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scNMT-seq: LIGER

Banff International Research Station for Mathematical Innovation and Discovery

Dr. Joshua Welch, is Assistant Professor of Computational Medicine and Bioinformatics in Department of Computational Medicine and Bioinformatics, University of Michigan (https://welch-lab.github.io/). Most recently, his lab has focused on developing open-source software for the processing, analysis, and modeling of single-cell sequencing data. Key contributions in this area include SingleSplice, the first computational method for single-cell splicing analysis; SLICER, an algorithm for inferring developmental trajectories; and LIGER, a general approach for integrating single-cell transcriptomic, epigenomic and spatial transcriptomic data. We used our previously published algorithm LIGER for this analysis. The advantage of our method is that it can integrate different single-cell modalities measured on different single cells. The corresponding disadvantage is that we do not leverage the known correspondence information from true multi-omic measurements. We tried multiple data processing strategies for the scNMT accessibility data. We observed limited alignment with all processing strategies, but the more differentiated cell types showed more correspondence. We also analyzed a different single-cell multi-omic dataset, SNARE-seq (RNA+ATAC) from mouse frontal cortex. LIGER was able to effectively integrate this dataset, finding corresponding cell types between RNA and ATAC data without using the known cell correspondences. We are further investigating the possible biological and technical explanations for these differences. Code is available https://github.com/jw156605/scNMT

Mathematics; Statistics; Biology and other natural sciences

video/mp4

Author affiliation: University of Michigan

2020-12-15

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/76803

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/4.0/