data_SMNN: A list of two expression matrices for two batches. The first...

In yycunc/SMNN: SMNN: Batch Effect Correction for Single-cell RNA-seq data with Supervised Mutual Nearest Neighbor Detection

Description

A list of two expression matrices for two batches. The first batch contains 400 cells of three cell types, fibroblasts, macrophages and endothelial cells. And the second batches has 500 cells of the same three cell types.

Usage

data("data_SMNN")

Format

An object of class list of length 2.

Examples

# Load the example data data_SMNN
data("data_SMNN")

# Provide the marker genes for cluster matching
markers <- c("Col1a1", "Pdgfra", "Ptprc", "Pecam1")

# Specify the cluster labels for each marker gene
cluster.info <- c(1, 1, 2, 3)

# Call function unifiedClusterLabelling to identify the corresponding clusters between two batches
matched_clusters <- unifiedClusterLabelling(data_SMNN$batch1.mat, data_SMNN$batch2.mat, features.use = markers, cluster.labels = cluster.info, min.perc = 0.3)

# Set python version to be compatible with SMNNcorrect implementation
library(reticulate)
use_python("/nas/longleaf/apps/python/3.5.1/bin/python3")

# Perform batch effect correction using SMNNcorrect
corrected.results <- SMNNcorrect(batches = list(data_SMNN$batch1.mat, data_SMNN$batch2.mat), batch.cluster.labels = matched_clusters, matched.clusters = c(1,2,3), k=20, sigma=1, cos.norm.in=TRUE, cos.norm.out=TRUE)

yycunc/SMNN documentation built on Dec. 29, 2021, 12:17 p.m.