Zeyuan Johnson Chen
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View article: Epigenetic patient stratification reveals a sub-endotype of type 2 asthma with altered B-cell response
Epigenetic patient stratification reveals a sub-endotype of type 2 asthma with altered B-cell response Open
Despite biomarker-guided treatment strategies, clinical outcomes among patients with type 2 (T2)-high asthma remain heterogeneous, with some patients responding poorly to T2-targeted biologic therapies. We developed a contrastive machine l…
View article: Integrated ambient modeling and genetic demultiplexing of single-cell RNA+ATAC multiome experiments with Ambimux
Integrated ambient modeling and genetic demultiplexing of single-cell RNA+ATAC multiome experiments with Ambimux Open
Single cell technologies have advanced at a rapid pace, providing assays for various molecular phenotypes. Droplet-based single cell technologies, particularly those based on nuclei isolation, such as simultaneous RNA+ATAC single-cell mult…
View article: Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue
Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue Open
Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromat…
View article: A unified model for cell-type resolution genomics from heterogeneous omics data
A unified model for cell-type resolution genomics from heterogeneous omics data Open
The vast majority of population-scale genomic datasets collected to date consist of “bulk” samples obtained from heterogeneous tissues, reflecting mixtures of different cell types. In order to facilitate discovery at the cell-type level, t…
View article: CONFINED: distinguishing biological from technical sources of variation by leveraging multiple methylation datasets
CONFINED: distinguishing biological from technical sources of variation by leveraging multiple methylation datasets Open
Methylation datasets are affected by innumerable sources of variability, both biological (cell-type composition, genetics) and technical (batch effects). Here, we propose a reference-free method based on sparse canonical correlation analys…
View article: Distinguishing biological from technical sources of variation by leveraging multiple methylation datasets
Distinguishing biological from technical sources of variation by leveraging multiple methylation datasets Open
DNA methylation remains one of the most widely studied epigenetic markers. One of the major challenges in population studies of methylation is the presence of global methylation effects that may mask local signals. Such global effects may …