Update README.md (83b0b112) · Commits · github_fork / DAseq2

README.md

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		@@ -7,9 +7,9 @@ This repository contains codes for running DA-seq in R.


		## Dependencies
		Required packages: RANN, tclust, ggplot2, cowplot, RColorBrewer, scales, Seurat (V2.3)
		Required packages: RANN, tclust, ggplot2, cowplot, RColorBrewer, scales, reticulate

		Suggested package: diffusionMap
		Suggested package: Seurat


		## Usage
		@@ -17,7 +17,7 @@ DA-seq can be used as follows:

		Let X be a N-by-p matrix of the PCA embeddings of merged scRNA-seq datasets A (A1 and A2) and B (B1 and B2); X.label be a vector of N specifying the original of each cell ('A1', 'A2', 'B1', or 'B2'); X.2d be the 2D embedding of the cells.

		For marker detection of each DA region, let SeuratObj be a Seurat V2.3.0 ([tutorial](https://satijalab.org/seurat/v2.4/pbmc3k_tutorial.html)) object containing the merged datasets (N cells), after proper preprocessing steps (normalization, scaling, etc.).
		For marker detection of each DA region, let X.data be the normalized expression matrix containing the merged datasets (N cells).

		~~~~
		X.da.cells <- getDAcells(
		@@ -39,11 +39,10 @@ X.da.regions <- getDAregion(
		plot.embedding = X.2d
		)

		X.da.markers <- findMarkersForDAregion(
		X.da.markers <- STGmarkerFinder(
		X = X.data,
		cell.idx = X.da.cells$da.cell.idx,
		da.region.label = X.da.regions$cluster.res,
		obj = SeuratObj,
		only.pos = T, min.pct = 0.1, min.diff.pct = 0.09
		da.region.label = X.da.regions$cluster.res
		)
		~~~~