table(ann_row1$Sig) ## ## Down Up ## 1296 2832 根据下调基因的个数,设置 gaps_row=1296,如下: ###拆分多个模块 pheatmap(dat[rownames(ann_row1),], cluster_rows = FALSE, show_rownames=FALSE, show_colnames = FALSE, scale="none", cluster_cols = FALSE, fontsize_row = 10, fontsize_...
Heatmap(mat, name = "mat", row_split = split, row_title = "{map[ x[1] ]}|{map[ x[2] ]}") Heatmap(mat, name = "mat", row_split = split, row_title = "%s|%s", row_title_rot = 0) Heatmap(mat, name = "mat", row_split = 2, row_title = "cluster_%s") Heatmap(...
column_ha<-HeatmapAnnotation(bar1=anno_barplot(runif(24)))row_ha<-rowAnnotation(bar2=expr$chr)Heatmap(mat,show_row_names=F,#cluster_rows=F,top_annotation=ha,bottom_annotation=column_ha,#对应的注释 right_annotation=row_ha) 其他常用调整的函数 #cluster_rows/columns :是否进行聚类 #show_column...
pheatmap::pheatmap(Cor,cluster_row=FALSE,cluster_col=FALSE,border=FALSE) border=FALSE 由于是随机生成的数据,就不显示聚类的效果(只需要把cluster_row和cluster_col删掉即可),总体来说用pheatmap绘制热图会相对简单一点,但是毫不逊色于其他包绘制的热图。此外,如果想对于行或列来显示一些注释信息(annotation),比如...
annotation_row =NA, # 行分组 annotation_colors = ann_colors, # 指定样本分组颜色, list格式 color = colorRampPalette(c("#0000FF", "#FFFCC8", "#FF0000"))(100), # 热图色卡颜色 border_color = NA, # cell有无边框,或指定颜色 cluster_rows = TRUE, # 显示行聚类 ...
ha = rowannotation( foo = anno_empty( border = false, # 计算空白注释的宽度 width = max_text_width(unlist(group)) + unit(4, "mm")) ) 3)通过向量拆分对应的行和列 heatmap(mat, name = "mat", #cluster_rows ...
seaborn.clustermap(data, pivot_kws=None, method='average', metric='euclidean', z_score=None, standard_scale=None, figsize=None, cbar_kws=None, row_cluster=True, col_cluster=True, row_linkage=None, col_linkage=None, row_colors=None, col_colors=None, mask=None, **kwargs) 除此之外,clus...
4. cluster_rows = TRUE,cluster_cols = TRUE 对于行列的数据是否做聚类,TRUE做聚类,反之不做。 5. cutree_rows = NA, cutree_cols =NA 此参数是将热图的行列分成几块,并相互独立开。 6. annotation_row = NA,annotation_col = NA 此参数是指对于行列的注释名称是否设置,当然这里设置名称需要以因子的形式...
(16, -1),4), matrix(rnorm(32, 1), 8)), rbind(matrix(rnorm(24, 1), 4), matrix(rnorm(48, -1), 8))) mat <- mat[sample(nrow(mat), nrow(mat)), sample(ncol(mat), ncol(mat))] rownames(mat) <- paste0("R", 1:12) colnames(mat) <- paste0("C", 1:10) # 常规矩阵...
ht <- Heatmap(mat,cluster_rows =F,#不按行聚类show_column_names =F,#不展示列名heatmap_legend_param =list(title ="Log2 relative abundance"),#设置热图图例名称col =c("#FFFFFF","#D32F2F"))#设置热图颜色 05 添加行...