[BioC] library (sma)

[Yee, Sook Wah]

Hi Bioconductor,

  The library(sma) is no longer supported on R-Console.  I was told to download library(limma) instead.  However, I am encountering problem when I need to work on the exercises following the examples given in this website link below.  Could you please let me know what I should do instead of using the code given in the examples in the link below for question 3 (Q3).  Thank you.

http://bioinf.wehi.edu.au/marray/ibc2004/lab4/lab4.html#5.%20R%20and%20Bioconductor%20WWW%20resources

Q3. You might also like to create a cluster image using the function heatmap in the package stats. We will create a clustering image that is commonly seen in many microarray literature.  By default, this function performs hierarchical clustering on both genes and samples and the function will slow down considerably if the number of genes are too large. For illustration purposes, we have selected 100 variable genes.

library(sma)
golubvar <- apply(golub, 1, var, na.rm = TRUE)
top100 <- stat.gnames(golubvar, 1:length(golubvar), crit = 100)$gnames
heatmap(golub[top100, ])


Regards,

Sook Wah