Parameter-bootstrap verification
Being able to accurately determine phylogeny depends on the accurate and efficient acquisition of target genes. At this time, selecting a suitable reference from closely related taxa for non-model species still remains challenging for researchers. To address this issue, we developed a parameter-bootstrap verification solution in GeneMiner. This method generates a new set of simulated reference data by employing a mutation model and repeated re-sampling. GeneMiner can then include the newly set of simulated reference data as input to assemble the target gene again. We observe target genes with bootstrap scores below 90 tend to have an unstable assembly, and therefore may not be reliable reference choices. While target genes with bootstrap scores above 90 can also exhibit an unstable assembly, their overall indel and substitution rates are comparatively lower. Our statistical analysis led us to select target genes with bootstrap scores of 90 or higher, which allowed us to mitigate the potential impact of unstable assembly. This indicates that the parameter-bootstrap verification method is effective in evaluating assembly results and can guide reference sequence selection. GeneMiner offers improved sensitivity to false substitutions compared to insertions and deletions, which excludes accounting for insertions and deletions in reference data. Users should exercise caution when inserting and removing large portions of the assembly results, although these large insertions and deletions have minimal impact on the phylogenetic results after being corrected. As an added measure to ensure accuracy when using GeneMiner, we suggest that users employ a software such as trimAL (Capella-Gutierrez et al., 2009) to edit the sorting file before constructing a phylogenetic tree.