5 Running Cluster 3.0 as a command line program

It is now possible to run Cluster 3.0 as a command line program. This may be useful if you want to run Cluster 3.0 on a remote server, and also allows automatic processing a large number of data files by running a batch script. Note, however, that the Python and Perl interfaces to the C Clustering Library are much better suited for this task and more powerful than the command line program (see the manual for the C Clustering Library at http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster/cluster.pdf).

The installation process of the command line version of Cluster 3.0 is straightforward; it compiled out of the box on Cygwin, Mac OS X, Linux, and Unix. To install, download the source code from http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster, and run
configure --without-x
make
make install
The executable is called cluster. To run this program, execute
cluster [options]
in which the options consist of the following command line parameters:

-f filename

File loading

-l

Specifies to log-transform the data before clustering (default is no log-transform)

-cg a|m

Specifies whether to center each row (gene) in the data set:
a: Subtract the mean of each row
m: Subtract the median of each row
(default is no centering)

-ng

Specifies to normalize each row (gene) in the data set (default is no normalization)

-ca a|m

Specifies whether to center each column (microarray) in the data set:
a: Subtract the mean of each column
m: Subtract the median of each column
(default is no centering)

-na

Specifies to normalize each column (microarray) in the data set (default is no normalization)

-u jobname

Allows you to specify a different name for the output files (default is derived from the input file name)

-g [0..9]

Specifies the distance measure for gene clustering. 0 means no gene clustering; for the values 1 through 9, see below (default: 1)

-e [0..9]

Specifies the distance measure for microarray clustering. 0 means no microarray clustering; for the values 1 through 9, see below (default: 0)

-m [msca]

Specifies which hierarchical clustering method to use:
m: Pairwise complete- (maximum-) linkage (default)
s: Pairwise single-linkage
c: Pairwise centroid-linkage
a: Pairwise average-linkage

-k number

Specifies whether to run k-meansclustering instead of hierarchical clustering, and the number of clusters k to use (default: 0, no k-means clustering)

-s

Specifies to calculate an SOM instead of hierarchical clustering

-x number

Specifies the horizontal dimension of the SOM grid (default: 2)

-y number

Specifies the vertical dimension of the SOM grid (default: 1)

-v, --version

Display version information

-h, --help

Display help information

For the command line options -g, -e, the following integers can be used to specify the distance measure:

0

No clustering

1

Uncentered correlation

2

Pearson correlation

3

Uncentered correlation, absolute value

4

Pearson correlation, absolute value

5

Spearman's rank correlation

6

Kendall's tau

7

Euclidean distance

8

City-block distance