music.basic.ct: Estimate cell type proportion with MuSiC and NNLS
In kalpita23/scRNA_package: Multi-subject single cell deconvolution

weight is estimated with cell type covariance

1	music.basic.ct(Y, X, S, Sigma.ct, iter.max, nu, eps)

`Y`	vector of bulk tissue expression
`X`	matrix, Signature matrix
`S`	vector of Avg. Library size
`Sigma.ct`	matrix of Subject level variation with
`iter.max`	numeric, maximum iteration number
`nu`	regulation parameter, take care of weight when taking recipical
`eps`	Thredshold of convergence

a list with elements: * p.nnls: vector of cell type proportions estimated by nnls (add up to 1) * q.nnls: vector of original estimation from nnls * fit.nnls: fitted value of Y from nnls * resid.nnls: residual value from nnls * p.weight: vector of cell type proportions estimated by weighted-nnls (add up to 1) * q.weight: vector of original estimation from weight-nnls * fit.weight: fitted value of Y from weighted-nnls * resid.weight: residual value from weighted-nnls * weight.gene: weight calculated from weighted-nnls * converge: 'Reach Maxiter', 'Converge at m' * rsd: residual value from weighted-nnls transfromed by weight * R.squared: R square of weighted-nnls * var.p: variance of weighted-nnls estimated cell type proportions

kalpita23/scRNA_package documentation built on June 26, 2020, 12:15 a.m.