deconvolute_NNLS: Non-negative Least Squares (NNLS) deconvolution
In Goralsth/FloodLight:
deconvolute_NNLS R Documentation
Non-negative Least Squares (NNLS) deconvolution
Description
Use NNLS to deconvolute a matrix of spots consisting of unknown cell types against a reference of known cell type marker gene signatures.
Usage
deconvolute_NNLS(cluster_markers, spots, L1 = 0.01)
Arguments
cluster_markers
matrix of marker genes vs. clusters, UMI counts
spots
matrix of marker genes vs. spots, same dimensions as cluster_markers
L1
L1/LASSO penalty to increase sparsity of the deconvolution
Details
We will need to find an L1 penalty that works best for deconvolution.
Goralsth/FloodLight documentation built on April 20, 2022, 12:42 a.m.
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.
| deconvolute_NNLS | R Documentation |
Non-negative Least Squares (NNLS) deconvolution
Description
Use NNLS to deconvolute a matrix of spots consisting of unknown cell types against a reference of known cell type marker gene signatures.
Usage
deconvolute_NNLS(cluster_markers, spots, L1 = 0.01)
Arguments
cluster_markers |
matrix of marker genes vs. clusters, UMI counts |
spots |
matrix of marker genes vs. spots, same dimensions as |
L1 |
L1/LASSO penalty to increase sparsity of the deconvolution |
Details
We will need to find an L1 penalty that works best for deconvolution.
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.