UNSUPERVISED SINGLE-LINK HIERARCHICAL CLUSTERING 来自 ResearchGate 喜欢 0 阅读量: 16 作者: DA Lupa 摘要: Summary: There are many clustering techniques presented in the literature. The particularity of single-link clustering is that it rather discovers the clusters as chains. We aim to identify ...
First, the single-link clustering is formally presented. Then, the concepts un-derlying the generic hierarchical classification technique are given. Next, analysis domains modeling a given facet of a dataset are described. A new language devoted to generate analysis domains is presented. Fur-ther,...
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 ...
It then computes a consensus matrix by summarizing the three individual clustering results. Finally, the consensus matrix is clustered using hierarchical clustering to produce final clustering results18. However, these traditional single-cell clustering methods are not ready to take the advantage of ...
6i) but were assigned to basal or goblet cells during clustering. Additionally, basal-goblet cells from the SfSRC model are located between basal and goblet cells in the UMAP embedding (Supplementary Fig. 6j), expressed both basal and goblet marker genes, and had a similar transcriptional ...
Thus, we propose Markov hierarchical clustering algorithm (MarkovHC), which reconstructs multi-scale pseudo-energy landscape by exploiting underlying metastability structure in an exponentially perturbed Markov chain . A Markov process describes the random walk of a hypothetically traveling cell in the ...
use scipy hierarchical linkage rather than fastcluster Feb 28, 2025 View all files README MIT license Consensus NMF (cNMF) cNMF is a pipeline for inferring gene expression programs from scRNA-Seq. It takes a count matrix (N cells X G genes) as input and produces a (K x G) matrix of ...
We evaluated how well clustering could recover cell types (using only cell types with at least 10 cells) by clustering each dataset based on the integrated reduced dimensional space using hierarchical graph-based clustering56 into between 2 and 50 clusters. For each clustering solution, we calculate...
We present scABC, an R package for the unsupervised clustering of single-cell epigenetic data, to classify scATAC-seq data and discover regions of open chromatin specific to cell identity.Similar content being viewed by others RA3 is a reference-guided approach for epigenetic characterization of ...
Based on these inferred proportions, a comprehensive hierarchical clustering analysis was conducted to uncover inherent patterns and relationships among the samples. Furthermore, survival analysis was performed using the Survival package (version 3.4-0). Specifically, relevant clinical subtypes were selected...