featurescatter函数用法 一、 featurescatter函数是单细胞数据分析中常用的可视化工具,尤其在基因表达相关性分析中表现突出。它的核心功能是通过散点图形式,直观展示两个特征(如基因)在细胞群体中的共表达模式。当我们需要验证某两个基因是否存在协同调控关系,或者比较不同样本间的表达差异时,这个函数就像显微镜般帮助我们...
使用FeatureScatter计算单核细胞的S100A8和S100A9相关性,结果显示相关系数为0.87两个基因在表达水平上存在较强的正相关性,说明S100A8和S100A9可能在单核细胞的生物学功能中共同起作用,它们可能参与了相似的细胞过程或信号通路。 小结 FeatureScatter提供了一个直观的方式来观察两个基因的表达水平是否存在某种关系,比如正...
FeatureScatter(pbmc, feature1 = "TMSB4X", feature2 = "B2M", cols=c(1:9), #每个类的颜色 span=0.1, #越大越平滑,也越失去细节 jitter=F) 2.源码解析 (1) FeatureScatter() 位置: # $ find . | grep "R$" | xargs grep -n "FeatureScatter" --color=auto # seurat-4.1.0/R/visualizatio...
使用FeatureScatter计算单核细胞的S100A8和S100A9相关性,结果显示相关系数为0.87两个基因在表达水平上存在较强的正相关性,说明S100A8和S100A9可能在单核细胞的生物学功能中共同起作用,它们可能参与了相似的细胞过程或信号通路。 小结 FeatureScatter提供了一个直观的方式来观察两个基因的表达水平是否存在某种关系,比如正...
minecraft:scatter_feature scatters a feature throughout a chunk. The x, y, and z fields are per-coordinate parameters. Coordinates represent an offset from the input position instead of an absolute position, and may be a single value, random distribution, or Molang expression that r...
geode_feature growing_plant_feature multiface_feature nether_cave_carver_feature ore_feature partially_exposed_blob scatter_feature search_feature sequence_feature single_block_feature snap_to_surface_feature structure_template_feature surface_relative_threshold tree_feature underwater_cave_carver_...
geode_feature growing_plant_feature multiface_feature nether_cave_carver_feature ore_feature partially_exposed_blob scatter_feature search_feature sequence_feature single_block_feature snap_to_surface_feature structure_template_feature surface_relative_threshold tree_feature underwater_cave_car...
object "minecraft:scatter_feature" : opt { object "description" { string "identifier" // The name of this feature in the form 'namespace_name:feature_name'. 'feature_name' must match the filename. } feature_reference "places_feature" // Named reference of feature to be plac...
shap.plots.scatter(shap_values[:, "Relationship"], color=random_number) If you want to label the color bar, useshap.Explanation. random_col = shap.Explanation(values=random_number, base_values=None, data=random_number, feature_names='random') ...
What problem does this feature solve? 1 What does the proposed API look like? 1fangsmile self-assigned this Apr 28, 2024 fangsmile changed the title [Feature] PivotTable support scatter chart [Feature] PivotChart support scatter chart Apr 28, 2024 fangsmile added a commit that referenced ...