While the algorithms differ considerably in terms of their computational efficiency, even the least efficient algorithm may sometimes be useful for small data sets.doi:10.1016/S0169-7161(82)02015-XRohlfF. JamesHandbook of StatisticsF.J. Rohlf, Single link clustering algorithms, RC 8569 (#37332...
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 initial cell annotations can be obtained either from cell-type assignments if available or by running a clustering algorithm. In all experiments in the paper, we run SATURN with initial cell-type assignments within the individual species but never matched across species. In addition to count ...
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 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...
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...
Additionally, Slingshot optionally allows the user to provide further supervision in the inference of the lineages by selecting clusters known to represent terminal cell states, imposing a local constraint on the MST algorithm. The constrained MST is obtained by first constructing the MST on all non...
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 statistical mechanics, notably entropy, stochastic proces...
Cells were phenotyped after segmentation using inForm’s trainable algorithm based on the R glmnet package82. Four algorithms were created to classify cells as CD8 + or ‘other’, CK19 + or ‘other’, TIGIT + or ‘other’, and PD1 + or ‘other’. Phenotypes were ...
Finally, similar to the graph-based algorithms implemented in the latest version of the CellRanger pipeline [9], we tested the graph-based Louvain clustering algorithm [10] with Euclidean distance over log2(x+1) transformed data. Details on individual methods are as follows. Seurat, Seurat_SNN...