Selection of relevant genes in cancer diagnosis based on their prediction accuracy
Artificial Intelligence in Medicine
| Hi-index | 3.84 |
Motivation: Genes are often characterized dichotomously as either housekeeping or single-tissue specific. We conjectured that crucial functional information resides in genes with midrange profiles of expression. Results: To obtain such novel information genome-wide, we have determined the mRNA expression levels for one of the largest hitherto analyzed set of 62 839 probesets in 12 representative normal human tissues. Indeed, when using a newly defined graded tissue specificity index τ, valued between 0 for housekeeping genes and 1 for tissue-specific genes, genes with midrange profiles having 0.15 50% of all expression patterns. We developed a binary classification, indicating for every gene the IB tissues in which it is overly expressed, and the 12 - IB tissues in which it shows low expression. The 85 dominant midrange patterns with IB = 2--11 were found to be bimodally distributed, and to contribute most significantly to the definition of tissue specification dendrograms. Our analyses provide a novel route to infer expression profiles for presumed ancestral nodes in the tissue dendrogram. Such definition has uncovered an unsuspected correlation, whereby de novo enhancement and diminution of gene expression go hand in hand. These findings highlight the importance of gene suppression events, with implications to the course of tissue specification in ontogeny and phylogeny. Availability: All data and analyses are publically available at the GeneNote website, http://genecards.weizmann.ac.il/genenote/ and, GEO accession GSE803. Contact: doron.lancet@weizmann.ac.il Supplementary information: Four tables available at the above site.