Comments (1)
Hi @mdeea accessors for Milo object elements are all described in the documentation - pay close attention to the Milo-class
docs for details. I'd also recommend familiarising yourself with the documentation for the SingleCellExperiment
package, on which the Milo-class
is built.
There is nothing stopping you from extracting nhood expression data from the object - as detailed in the docs - which is stored in the nhoodExpression
slot - you can then generate plots using whatever packages you are familiar with. All plotting functions in Milo use ggplot, so you can alter the output with additional layers/geometries as you see fit.
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Related Issues (20)
- Error in `scale_color_gradient2()` HOT 5
- Applicability to Cancer Samples HOT 1
- GLMM vignette HOT 3
- Lack of Robustness to Missing Values in Dependent Variable HOT 3
- Cell Condition Relabelling Functionality HOT 3
- Prevention of Neighbourhood Merging of Similar Cell Types into Neighbourhood Groups HOT 1
- Cell type is lost during annotateNhoods HOT 5
- Function Not Found Error HOT 3
- nhood size distribution: some neighbourhoods have over 2000 cells HOT 4
- Progress Bar for GLMM HOT 6
- object 'as.SimpleList' of mode 'function' was not found when running calcNhoodDistance HOT 2
- Multiple comparisons gives identical results by using model.contrasts HOT 12
- Does MiloR take into account that the two compared conditions have different number of cells? HOT 2
- Log10 FC or Log2 FC? HOT 1
- How to use MiloR after subsetting the cell types from total cell types? HOT 4
- Direction of test for logFC calculation HOT 1
- Existence of 2 tuitorials for the "Differential abundance testing with Milo - Mouse gastrulation example" HOT 3
- Import precomputed graph HOT 7
- makeNhoods graph refinement (issue with isolated vertices) HOT 4
- No Significant Neighbourhoods Result is Error HOT 1
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