0000000000037347
AUTHOR
Huidong Chen
showing 6 related works from this author
MOESM3 of Assessment of computational methods for the analysis of single-cell ATAC-seq data
2019
Additional file 3: Review history.
Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM
2019
Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell techno…
STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of omics data
2018
AbstractSingle-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.
Assessment of computational methods for the analysis of single-cell ATAC-seq data
2019
Abstract Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans), lead to inherent data sparsity (1–10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (10–45% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level. Results We present a benchmarking framework that …
MOESM2 of Assessment of computational methods for the analysis of single-cell ATAC-seq data
2019
Additional file 2: Code to reproduce the analyses.
MOESM1 of Assessment of computational methods for the analysis of single-cell ATAC-seq data
2019
Additional file 1: Figures S1–S24, Tables S1-S21, Supplementary Notes, and Supplementary figure legends