Learning latent embedding of multi-modal single cell data and cross-modality relationship simultaneously
Motivation Single cell multi-omics studies allow researchers to understand cell differentiation
and development mechanisms in a more comprehensive manner. Single cell ATAC …
and development mechanisms in a more comprehensive manner. Single cell ATAC …
Integrating unmatched scrna-seq and scatac-seq data and learning cross-modality relationship simultaneously
It is a challenging task to integrate scRNA-seq and scATAC-seq data obtained from different
batches. Existing methods tend to use a pre-defined gene activity matrix (GAM) to convert …
batches. Existing methods tend to use a pre-defined gene activity matrix (GAM) to convert …
Simultaneous deep generative modelling and clustering of single-cell genomic data
Recent advances in single-cell technologies, including single-cell ATAC-seq (scATAC-seq),
have enabled large-scale profiling of the chromatin accessibility landscape at the single-cell …
have enabled large-scale profiling of the chromatin accessibility landscape at the single-cell …
BABEL enables cross-modality translation between multiomic profiles at single-cell resolution
Simultaneous profiling of multiomic modalities within a single cell is a grand challenge for
single-cell biology. While there have been impressive technical innovations demonstrating …
single-cell biology. While there have been impressive technical innovations demonstrating …
scDART: integrating unmatched scRNA-seq and scATAC-seq data and learning cross-modality relationship simultaneously
It is a challenging task to integrate scRNA-seq and scATAC-seq data obtained from different
batches. Existing methods tend to use a pre-defined gene activity matrix to convert the …
batches. Existing methods tend to use a pre-defined gene activity matrix to convert the …
[HTML][HTML] scTIE: data integration and inference of gene regulation using single-cell temporal multimodal data
Single-cell technologies offer unprecedented opportunities to dissect gene regulatory
mechanisms in context-specific ways. Although there are computational methods for …
mechanisms in context-specific ways. Although there are computational methods for …
RISC: robust integration of single-cell RNA-seq datasets with different extents of cell cluster overlap
Y Liu, T Wang, D Zheng - BioRxiv, 2018 - biorxiv.org
Single cell RNA-seq (scRNA-seq) has remarkably advanced our understanding of cellular
heterogeneity and dynamics in tissue development, diseases, and cancers. Integrated data …
heterogeneity and dynamics in tissue development, diseases, and cancers. Integrated data …
One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data
Integrative analysis of large-scale single-cell RNA sequencing (scRNA-seq) datasets can
aggregate complementary biological information from different datasets. However, most …
aggregate complementary biological information from different datasets. However, most …
[HTML][HTML] CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal
In recent years, there has been a growing interest in profiling multiomic modalities within
individual cells simultaneously. One such example is integrating combined single-cell RNA …
individual cells simultaneously. One such example is integrating combined single-cell RNA …
The Power of Two: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis
Discovering a lower-dimensional embedding of single-cell data can greatly improve
downstream analysis. The embedding should encapsulate both the high-level semantics …
downstream analysis. The embedding should encapsulate both the high-level semantics …