Description Usage Arguments Value Examples
Constrained ordinary least squares is implemented using a quadratic programming approach, as such:
min_{x>0}||B-Sx||^2
S is a gene by cell-type signature matrix, B is a list containing bulk data, and x is the number of cells from each cell type present in the bulk data. x is then normalized:
\tilde{x} = \frac{x}{∑_{j=1}^n x},
where j is the cell-type index.
1 | solveOLS(S, B)
|
S |
Gene by cell-type matrix consisting of averaged expression values across cells from each cell type |
B |
List containing bulk data values. |
List containing proportion of each cell type present in bulk data set.
1 | prop <- solveOLS(S,B)
|
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