Single-cell

SIMBA: SIngle-cell eMBedding Along with features
SIMBA is a method to embed cells along with their defining features such as gene expression, transcription factor binding sequences and chromatin accessibility peaks into the same latent space. The joint embedding of cells and features allows SIMBA to perform various types of single cell tasks, including but not limited to single-modal analysis (e.g. scRNA-seq and scATAC-seq analysis), multimodal analysis, batch correction, and multi-omic integration.
Huidong Chen, Jayoung Ryu, Michael E Vinyard, Adam Lerer, Luca Pinello
SIMBA: SIngle-cell eMBedding Along with features
singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality
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David F. Stein, Huidong Chen, Michael E. Vinyard, Qian Qin, Rebecca D. Combs, Qian Zhang, Luca Pinello
singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality
Current progress and potential opportunities to infer single-cell developmental trajectory and cell fate
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Lingfei Wang, Qian Zhang, Qian Qin, Nikolaos Trasanidis, Michael Vinyard, Huidong Chen, Luca Pinello
Current progress and potential opportunities to infer single-cell developmental trajectory and cell fate
Aging-associated alterations in mammary epithelia and stroma revealed by single-cell RNA sequencing
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Carman Man-Chung Li, Hana Shapiro, Christina Tsiobikas, Laura M. Selfors, Huidong Chen, Jennifer Rosenbluth, Luca Pinello, Kaitlin Moore, Kushali P. Gupta, G. Kenneth Gray, Yaara Oren, Michael J. Steinbaugh, Jennifer L. Guerriero, Aviv Regev, Joan S. Brugge
Aging-associated alterations in mammary epithelia and stroma revealed by single-cell RNA sequencing
Parallel single-cell RNA-seq and genetic recording reveals lineage decisions in developing embryoid bodies
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Ik Soo Kim, Jingyi Wu, Gilbert J. Rahme, Sofia Battaglia, Atray Dixit, Elizabeth Gaskell, Huidong Chen, Luca Pinello, Bradley E. Bernstein
Parallel single-cell RNA-seq and genetic recording reveals lineage decisions in developing embryoid bodies
Assessment of computational methods for the analysis of single-cell ATAC-seq data
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Huidong Chen, Caleb Lareau, Tommaso Andreani, Michael E. Vinyard, Sara P. Garcia, Kendell Clement, Miguel A. Andrade-Navarro, Jason D. Buenrostro, Luca Pinello
Assessment of computational methods for the analysis of single-cell ATAC-seq data
Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
An interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.
Huidong Chen, Luca Albergante, Jonathan Y. Hsu, Caleb A. Lareau, Giosuè Lo Bosco, Jihong Guan, Shuigeng Zhou, Alexander N. Gorban, Daniel E. Bauer, Martin J. Aryee, David M. Langenau, Andrei Zinovyev, Jason D. Buenrostro, Guo-Cheng Yuan, Luca Pinello
Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing
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Xiaoping Han, Haide Chen, Daosheng Huang, Huidong Chen, Lijiang Fei, Chen Cheng, He Huang, Guo-Cheng Yuan, Guoji Guo
Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing
Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing
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Qin Tang, Sowmya Iyer, Riadh Lobbardi, John C. Moore, Huidong Chen, Caleb Lareaun, Christine Hebert, McKenzie L. Shaw, Cyril Neftel, Mario L. Suva, Craig J. Ceol, Andre Bernards, Martin Aryee, Luca Pinello, Iain A. Drummond, David M. Langenau
Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing
GiniClust: detecting rare cell types from single-cell gene expression data with Gini index
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Lan Jiang, Huidong Chen, Luca Pinello, Guo-Cheng Yuan
GiniClust: detecting rare cell types from single-cell gene expression data with Gini index