csfit: csfit: Deconvolution from Known Cell Proportions

In shenorrLab/csSAM: csSAM - cell-specific Significance Analysis of Microarrays

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

cc	Matrix of cell-frequency. (n by k, n samples, k cell-types)
G	Matrix of gene expression, columns ordered in the same order at the cell-frequency matrix (n by g, n samples, g genes)
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.
n	The number of samples used in the fit.

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, doi: 10.1038/nmeth.1439 (URL: http://doi.org/10.1038/nmeth.1439).

shenorrLab/csSAM documentation built on May 29, 2019, 9:23 p.m.