Here we extend a previous method, significance of hierarchical clustering, to propose a model-based hypothesis testing approach that incorporates significance analysis into the clustering algorithm and permits statistical evaluation of clusters as distinct cell populations. We also adapt this approach to ...
E Hierarchical clustering of the CD8 + T cell subsets based on dysfunction and cytotoxicity scores. F Composition of the CD8 + T cell subset (excluding the two non-T cell clusters and the single-patient cluster). Full size image Because our initial T/NK clustering did not identify...
Single-cell and single-nucleus RNA-sequencing (sxRNA-seq) is increasingly being used to characterise the transcriptomic state of cell types at homeostasis, during development and in disease. However, this is a challenging task, as biological effects can
a Hierarchical clustering of the correlation between each transformed subpopulation and a database of cell type-specific expression profiles with high variability across the data set. We find three cell type clusters referred to as Neural/ESC, Immune, and Mesenchymal/MSC which divide the tumor cell...
A key task in single-cell RNA-seq (scRNA-seq) data analysis is to accurately detect the number of cell types in the sample, which can be critical for downstream analyses such as cell type identification. Various scRNA-seq data clustering algorithms have
Agglomerative hierarchical clustering is a “bottom up” approach: each observation starts in its own cluster, and pairs of clusters are iteratively merged based on inter-cluster distances. Ward’s method [16] was used as linkage criterion. We included in the comparison four variants of hierarchica...
Enhlink can easily process data generated by the Cell Ranger pipelines, or any sparse matrices saved in the appropriate format. Enhlink infers distal and context-specific enhancer–promoter linkages Melissa - [R] - Melissa (MEthyLation Inference for Single cell Analysis), a Bayesian hierarchical ...
Single-cell omics is transforming our understanding of cell biology and disease, yet the systems-level analysis and interpretation of single-cell data faces many challenges. In this Perspective, we describe the impact that fundamental concepts from stati
"SCALE: modeling allele-specific gene expression by single-cell RNA sequencing." Genome Biology 18.1 (2017): 74. link Common questions How to adjust for possible heterogeneity within the cell population? SCALE needs to be applied to a homogeneous cell population, where the same bursting kinetics ...
Integration of single-cell RNA sequencing data between different samples has been a major challenge for analyzing cell populations. However, strategies to integrate differential expression analysis of single-cell data remain underinvestigated. Here, we b