Description Usage Arguments Details Value Examples
Tests whether a given set of genes are significantly shifted to the left or right of the Michaelis-Menten curve.
1 | M3DropTestShift(expr_mat, genes_to_test, name="", background=rownames(expr_mat), suppress.plot=FALSE)
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expr_mat |
a numeric matrix of normalized (not log-transformed) expression values, columns = samples, rows = genes. |
genes_to_test |
vector of gene names to test. |
name |
string used to title the plot. |
background |
vector of gene names to test against. (default = all genes) |
suppress.plot |
logical, whether to the fitted Michaelis-Menten curve and highlight the given set of genes to test. |
Fits a Michaelis-Menten function to the dropout-rate of the provided data, then tests whether a given set of genes (eg. pseudogenes) is significantly shifted left or right of the curve. Horizontal residuals are calculated as :
log_10(S) - log_10( (K * (1 - P)) / P )
. Uses a Wilcox rank-sum test/Mann-Whitney U test to compare the residuals for the given genes to the residuals for all genes.
A one row dataframe with columns: sample (median horizontal residual of genes in the test set), pop (median horizontal residual of genes in the background set), p.value
1 2 3 | library(M3DExampleData)
gene_set <- c("Dppa2","Tdgf1","Rnf130","Tet1","Uhrf1","Pttg1","Zfp600","Stat1")
shift_output <- M3DropTestShift(Mmus_example_list$data, gene_set)
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