«Using innovative data normalization and
gene selection approaches, we combined the statistical power of multiple genomic studies and masked their variability and batch effects to identify robust early diagnostic biomarkers of pancreatic cancer,» said first author Manoj Bhasin, PhD, Co-Director of BIDMC's Genomics, Proteomics, Bioinformatics and Systems Biology Center and Assistant Professor of Medicine at HMS.
Not exact matches
A companion paper published in BMC Evolutionary Biology by colleagues at the EPA lab in Narragansett, RI, that used a «candidate
gene scan»
approach — examining SNPs from 42
genes associated with the AHR pathway — also identified AHR2 as a
gene that appears to be under
selection and is likely to be involved in the resistance.
Ensuring appropriate target
gene selection and maintaining a diversified pre-clinical engine are key aspects of our strategic
approach.
Despite exploiting signatures displaying different statistical properties, these methods individually detected
genes previously identified as undergoing
selection in domesticated horses, such as KITLG (9) and melanocortin 1 receptor (MC1R)(40), providing important validation of the
approach as a whole.
To ask whether
genes lying within regions of differentiation were significantly more affected by positive
selection than the genome - wide average, we used two
approaches.
A common
approach is to sort
genes by
gene ontology (GO)[9] category and speculate on their likely function, involvement in potential pathways, and reasons for being under
selection.
In human medicine, the identity of cytogenetic aberrations has been shown to also assist in the localization of cancer - associated
genes and even
selection of the most appropriate therapeutic
approach.