About scMiko

scMiko is an R package developed for single-cell RNA-seq analysis. It was designed using the Seurat framework, and offers existing and novel single-cell analytic work flows.

Refer to our getting started with scMiko article for installation instructions.

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

Details can be found in our recent work: Mikolajewicz, et al., BioRxiv

About scPipeline

The scPipeline analysis pipeline is a modular collection of R markdown scripts that generate flexdashboard reports for scRNAseq analyses, and is dependent on the scMiko package. The modular framework permits flexible usage, without necessitating complete reliance on a single analysis platform. Additionally, the self-contained reports that are generated by each module provide a comprehensive analysis summary and log of analytic parameters and scripts, thereby ensuring reproducible and shareable analysis workflows.

Refer to our getting started with scPipeline article for installation and configuration instructions, and to our scPipeline overview article for detailed module overviews and examples of analyses.

Currently the following analysis modules are available:

scMiko and scPipeline are developed and maintained by the Moffat lab.

Authors

Acknowledgments