.png){kind=icon}
返回
scClassify: sample size estimation and multiscale classification of cells using single and multiple reference
.png){kind=icon}
OA
AI
DOI：10.15252/msb.20199389.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Automated cell type identification is a key computational challenge in single-cellRNA-sequencing (scRNA-seq) data. To capitalise on the large collection of well-annotated scRNA-seq datasets, we developed scClassify, a multiscale classification framework based on ensemble learning and cell type hierarchies constructed from single or multiple annotated datasets as references. scClassify enables the estimation of sample size required for accurate classification of cell types in a cell type hierarchy and allows joint classification of cells when multiple references are available. We show that scClassify consistently performs better than other supervised cell type classification methods across 114 pairs of reference and testing data, representing a diverse combination of sizes, technologies and levels of complexity, and further demonstrate the unique components of scClassify through simulations and compendia of experimental datasets. Finally, we demonstrate the scalability of scClassify on large single-cell atlases and highlight a novel application of identifying subpopulations of cells from the Tabula Muris data that were unidentified in the original publication. Together, scClassify represents state-of-the-art methodology in automated cell type identification from scRNA-seq data.
Keyword:
cell type hierarchy
cell type identification
multiscale classification
sample size estimation
single-cell
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.7
论文数:
1.6K
被引数:
1.0W
机构
引用论文
Differential distribution improves gene selection stability and has competitive classification performance for patient survival.png)
NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏Single-Cell Transcriptome Profiling of Human Pancreatic Islets in Health and Type 2 Diabetes健康和2型糖尿病中人胰岛的单细胞转录组图谱CELL METABOLISMOAAI
CELL METABOLISMIF30.9
OAAI分享收藏Measurement of the multi-TeV neutrino interaction cross-section with IceCube using Earth absorptionNature
OAAI
NatureIF0
OAAI分享收藏Single-cell transcriptomes identify human islet cell signatures and reveal cell-type specific expression changes in type 2 diabetesGENOME RESEARCHOAAI
GENOME RESEARCHIF5.5
OAAI分享收藏DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest NeighborsDoubletFinder: 使用人工最近邻在单细胞RNA测序数据中进行双峰检测CELL SYSTEMSOAAI
CELL SYSTEMSIF7.7
OAAI分享收藏
查看更多内容