CellMix 1.6

Cell-Specific Expression by Standard Least-Squares

Description

Estimates cell-specific proportions given known proportions expression signatures, using least-squares fitting.

Usage

gedAlgorithm.cs_lsfit(..., rescale = TRUE, fit = c("ls", "nnls"))

Arguments

...
extra arguments passed to fitting the methods .nn_lsfit or .fcnnls.
rescale
logical used when estimating proportions from signatures, that indicates if the esti,ated coefficients should be scaled to sum up to one (TRUE) or left as estimated by the linear regression (FALSE). This scaling is performed after the coefficients have been forced to be nonnegative.
fit
least-square fitting method: ls uses lm, nnls uses fcnnls.

Details

The algorithm applies the same methods as the ged algorithm lsfit but to the transposed problem of estimating signatures from proportions. It is included in the CellMix package for test/experimental purposes.

Examples


# random target matrix
x <- rmatrix(100, 20)
# random cell proprtions
p <- rmatrix(3, 20)

# deconvolve using standard least-squares
res <- ged(x, p, 'cs-lsfit')
head(basis(res))

##         [,1]   [,2]    [,3]
## [1,] 0.46277 0.4749 0.08808
## [2,] 0.32924 0.4077 0.23206
## [3,] 0.01626 0.5285 0.47800
## [4,] 0.53150 0.4500 0.09519
## [5,] 0.16005 0.5324 0.41598
## [6,] 0.40514 0.5402 0.12278

# proportions are not updated
identical(coef(res), p)

## [1] TRUE

## Don't show: 
    stopifnot(identical(coef(res), p))
    stopifnot( nmf.equal(res, ged(x, p, 'cs-lsfit')) )
## End Don't show

# deconvolve using nonnegative least-squares
res <- ged(x, p, 'cs-lsfit', fit = 'nnls')
head(basis(res))

##         [,1]   [,2]    [,3]
## [1,] 0.46277 0.4749 0.08808
## [2,] 0.32924 0.4077 0.23206
## [3,] 0.01626 0.5285 0.47800
## [4,] 0.53150 0.4500 0.09519
## [5,] 0.16005 0.5324 0.41598
## [6,] 0.40514 0.5402 0.12278

# proportions are not updated
identical(coef(res), p)

## [1] TRUE

## Don't show: 
    stopifnot(identical(coef(res), p))
    stopifnot( nmf.equal(res, ged(x, p, 'cs-lsfit', fit = 'nnls'), tolerance = 10^-15) )
## End Don't show