEO under accession number GSE68983.

 

Analysis Code

The analysis code is available on GitHub: koenecke_enhancer_papers_2016.

 

Virtual Server

We have also made available a virtual server image with all the software packages, analysis code and raw data used in the paper. This virtual server is hosted by Amazon Web Services (AWS) as an Amazon Machine Image (AMI).  Please see the AWS web page for information about this service. Specific instructions regarding our AMI are below.

AMI ID: ami-6ba0d37c (requires an Amazon Web Services account)

This AMI was built from the official Ubuntu 15.04 image. A list of packages installed on the instance (both Ubuntu and R/Bioconductor) is available here.

 

Launching an Instance

Use the AMI link above after logging in to your AWS account to launch an instance based on this AMI. If you plan to re-run the analysis, we recommend using an instance with at least 32GB of memory. Please note you will be charged by Amazon for both the instance running time and the instance storage, which is 150GB due to the large amount of included raw and processed data files.

 

Connecting to the Instance

As the AMI runs Ubuntu 15.04, you should login via SSH using the "ubuntu" user and the SSH private key you supplied during instance creation.

 

Location of Files

All analysis code is in /data/analysis/enhancer_papers. This directory is a clone of our GitHub repository. You might consider performing a "git pull" from this directory to update the code to the latest version available on GitHub.

Raw and processed data files can be found in various directories inside /data.

Please feel free to contact us if you have any questions or comments about the AMI or analysis code.