Analyzing the RNA from model organisms can lend to significant discoveries in the microbiology field; however, differences across similar-purposed alignment software can lead to false analysis. Currently, there are several alignment software present, and our goal is to determine which one of these software is the “best” through the analysis of Rhizophagus irregularis in relation to Manihot esculenta. However, the word “best” has no set definition in this particular situation; furthermore, since there are no standard metrics we pulled from prior studies with very similar goals. We took our best aligner candidate(s) and re-aligned some of the more popular RNASeq papers from the past decade to see what genes/transcripts of importance were missed. Based on the factors separating our best candidate from the other alignment software, we can determine what common feature these genes may share. Without determining these factors, we could find a higher gap ratio (intronic regions), higher genomic ambiguity, less straightforward transcript derivation, etc. in our datasets.