sslmm: Computing Summary-level Data from Individual-level Data
| sslmm | R Documentation |
Computing Summary-level Data from Individual-level Data
Description
sslmm can be used to compute the correlation-related summary statistics (summary-level data) for lmm function.
Usage
sslmm(X, Y, Z)
Arguments
X |
A design matrix for fixed effects, with rows corresponding to the columns of Y. |
Y |
A features-by-samples matrix of responses (genes-by-cells matrix of gene expressions for scRNA-seq). |
Z |
A design matrix for random effects, with rows corresponding to the columns of Y. |
Value
A list of summary statistics: XX = t(X)%*%X, XY = t(X)%*%t(Y), ZX = t(Z)%*%X, ZY = t(Z)%*%t(Y), ZZ = t(Z)%*%Z, Ynorm = rowSums(Y*Y) and n = nrow(X).
Examples
n <- 1e3
set.seed(2024)
p <- 2
X <- matrix(rnorm(p*n), n, p)
colnames(X) <- paste0("X", 1:ncol(X))
m <- 3
Y <- matrix(rnorm(m*n), m, n)
rownames(Y) <- paste0("Y", 1:nrow(Y))
q <- 4
Z <- gl(q, n/q, labels = letters[1:q])
Z <- model.matrix(~ 0 + Z)
sslmm(X, Y, Z)
