CURRENT COLLABORATIONS

The BDC Informatics Team is focused on using innovative and cutting-edge technologies to understand the role of different cell types in the development of diabetes. This includes studying immune cell populations to explore why immune cells are activated in T1D and studying islet cell populations to determine the transcriptional regulation and determination of islet cell fate and to understand how beta cells may be contributing to their own demise in T1D and T2D. We aim to understand the involvement of these cells in diabetes to work towards early detection, prevention, and a cure for diabetes.
We use cutting-edge sequencing technologies to investigate these topics, including multiome single-cell sequencing techniques such as scRNA-seq, scATAC-seq, antigen detection with scLIBRA-seq, surface protein profiling with CITE-seq, TCR and BCR sequencing with scVDJ-seq, and histone binding analysis using droplet-paired tag. Our team analyzes these complex datasets, develops novel algorithms for data processing, and creates predictive models to uncover meaningful correlations and insights.
 To the end, we closely collaborate with many of the labs at the Barbara Davis Center for Diabetes.

  • Sussel Lab

    Our collaborations with the Sussel lab focus on understanding the transcriptional regulation of islet cell fate and function. We use innovative tools to explore all levels of transcriptional regulation from transcription factor activity to RNA splicing, to RNA modifications. These collaborations utilize single cell RNA-seq, long read single cell RNA-seq with nanopore sequencing, direct RNA sequencing with nanopore, ChIP-seq, RNA-seq, and ATAC-seq. In these collaborations, we focus on developing and implementing novel tools to analyze these data and performing multiomic integration of the different sequencing modalities. See more about projects in in the Sussel lab (here)

  • Smith Lab

    The Smith lab and our team collaborate on projects that focus on unraveling the role of B cells in the development of T1D. We are using single cell technologies that pair VDJ, transcriptome, and antigen reactivity to discover the phenotypic markers of autoreactive B cells and to understand the changes in gene expression and clonal repertoire of islet-reactive B cells in healthy and autoimmune prone individuals. In these collaborations, we focus on developing pipelines to analyze the multiomic datasets, how to determine antigen reactivity from LIBRA-seq data, and we develop computational models to use VDJ information to predict autoreactivity and cell state of B cells. See more about projects in the Smith lab (here)

  • Friedman Lab

    We partner with the Friedman lab to evaluate the role of myeloid cells in the development of T1D. We are integrating single cell datasets from many different sources to generate a map of myeloid cells in mice and many different human donors. In these collaborations, we focus on identifying the best methods for data integration and differential expression across many donors and developing pipelines to remove phagocytosed passenger transcripts that can be identified in the myeloid cells.

  • Nakayama Lab

    Together with the Nakayama lab, we identify and characterize autoreactive T cells and novel autoantigens in T1D. The Nakayama lab has developed many novel methods to create high throughput assays to identify these autoreactive T cells and autoantigens. We have written many pipelines that can demultiplex and analyze the data generated by these new methods. We are also working closely with the Nakayama lab to pair single cell sequencing with detection of autoreactive TCRs.

  • Davidson Lab

    We collaborate with the Davidson lab to find biomarkers of T1D from peripherial blood. In this collaboration, we integrate multimodal single cell data with other measurement types to try to identify biomarkers in the blood.

  • Wortham Lab

    Our team has recently started a collaboration with the Wortham lab to explore the epigenetic regulation of beta cells in diabetes. These collaborations harness innovative technologies, like single cell droplet paired tag, to determine the histone landscape alongside the transcriptome in single cells.

Technical & Analytical Collaborations

In addition to our core partnerships, we also perform analysis of data for all
of the labs at the BDC! This includes analysis of bulk sequencing data,
planning sequencing experiments, performing motif finding, and planning genetic experiments.