solveSVR: Solve overdetermined system of equations, Sx=B, for x, using...
In PelzKo/dwls: Dampened Weighted Least Square for Deconvolution of Bulk mRNA Data
Description
Usage
Arguments
Value
Examples
Description
Solve overdetermined system of equations, Sx=B, for x, using nu-support vector regression with a linear kernel.
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.
Usage
1
solveSVR(S, B)
Arguments
S
Gene by cell-type matrix consisting of averaged expression values across cells from each cell type
B
List containing bulk data values.
Value
List containing proportion of each cell type present in bulk data set.
Examples
1
prop <- solveSVR(S,B)
PelzKo/dwls documentation built on Dec. 18, 2021, 6:46 a.m.
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Description Usage Arguments Value Examples
Description
Solve overdetermined system of equations, Sx=B, for x, using nu-support vector regression with a linear kernel. 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.
Usage
1 | solveSVR(S, B)
|
Arguments
S |
Gene by cell-type matrix consisting of averaged expression values across cells from each cell type |
B |
List containing bulk data values. |
Value
List containing proportion of each cell type present in bulk data set.
Examples
1 | prop <- solveSVR(S,B)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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