[HTML][HTML] Statistics or biology: the zero-inflation controversy about scRNA-seq data
Researchers view vast zeros in single-cell RNA-seq data differently: some regard zeros as
biological signals representing no or low gene expression, while others regard zeros as …
biological signals representing no or low gene expression, while others regard zeros as …
Enhancing scientific discoveries in molecular biology with deep generative models
Generative models provide a well‐established statistical framework for evaluating
uncertainty and deriving conclusions from large data sets especially in the presence of …
uncertainty and deriving conclusions from large data sets especially in the presence of …
DestVI identifies continuums of cell types in spatial transcriptomics data
Most spatial transcriptomics technologies are limited by their resolution, with spot sizes
larger than that of a single cell. Although joint analysis with single-cell RNA sequencing can …
larger than that of a single cell. Although joint analysis with single-cell RNA sequencing can …
Bacterial droplet-based single-cell RNA-seq reveals antibiotic-associated heterogeneous cellular states
P Ma, HM Amemiya, LL He, SJ Gandhi, R Nicol… - Cell, 2023 - cell.com
We introduce BacDrop, a highly scalable technology for bacterial single-cell RNA
sequencing that has overcome many challenges hindering the development of scRNA-seq …
sequencing that has overcome many challenges hindering the development of scRNA-seq …
STARsolo: accurate, fast and versatile mapping/quantification of single-cell and single-nucleus RNA-seq data
We present STARsolo, a comprehensive turnkey solution for quantifying gene expression in
single-cell/nucleus RNA-seq data, built into RNA-seq aligner STAR. Using simulated data …
single-cell/nucleus RNA-seq data, built into RNA-seq aligner STAR. Using simulated data …
Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models
As the number of single‐cell transcriptomics datasets grows, the natural next step is to
integrate the accumulating data to achieve a common ontology of cell types and states …
integrate the accumulating data to achieve a common ontology of cell types and states …
[HTML][HTML] Clustering of single-cell multi-omics data with a multimodal deep learning method
Single-cell multimodal sequencing technologies are developed to simultaneously profile
different modalities of data in the same cell. It provides a unique opportunity to jointly …
different modalities of data in the same cell. It provides a unique opportunity to jointly …
[HTML][HTML] Robust single-cell matching and multimodal analysis using shared and distinct features
The ability to align individual cellular information from multiple experimental sources is
fundamental for a systems-level understanding of biological processes. However, currently …
fundamental for a systems-level understanding of biological processes. However, currently …
[HTML][HTML] Mapping human adult hippocampal neurogenesis with single-cell transcriptomics: reconciling controversy or fueling the debate?
The notion of exploiting the regenerative potential of the human brain in physiological aging
or neurological diseases represents a particularly attractive alternative to conventional …
or neurological diseases represents a particularly attractive alternative to conventional …
[HTML][HTML] Hotspot identifies informative gene modules across modalities of single-cell genomics
D DeTomaso, N Yosef - Cell systems, 2021 - cell.com
Two fundamental aims that emerge when analyzing single-cell RNA-seq data are identifying
which genes vary in an informative manner and determining how these genes organize into …
which genes vary in an informative manner and determining how these genes organize into …