{% extends "bootstrap/base.html" %} {% import "bootstrap/fixes.html" as fixes %} {% import "bootstrap/wtf.html" as wtf %} {% block head %}{{super()}}{{fixes.ie8()}}{% endblock %} {% block html_attribs %} lang="en"{% endblock %} {% block metas %} {% endblock %} {% block title %}LISA{% endblock %} {% block navbar %} {% endblock %} {% block styles %} {% endblock %} {% block content %}
The motivation of Lisa is to use public along with in-house chromatin profile data from a comprehensive database of human and mouse DNase-seq, and H3K27ac ChIP-seq profiles, to determine the transcription factors and chromatin regulators that are directly responsible for the perturbation of a differentially expressed gene set. To run LISA, the only thing you need is the differential gene list from whatever biological process you are interested in. The gene set can be official gene symbols or refseq ids (refseq ids should remove the version number, e.g., NM_001145775 or XR_112606). Then you will be able to leverage the power of the most comprehensive DNase and ChIP-seq database (CistromeDB) to discover the key transcription factors and chromatin regulators. One tip for viewing the TR ranking table is to click on those p-values, a Cistrome DB page will come along. For user who has plenty of gene sets, please use the local version of Lisa at github. If your encounter any issue, please contact lisa@jimmy.harvard.edu. If you like the tool, please cite the paper at biorxiv.
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