We are a bioinformatics research lab in the Department of Biomedical Engineering at Johns Hopkins University. We are also a part of the Center for Computational Biology and Department of Computer Science.
We develop methods for analyzing spatially resolved transcriptomic sequencing and imaging data.
Spatial organization at both the subcellular-level within cells as well as the cellular-level within tissues play important roles in regulating cell identity and function. Recent technological advances have enabled high-throughput spatially resolved transcriptomic profiling at single-molecule and near-single-cell resolution. We develop machine learning and other statistical approaches as open-source computational software to take advantage of this new spatial information in deriving biological insights regarding how spatial organization plays a role in both healthy and diseased settings.
- Brendan F Miller, Lyla Atta, Arpan Sahoo, Feiyang Huang, Jean Fan^. Reference-free cell-type deconvolution of pixel-resolution spatially resolved transcriptomics data. bioRxiv. 2021. doi: 10.1101/2021.06.15.448381
- Lyla Atta, Arpan Sahoo, Jean Fan^. VeloViz: RNA-velocity informed embeddings for visualizing cellular trajectories. bioRxiv. 2021. doi: 10.1101/2021.01.28.425293
- Brendan F Miller, Dhananjay Bambah-Mukku, Catherine Dulac, Xiaowei Zhuang, Jean Fan^. Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities. Genome Research. 2021. doi:10.1101/gr.271288.120
- Chenglong Xia*, Jean Fan*, George Emanuel*, Junjie Hao, and Xiaowei Zhuang. Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression. PNAS. 2019. doi:10.1073/pnas.1912459116
We apply these methods to better understand the impact of cellular heterogeneity on cancer pathogenesis and prognosis.
Advancements in high-throughput sequencing and imaging technologies have uncovered tremendous genetic, epigenetic, transcriptional, and spatial heterogeneity in various cancers but their impact on clinical outcomes is not well understood. We establish close collaborations with clinical collaborators to develop and apply bioinformatics methods that contribute to a more complete understanding of how cellular heterogeneity impacts tumor progression, therapeutic resistance, and ultimately clinical prognosis. We are particularly interested in pediatric gliomas.
- Jean Fan^, Kamil Slowikowski, Fan Zhang. Single-cell transcriptomics in cancer - computational challenges and opportunities. Nature Experimental and Molecular Medicine. Sept 15, 2020, doi.org:10.1038/s12276-020-0422-0
- Jean Fan*, Hae-Ock Lee*, Soohyun Lee, Da-eun Ryu, Semin Lee, et al. Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq. Genome Research. 2018. doi:10.1101/gr.228080.117
- Lili Wang*, Jean Fan*, Joshua M. Francis, George Georghiou, Sarah Hergert, et al. Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia. Genome Research. 2017. doi:10.1101/gr.217331.116
- Reference-free cell-type deconvolution of pixel-resolution spatially resolved transcriptomics data on 16 June 2021
- Interactions between cancer cells and immune cells drive transitions to mesenchymal-like states in glioblastoma on 03 June 2021
- Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities on 25 May 2021
- VeloViz - RNA-velocity informed embeddings for visualizing cellular trajectories on 29 January 2021
- Spatial organization of the transcriptome in individual neurons on 08 December 2020
- We welcome Leela Mehta-Harwitz to the lab! Welcome Leela! on 22 June 2021
- Dr. Fan gives an invited seminar at the Spatial Omics Seminar series. on 11 June 2021
- Dr. Fan participates in the Break Through Cancer panel on Spatial Profiling. on 09 June 2021
- The JEFworks lab receives support from the NSF CAREER awards. on 08 June 2021
- Dr. Fan gives an invited seminar at the USC Biostatistics Division. on 20 May 2021
Latest Blog Posts
- Complementing single-cell clustering analysis with MERINGUE spatial analysis on 21 June 2021
- Randomly Generating Music with R on 19 April 2021
- Animating the Cell Cycle on 28 December 2020
- Using R To Find The Missing Faculty on 30 November 2020
- Using scVelo in R using Reticulate on 25 August 2020
- A Guide to Responding to Scientific Peer Review on 17 June 2020
- Quickly Creating Pseudobulks on 06 April 2020
- A Guide to Scientific Peer Review on 23 March 2020
- Ten PhD Transition Tips for the Biological Sciences on 23 January 2020
- RNA Velocity Analysis (In Situ) - Tutorial and Tips on 14 January 2020