All Publications

  • A Customizable Analysis Flow in Integrative Multi-Omics. Biomolecules Lancaster, S. M., Sanghi, A., Wu, S., Snyder, M. P. 2020; 10 (12)


    The number of researchers using multi-omics is growing. Though still expensive, every year it is cheaper to perform multi-omic studies, often exponentially so. In addition to its increasing accessibility, multi-omics reveals a view of systems biology to an unprecedented depth. Thus, multi-omics can be used to answer a broad range of biological questions in finer resolution than previous methods. We used six omic measurements-four nucleic acid (i.e., genomic, epigenomic, transcriptomics, and metagenomic) and two mass spectrometry (proteomics and metabolomics) based-to highlight an analysis workflow on this type of data, which is often vast. This workflow is not exhaustive of all the omic measurements or analysis methods, but it will provide an experienced or even a novice multi-omic researcher with the tools necessary to analyze their data. This review begins with analyzing a single ome and study design, and then synthesizes best practices in data integration techniques that include machine learning. Furthermore, we delineate methods to validate findings from multi-omic integration. Ultimately, multi-omic integration offers a window into the complexity of molecular interactions and a comprehensive view of systems biology.

    View details for DOI 10.3390/biom10121606

    View details for PubMedID 33260881

  • Landscape of cohesin-mediated chromatin loops in the human genome. Nature Grubert, F. n., Srivas, R. n., Spacek, D. V., Kasowski, M. n., Ruiz-Velasco, M. n., Sinnott-Armstrong, N. n., Greenside, P. n., Narasimha, A. n., Liu, Q. n., Geller, B. n., Sanghi, A. n., Kulik, M. n., Sa, S. n., Rabinovitch, M. n., Kundaje, A. n., Dalton, S. n., Zaugg, J. B., Snyder, M. n. 2020; 583 (7818): 737–43


    Physical interactions between distal regulatory elements have a key role in regulating gene expression, but the extent to which these interactions vary between cell types and contribute to cell-type-specific gene expression remains unclear. Here, to address these questions as part of phase III of the Encyclopedia of DNA Elements (ENCODE), we mapped cohesin-mediated chromatin loops, using chromatin interaction analysis by paired-end tag sequencing (ChIA-PET), and analysed gene expression in 24 diverse human cell types, including core ENCODE cell lines. Twenty-eight per cent of all chromatin loops vary across cell types; these variations modestly correlate with changes in gene expression and are effective at grouping cell types according to their tissue of origin. The connectivity of genes corresponds to different functional classes, with housekeeping genes having few contacts, and dosage-sensitive genes being more connected to enhancer elements. This atlas of chromatin loops complements the diverse maps of regulatory architecture that comprise the ENCODE Encyclopedia, and will help to support emerging analyses of genome structure and function.

    View details for DOI 10.1038/s41586-020-2151-x

    View details for PubMedID 32728247

  • A knowledge base of vasopressin actions in the kidney. American journal of physiology. Renal physiology Sanghi, A. n., Zaringhalam, M. n., Corcoran, C. C., Saeed, F. n., Hoffert, J. D., Sandoval, P. n., Pisitkun, T. n., Knepper, M. A. 2014; 307 (6): F747–55


    Biological information is growing at a rapid pace, making it difficult for individual investigators to be familiar with all information that is relevant to their own research. Computers are beginning to be used to extract and curate biological information; however, the complexity of human language used in research papers continues to be a critical barrier to full automation of knowledge extraction. Here, we report a manually curated knowledge base of vasopressin actions in renal epithelial cells that is designed to be readable either by humans or by computer programs using natural language processing algorithms. The knowledge base consists of three related databases accessible at One of the component databases reports vasopressin actions on individual proteins expressed in renal epithelia, including effects on phosphorylation, protein abundances, protein translocation from one subcellular compartment to another, protein-protein binding interactions, etc. The second database reports vasopressin actions on physiological measures in renal epithelia, and the third reports specific mRNA species whose abundances change in response to vasopressin. We illustrate the application of the knowledge base by using it to generate a protein kinase network that connects vasopressin binding in collecting duct cells to physiological effects to regulate the water channel protein aquaporin-2.

    View details for DOI 10.1152/ajprenal.00012.2014

    View details for PubMedID 25056354

    View details for PubMedCentralID PMC4166727