Single-link Clustering http://soj.sysu.edu.cn/show_problem.php?pid=1000&cid=1750 题目说是单链聚类,其实就是最小生成树,输出第k-1大的边; 我用的是kruskal算法: 1 #include <iostream> 2 #include <cstdio> 3 #include <cstring> 4 #include <cmath> 5 #include <algorithm> 6 #include <...
The structural heterogeneity was determined by analyzing the 3D density maps reconstructed from the centroids of clusters in latent space generated by the simple Kmeans clustering algorithm45. The latent space of different methods was also visualized in 2D using UMAP21. The structural heterogeneity was...
A single-cell clustering algorithm should be computationally efficient. As the number of cells sequenced continues to grow, single-cell RNA-sequencing (scRNA-seq) datasets can have more than a million cells, and clustering once on such a large dataset can take days16. Therefore, it is important...
It is rare that a single set of parameters in any clustering algorithm will resolve all putative cell types equally well, especially given the multi-scale organization of most biological systems. Thus, we highlight that an important aspect of chooseR is its ability to identify which clusters are...
A fast parallel algorithm of single link heuristics of hierarchical clustering is presented. Its time processor product is optimal and the parallel time is the square of the logarithm. The algorithm is based on computing a minimum spanning tree which can be done in O(log/sup 2/ n) time usin...
The tumor microenvironment (TME) in pancreatic ductal adenocarcinoma (PDAC) is a complex ecosystem that drives tumor progression; however, in-depth single cell characterization of the PDAC TME and its role in response to therapy is lacking. Here, we perf
& Strimmer, K. An empirical Bayes approach to inferring large-scale gene association networks. Bioinformatics 21, 754–764 (2005). PubMed Google Scholar Opgen-Rhein, R. & Strimmer, K. From correlation to causation networks: a simple approximate learning algorithm and its application to high-...
Week 4: June 3, 2021(Aldo).SCODE: Matsumoto et al. SCODE: an efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation, Bioinformatics, Volume 33, Issue 15, 2017, Pages 2314–2321.Code Week 5: June 17, 2021(Wessel).Ridge estimation of network models ...
This k-nearest neighbors graph was used as input to Phenograph [24], a modularity-based clustering algorithm. The similarity matrix described above was converted to a distance matrix, and used as input to tSNE [25] for visualization. Differential expression analysis was conducted using a binomial...
New modulermDoubletsadded,to remove potential doublets usingDoubletFinderalgorithm (v1.3.1) footprintmodule: support comparison of any two sets of cell clusters (v1.3.0) integrate: add VFACS (Variable Features Across ClusterS) option for the integration module,which reselect highly variable features...