Releases: NMikolajewicz/scMiko
v1.0.1 scMiko
New features offered in scMiko include:
Differential expression analysis using the co-dependency index (CDI)
CDI identified binary DEGs
binary DEGs are highly-specific
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Specificity-based cluster resolution selection criterion
method to identify optimal clustering configurations
out-performs resampling-based approaches
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Cell-type annotation using Miko Scoring pipeline
unbiased scoring of variably-sized gene sets
hypothesis-testing frame work that accepts or rejects of candidate annotations
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Gene program discovery using scale-free shared-nearest neighbor network (SSN) analysis
gene program discovery algorithm to identify and functionally annotate gene programs in an unsupervised manner
outperforms ICA and NMF methods in terms of GO term recovery and STRING PPI enrichment
Vignette
scMiko v1.0.0
New features offered in scMiko include:
Differential expression analysis using the co-dependency index (CDI)
CDI identified binary DEGs
binary DEGs are highly-specific
Vignette
Specificity-based cluster resolution selection criterion
method to identify optimal clustering configurations
out-performs resampling-based approaches
Vignette
Cell-type annotation using Miko Scoring pipeline
unbiased scoring of variably-sized gene sets
hypothesis-testing frame work that accepts or rejects of candidate annotations
Vignette
Gene program discovery using scale-free shared-nearest neighbor network (SSN) analysis
gene program discovery algorithm to identify and functionally annotate gene programs in an unsupervised manner
outperforms ICA and NMF methods in terms of GO term recovery and STRING PPI enrichment
Vignette