Comments (1)
MikeDMorgan
commented on August 10, 2024
Hi @DarioS Milo is a general tool for differential abundance analysis. There could be many reasons for many tumour cell states being patient specific, and these could be biological or technical reasons. There is no reason why Milo can't be used for analysing cancer data as long as the assumptions are reasonably met. This is not specific to cancer data, but any data set that an analyst wishes to apply Milo to.
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Related Issues (20)
- 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
- Mass cytometry data HOT 1
- MiloR in spatial transcriptomics data HOT 1
- Gene expression testing of only DA neighborhoods within group?? HOT 3
- Can you implement a complete miloR in python ? HOT 1
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