Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome.
BACKGROUND
We investigate and quantify the generalizability of the white blood cell (WBC) transcriptome to the general, multiorgan transcriptome. We use data from the NCBI's Gene Expression Omnibus (GEO) public repository to define two datasets for comparison, WBC and OO (Other Organ) sets.


RESULTS
Comprehensive pair-wise correlation and expression level profiles are calculated for both datasets (with sizes of 81 and 1463, respectively). We have used mapping and ranking across the Gene Ontology (GO) categories to quantify similarity between the two sets. GO mappings of the most correlated and highly expressed genes from the two datasets tightly match, with the notable exceptions of components of the ribosome, cell adhesion and immune response. That is, 10 877 or 48.8% of all measured genes do not change >10% of rank range between WBC and OO; only 878 (3.9%) change rank >50%. Two trans-tissue gene lists are defined, the most changing and the least changing genes in expression rank. We also provide a general, quantitative measure of the probability of expression rank and correlation profile in the OO system given the expression rank and correlation profile in the WBC dataset.
National Center for Biomedical Computing Informatics for Integrating Biology and the Bedside (i2b2), Boston, MA 02115, USA.
Isaac S
IS
Kohane
Vladimir I
VI
Valtchinov
D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks; D006801:Humans; D007962:Leukocytes / Q000378:metabolism*; D009369:Neoplasms / Q000235:genetics; D014157:Transcription Factors / Q000378:metabolism; D018875:Vocabulary, Controlled
D014157:Transcription Factors