Attach dataset's labelings

Once we have a dataset loaded we can attach labelings to it to provide additional information about the various rows, columns, and even cells of the dataset. For instance one typically wants a unique name for each row attached to the dataset so the summary plots can tell you the name of an interesting looking vector. With the Cho data set, this would be ORF (gene) identifiers.

orfs = labelings.Labeling(cho, 'orfs')
orfs.labelRows("ORFs.rlab")
cho.setPrimaryRowLabeling(orfs)

Once we have our primary labeling we might as well attach some other useful pieces of information. Included with the Cho dataset are labelings containing such things as gene common names, DiagEM clustering results, and a clustering which was manually done by [Cho et al., 1998].

names = labelings.Labeling(cho, 'names')
names.labelRows("CommonNames.rlab")

em = labelings.Labeling(cho, 'em')
em.labelRows("EM.rlab")

cho_clustering = labelings.Labeling(cho, 'cho_clustering')
cho_clustering.labelRows("ChoClassification.rlab")

We can also attach information to the columns of the dataset. The primaryColumnLabeling is used for many of the condition (x-axis) labels along the plots. For the Cho data set, this would be the time (in hours) at which each sample was taken for the time course experiment.

times = labelings.Labeling(cho, 'times')
times.labelCols("times.clab")
cho.setPrimaryColumnLabeling(times)



Brandon King 2005-07-29