YeastCellCycle


This data set contains a subset of yeast cell cycle data taken from Spellman et al. (1998) (See the reference below). Spellman et al. (1998) monitored the genome-wide mRNA levels for 6108 yeast genes at 7-minute intervals for 119 minutes. A total of 256 genes were identified to oscillate significantly in at least two data sets. This example data set contains the log ratios of these 256 genes at the first 16 time points(from 0 min to 105 min).


datasets

We proposed a new model-based clustering method, called the clustering of
regression models method(CORM), which groups genes that share a similar
relationship to the covariate(s). This method provides a unified approach
for a family of clustering procedures and can be applied to data collected
with various experimental designs. This package includes the implementation
for two such clustering procedures: (1) the Clustering of Linear Models
(CLM) method, and (2) the Clustering of Linear Mixed Models (CLMM) method.

Jiejun Shi

CORM

The Clustering of Regression Models Method

YeastCellCycle function

A list comprised of three components: normalizedData, normalizedData.sample and designMatrix.
 <ol>
<li> normalizedData is a three dimensional array containing the normalized expression data of the 256 genes during yeast cell-cycle. 
 </li>
<li> normalizedData.sample is a randomly selected sample from normalizedData. It only contains 64 genes.
 </li>
<li> designMatrix is a three dimensional array used to fit the clustering of linear mixed models (CLMM).
 </li>
</ol>

Format

http://genome-www.stanford.edu/cellcycle/data/rawdata/

YeastCellCycle: Yeast Cell Cycle Data Set

Description

Usage

Arguments

Format

Source

References