PGEE (version 1.5)

yeastG1: Yeast cell-cycle gene expression data

Description

A yeast cell-cycle gene expression data set collected in the CDC15 experiment of Spellman et al. (1998) where genome-wide mRNA levels of 6178 yeast open reading frames (ORFs) in a two cell-cycle period were measured at M/G1-G1-S-G2-M stages. However, to better understand the phenomenon underlying cell-cycle process, it is important to identify transcription factors (TFs) that regulate the gene expression levels of cell cycle-regulated genes. In this study, we presented a subset of 283 cell-cycled-regularized genes observed over 4 time points at G1 stage and the standardized binding probabilities of a total of 96 TFs obtained from a mixture model approach of Wang et al. (2007) based on the ChIP data of Lee et al. (2002).

Usage

data("yeastG1")

Details

A data frame with 1132 observations (283 cell-cycled-regularized genes observed over 4 time points) with 99 variables (e.g., id, y, time, and 96 TFs).

References

Lee, T.I., Rinaldi, N.J., Robert, F., Odom, D.T., Bar-Joseph, Z., Gerber, G.K., Hannett, N.M., Harbison, C.T., Thompson, C.M., Simon, I., et al. (2002). Transcriptional regulatory networks in Saccharomyces cerevisiae. Science, 298, 799--804. Spellman, P.T., Sherlock, G., Zhang, M.Q., Iyer, V.R., Anders, K., Eisen, M.B., Brown, P.O., Botstein, D., and Futcher, B. (1998). Comprehensive identification of cell cycle regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Molecular Biology of Cell, 9, 3273--3297. Wang, L., Chen, G., and Li, H. (2007). Group SCAD regression analysis for microarray time course gene expression data. Bioinformatics, 23, 1486--1494. Wang, L., Zhou, J., and Qu, A. (2012). Penalized generalized estimating equations for high-dimensional longitudinal data anaysis. Biometrics, 68, 353--360.

Examples

## Not run: ------------------------------------
# library(PGEE)
# # load data
# data(yeastG1)
# data <- yeastG1
# # get the column names
# colnames(data)[1:9]
# # see some portion of yeast G1 data
# head(data,5)[1:9]
# 
# # define the input arguments
# formula <- "y ~.-id"
# family <- gaussian(link = "identity")
# lambda.vec <- seq(0.01,0.2,0.01)
# # find the optimum lambda
# cv <- CVfit(formula = formula, id = id, data = data, family = family, scale.fix = TRUE,
# scale.value = 1, fold = 4, lambda.vec = lambda.vec, pindex = c(1,2), eps = 10^-6,
# maxiter = 30, tol = 10^-6)
# # print the results
# print(cv)
# 
# # see the returned values by CVfit
# names(cv)
# # get the optimum lambda
# cv$lam.opt
# 
# #fit the PGEE model
# myfit1 <- PGEE(formula = formula, id = id, data = data, na.action = NULL,
# family = family, corstr = "independence", Mv = NULL,
# beta_int = c(rep(0,dim(data)[2]-1)), R = NULL, scale.fix = TRUE,
# scale.value = 1, lambda = cv$lam.opt, pindex = c(1,2), eps = 10^-6, 
# maxiter = 30, tol = 10^-6, silent = TRUE)
# 
# # get the values returned by myfit object
# names(myfit1)
# # get the values returned by summary(myfit) object
# names(summary(myfit1))
# # see a portion of the results returned by coef(summary(myfit1))
# head(coef(summary(myfit1)),7)
# 
# # see the variables which have non-zero coefficients
# index1 <- which(abs(coef(summary(myfit1))[,"Estimate"]) > 10^-3)
# names(abs(coef(summary(myfit1))[index1,"Estimate"]))
# 
# # see the PGEE summary statistics of these non-zero variables
# coef(summary(myfit1))[index1,]
# 
# # fit the GEE model
# myfit2 <- MGEE(formula = formula, id = id, data = data, na.action = NULL,
# family = family, corstr = "independence", Mv = NULL,
# beta_int = c(rep(0,dim(data)[2]-1)), R = NULL, scale.fix = TRUE,
# scale.value = 1, maxiter = 30, tol = 10^-6, silent = TRUE)
# 
# # get the GEE summary statistics of the variables that turned out to be
# # non-zero in PGEE analysis
# coef(summary(myfit2))[index1,]
# 
# # see the significantly associated TFs in PGEE analysis
# names(which(abs(coef(summary(myfit1))[index1,"Robust z"]) > 1.96))
# 
# # see the significantly associated TFs in GEE analysis
# names(which(abs(coef(summary(myfit2))[,"Robust z"]) > 1.96))
# 
## ---------------------------------------------