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

1
  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.

Author(s)

Shai Shen-Orr, Rob Tibshirani, Narasimhan Balasubramanian, David Wang

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, <URL: http://dx.doi.org/10.1038/nmeth.1439>, <URL: http://www.ncbi.nlm.nih.gov/pubmed/20208531>.