We provide a series of vignettes to help users to get started with scPlant.
Pre-processing
We recommend CellFunTopic package to perform data pre-processing (quality control, normalization, dimension reduction, clustering, differential expression analysis, etc.) for convenience.
Cross-species integration
scPlant allows cross-species integration of single-cell data in matched organs/tissues using one-by-one orthologous genes as anchors.
Functional annotation
scPlant provides methods for Gene Set Enrichment Analysis (GSEA) in model plants. We recommend CellFunTopic package to visualize the GSEA result and perform topic modelling, revealing cellular programs shared across cell types or exclusive to a particular cell type.
Gene regulatory network construction
scPlant pipeline have incorporated the widely used single-cell GRN analysis tool SCENIC (Aibar et al., 2017), and prepared required cisTarget databases to apply SCENIC in plants such as Arabidopsis thaliana, Oryza sativa, Zea mays. A recently published plant specific GRN inference tool MINI-EX (Ferrari et al., 2022) has also been incorporated into the scPlant pipeline.
Paired motif enrichment
scPlant pipeline have adapted the Paired Motif Enrichment Tool (PMET) (Rich-Griffin et al., 2020) to predict pairs of TF binding motifs within the promoter regions of cell-type specific marker genes.
Automatic cell-type annotation
scPlant have implemented several different solutions for automatic cell-type annotation that are based on popular tools, including SingleR, Garnett, scCATCH, Celaref and CellAssign.
Estimating the cell type composition of bulk samples
scPlant helps estimating the cell type composition of bulk samples using a single cell reference. Cell-type deconvolution was implemented based on the CIBERSORT algorithm.
Pseudotime trajectory inference
scPlant offers convenient implementation of pseudotime trajectory inference by incorporating 4 public tools: Monolce2, Monolce3, Slingshot and CytoTRACE.
Explore in Built-in Shiny APP
The gene regulatory network, differentially expressed genes, and functional annotation can be explored interactively in the built-in Shiny web application.