Use of DAVID algorithms for clustering custom annotated gene lists in a non-model organism, rainbow trout

The DAVID gene functional classification tool requires adaptations for use in non-model species and there is little available information to guide selection of a kappa score. Our objective was to develop an R-script that allows custom gene identifiers and novel annotation information to be incorporated into analyses, then use such data to evaluate the number of differentially expressed genes (DEGs) in a comparison based on kappa score selection.

Using an R-script we developed and multiple data sets ranging from 555 to 3340 annotated DEGs from a study in rainbow trout, we found the percentage of DEGs harbored within a module and the number of genes shared among multiple modules decreased with increasing kappa score regardless of the number of DEGs in the comparison. The number of genes in enriched modules peaked at a kappa score of 0.5 for the comparisons with 3340 and 1313 DEGs and 0.3 for 555 DEGs. The number of genes harbored within enriched modules generally decreased with increasing kappa score; however, this was affected by whether the largest modules were significantly enriched. Large non-enriched modules can be reanalyzed using a higher kappa score resulting in some of the genes clustering in smaller enriched modules.