如果后面的 learn_graph(cds2, use_partition = F)的use_partition为F,则不用partition来做不同pseudotime推测,没有没有必要设置partition;cds2@clusters$UMAP$partitions<-factor(x=rep(1,length(rownames(colData(cds2))),levels=1)names(cds2@clusters$UMAP$partitions)<-rownames(colData...
monocle.object = learn_graph(monocle.object, learn_graph_control=list(ncenter=500), use_partition = FALSE) plot_cells(monocle.object, color_cells_by="partition", group_cells_by="partition") a helper function to identify the root principal points: make cluster 2 the root get_earliest_principa...
Monocle3 ### Load data from Seurat formatp_load(monocle3,Seurat,tidyverse,patchwork)sce<-readRDS("sce.rds")data<-GetAssayData(sce,assay="RNA",layer="counts")cell_metadata<-sce@meta.data gene_annotation<-data.frame(gene_short_name=rownames(data))rownames(gene_annotation)<-rownames(data)cd...
在本指南[1]中,会展示如何利用Monocle 3软件和单细胞ATAC-seq数据来构建细胞发展轨迹。 为了方便在Seurat(Signac所使用的)和CellDataSet(Monocle 3所使用的)这两种数据格式之间进行转换,将使用GitHub上的SeuratWrappers包里的一个转换工具。 数据加载 将采用一个单细胞ATAC-seq数据集,该数据集包含了由Satpathy和Granja...
basic partition_cells working Jan 26, 2019 tests prepare for version 0.2.2.0 and fix typos Jun 10, 2020 vignettes slim vignette Sep 13, 2019 .Rbuildignore initial commit Jan 25, 2019 .gitignore update gitignore Jul 30, 2019 .travis.yml ...
I already have a set of genes that vary in some interesting way across the clusters. I would like to use find_gene_modules() to group them into using Louvain community analysis. I am given the error: Error in leidenbase::leiden_find_partition(graph_result[["g"]], partition_type = part...
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cds<-cluster_cells(cds)#聚类之后,每一个cluster会自成一个”拟时序轨迹“plot_cells(cds,color_cells_by="partition") image.png 这个图里黑色的线就是拟时序走向的背景,带有数字的灰色圈圈代表的是拟时序分支的leaf,他们被黑色的branch_points所隔开 ...
(cds, use_partition = F) get_earliest_principal_node <- function(cds, ct_bin=c("13", "vRG-oRG-PgS")){ cell_ids <- which(colData(cds)[, "gw"] == ct_bin[1] & colData(cds)[, "cluster.ids.wnn"] == ct_bin[2] ) closest_vertex <- cds@principal_graph_aux[["UMAP"]]$pr...