Compute a correlation matrix of gene expression. For matrices, this function will
correlate the columns; for Seurat objects, this function automatically retrieves
the cluster means of the provided genes using meanClusterExpression
,
and then correlates the cluster means.
correlateExpression(s1, s2, genes, from_sp, to_sp, return_input = FALSE)
s1 | A Seurat object, or a gene x cluster/sample matrix giving mean cluster/sample expression for dataset 1. If a matrix, rownames should be gene symbols. This dataset will form the x-axis of the plot; column names will be pulled from the column names of this object. |
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s2 | A Seurat object, or a gene x cluster/sample matrix giving mean cluster/sample expression for dataset 2. This dataset will form the y-axis of the plot; row names will be pulled from the column names of this object. |
genes | Character vector of genes, in the same species as |
from_sp | Species of |
to_sp | Species of |
method | Character, one of "pearson", "kendall", "spearman", specifying the method to use for the correlations. Default: "spearman" |
# Compute pairwise correlations between clusters in pbmc # NOT RUN # correlateExpression(s1 = pbmc, # s2 = pbmc, # genes = head(rownames(pbmc@raw.data), 100), # from_sp = "hg", # to_sp = "hg")