The basal transcriptional dataset (CMP versus control) was interrogated with terms that would potentially reveal a neurotrophin-based or age-related bias in the CMP-mediated transcriptome set.
Datasets for basal and dexamethasone-induced DOC levels were subjected to simple interval mapping analysis using Haley Knott regression equations.
MYC over-expression in basal cancer in other datasets can be distinguished on the basis of frequency [50], but our analysis of the five meta-analysis datasets indicates that it is not a prominent feature, ranking below the top 1000 differentially expressed mRNAs.
When analyzed in a different cancer dataset, the basal-like subtype had a poor outcome when compared to other subtypes of breast cancer [ 35].
To determine how much sequence data would be necessary to resolve each of the basal nodes we simulated datasets of 10 kb, 12 kb, and 14 kb based on the best tree, using the same sequence parameters of the original combined dataset.
This high R2 may reflect the relatively large plot size (0.25 ha) and wide range in basal area covered by the dataset as increases in both factors often result in increases in the coefficient of determination (see Zhao et al., 2009 for details on effects of plot size on precision).
The accuracy is calculated based on the percentage of the predicted basal subtype on the corresponding dataset.
For analysis of the single replicate dataset generated for basal gene expression levels in 10-day old seedlings of both genotypes, DChip was used [ 41].
For introns, the reduced dataset improved the basal split among rodent suborders (node I in Additional file 4) whereas for mitochondrial and exonic regions, support is increased at the more terminal nodes (C, E or G in Additional file 4).
A specific type of obesity, an elevated waist:hip ratio, was associated with the basal subtype in the Carolina dataset [ 40], but overall, the factors that determine subtype – genetics, microenvironment, environmental or developmental exposures – remain unclear.
