The Stowers Institute contributing authors have selected to
present the raw data of this manuscript resulting from work performed at The
Stowers Institute. Data sets have been deposited in GEO under the accession
number GSE137193. Data used to train, evaluate and interpret the BPNet
models are found on ZENODO. The analysis code for the manuscript is
available in GitHub under the "kundajelab/bpnet-manuscript"
repository. The BPNet software package is available at GITHUB. The
ChIP-nexus data processing pipeline is available at GITHUB. Software to trim and
de-duplicate ChIP-nexus reads is available at <a href="https://github.com/Avsecz/nimnexus/" target="_blank" title="https://github.com/avsecz/nimnexus/" rel="noopener nofollow noreferrer">GITHUB</a>. The
BPNet model trained on ChIP-nexus data is available on Kipoi under the name
"BPNet-OSKN". Genome browser tracks showing observed/predicted
ChIP-nexus signal and the contribution scores for all factors are available
Stowers Original Data Repository
Supporting the scientific spirit of transparency, the Stowers Institute for Medical Research makes the data underlying its scientific publications freely accessible to the scientific community. Access to original, unprocessed data allows other scientists to validate and extend findings made by Stowers researchers.