از داده‌های خام تا درخت‌های فیلوژنتیک: گردش کار بیوانفورماتیکی من

Building a Reproducible Dry-Lab Pipeline

Resolving the taxonomic identity of endophytic fungi requires much more than running a simple BLAST search. Over the course of my research on mangrove endophytes, I built a streamlined bioinformatics workflow to take raw Sanger sequencing outputs and turn them into publication-ready phylogenetic trees.

The process begins with inspecting raw chromatograms to trim low-quality bases and resolve ambiguous calls. Once the consensus sequences are assembled, I compile reference strain sequences from GenBank and use custom Python scripts in the command-line terminal to automate header formatting and file conversions between FASTA and NEXUS formats. For multiple sequence alignment, I rely on MAFFT to handle complex ribosomal and protein-coding regions, followed by careful manual refinement in AliView and MEGA12 to ensure positional homology.

Finally, for phylogenetic reconstruction, I combine Maximum Likelihood analysis in IQ-TREE (using ModelFinder for optimal substitution models and ultrafast bootstrap support) with Bayesian Inference in MrBayes and parsimony analyses in PAUP*. The resulting topologies are visualized in FigTree and exported for final graphic layout. Having a reproducible dry-lab pipeline has been essential for accurately placing cryptic mangrove isolates within their evolutionary frameworks.