The purpose of this Core is to provide bioinformatics analysis of transcriptomic, and DNA-protein interactions. Next-generation sequencers have transformed genomic research, yet the analysis of this data remains a bottleneck. Our Core will provide the essential data analysis service to render this data accessible and interpretable to the members of this CORT. The PI and staff of this Core have extensive experience in the analysis of genomic data, as well as familiarity with the underlying biology of the associated projects. Despite the fact that microarray and sequencing cores exist at UCLA, none of these provide data analysis as a service. Therefore the typical biology group that does not have internal computational expertise is often left with data and no ability to interpret it. The Core we are proposing here will remove this impediment so that all the groups within this Program Project will be able to not only collect sequencing data from their samples, but also obtain processed and analyzed data that can be directly interpreted by researchers without computational expertise. This functionality should render genomics research far more accessible to all members of this Program Project. We will also work with more computationally more experienced researchers in each lab of this Program to refine analysis tools.
The Aims of this Core are: 1. Analysis of RNA-seq data: we will provide quantification and variant detection analyses of RNA-seq data. 2. Analysis of ChlP-seq data: we will provide the location of peaks, average peak distributions and motifs. 3. Data display on genome browser: in all cases this core will also load genome-wide data onto our installation of the UCSC genome browser so that users can see at single base resolution the data generated from each sample. We will also upload data and analysis tools to the Wiki site for exchange. 4. Data Quality metrics: we will generate quality metrics for sequence data to provide an estimate of the quality of the sample.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Specialized Center (P50)
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Special Emphasis Panel (ZAR1-KM)
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University of California Los Angeles
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Inkeles, Megan S; Scumpia, Philip O; Swindell, William R et al. (2015) Comparison of molecular signatures from multiple skin diseases identifies mechanisms of immunopathogenesis. J Invest Dermatol 135:151-9
Smale, Stephen T (2014) Transcriptional regulation in the immune system: a status report. Trends Immunol 35:190-4
Montoya, Dennis; Inkeles, Megan S; Liu, Phillip T et al. (2014) IL-32 is a molecular marker of a host defense network in human tuberculosis. Sci Transl Med 6:250ra114
Adams, John S; Rafison, Brandon; Witzel, Sten et al. (2014) Regulation of the extrarenal CYP27B1-hydroxylase. J Steroid Biochem Mol Biol 144 Pt A:22-7
Chun, Rene F; Liu, Philip T; Modlin, Robert L et al. (2014) Impact of vitamin D on immune function: lessons learned from genome-wide analysis. Front Physiol 5:151
Teles, Rosane M B; Graeber, Thomas G; Krutzik, Stephan R et al. (2013) Type I interferon suppresses type II interferon-triggered human anti-mycobacterial responses. Science 339:1448-53