bestDeconvolution | Find cell-type gene signatures and do deconvolution |
bigstatsenet | Elastic-net for compressed sensing using bigstatsr |
calculateError | Find errors in estimated proportion matrix and signature |
csDeCompress | TOAST-NMF deconvolution |
estimateUnmix | Run unmix from DESeq2 |
expandTarget | Expand targetted panel to larger feature space |
findInformSet | Select the compartment specific genes |
findNumberCells | Select the number of cell types using SVD methods |
hello | Hello, World! |
iterateSigs | Use NMF repeatedly with TOAST framework to find cell-type... |
kaiser | Kaiser method to determine number of important SVs |
l1Magic | Non-linear for compressed sensing |
l2Magic | Elastic-net for compressed sensing |
lar | Least angle regression for compressed sensing |
linCor | Use mutual linearity to find cell-type gene signatures and do... |
mseError | Select the number of cell types using SVD methods |
nmfOut | NMF function for TOAST |
trainCS | Wrapper to train compression matrix |
trainCS_gene | Wrapper to train compression matrix |
TVMagic | Elastic-net for compressed sensing |
vardecomp | Select CTS genes with variance proporties |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.