csfit: csfit: Deconvolution from Known Cell Proportions
Description
Deconvolves cell-specific expression using least-squares
fit. Input is the heterogeneous sample gene expression of
a group of samples and the matching cell-frequencies of
the sample. The lower limit for the number of samples
needed to deconvolving the cell-specific expression of N
cell-types is N+1. For a single color array - the result
could be interpreted as the average expression level of a
given gene in a cell-type of that group. Multiplied by
the frequency of a given cell-type in an individual in
the group, it is the amount contributed by that cell type
to the overall measured expression on the array.
Usage
csfit(cc, G, logRm = FALSE, logBase = 2)
Arguments
G
Matrix of gene expression, columns ordered in
the same order at the cell-frequency matrix (n by g, n
samples, g genes)
cc
Matrix of cell-frequency. (n by k, n samples, k
cell-types)
logRm
Exponentiate data for deconvolution stage.
Default is FALSE
logBase
Base of logarithm used to determine
exponentiation factor. Default is 2
Value
A list with three attributes:
ghat
A matrix of
cell-specific expression for each gene as derived from
the coefficients of the fit. (Size: k by g, k cell types,
gp genes)
se
Standard error of the fit
coefficients
residuals
The individual sample
residuals.
References
Shen-Orr SS, Tibshirani R, Khatri P, Bodian DL, Staedtler
F, Perry NM, Hastie T, Sarwal MM, Davis MM and Butte AJ
(2010). "Cell type-specific gene expression differences
in complex tissues." _Nature methods_, *7*(4), pp. 287-9.
ISSN 1548-7105, , .