rowlmMatVec: Fit a linear model with rows of mat and vec, possibly adding...
In nickytong/GenAnalysis: Genomic Analysis

Fit a linear model with rows of mat and vec, possibly adding an adjustment variable (adj)

1 2	rowlmMatVec(mat, vec, adj, matIsX = TRUE, collapse = TRUE, parallel = FALSE, core = 12)

`mat`	a matrix
`vec`	a vector, length of ncol(mat)
`adj`	a vector for adjustment variable
`matIsX`	by default, mat rows are continuous (i.e. expr) and vec is categorical response; but for CN data where mat is categorical and the response might be continuous or not. in this case, we want lm(y~x) treats rows of mat as y and vec as x. This can be achieved by specifying matIsX=FALSE that makes rows of mat as the response variable
`collapse`	when vec is non-numeric which will be treated as factor, there are multiple coefs for different levels. We thus need to summarize them into a scaler (by mean). if collapse=FALSE, all coefs will be returned.
`core`	number of cores to use for parallel
`adj`	this can be a vector or a data frame that contains multiple variables to be adjusted. It needs to have nrow=length(vec).—-> now demands a 1 column for easy handling