Estimate cell type proportion with MuSiC and NNLS

weight is estimated with cell type covariance

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

Arguments

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 reciprocal

eps

Threshold of convergence

Value

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.