We demonstrate how to perform phylogenetic analyses and graphics in a single workflow using R for mtDNA sequences. Moreover, a haplotype network based on nucleotide differences between haplotypes can be created. It is frequently used in phylogenetic research and it is possible to group individuals as haplotypes by defining variations in the mtDNA for every population. One of the strongest biomarkers used to estimate phylogenetic relationships is also mitochondrial DNA. Therefore, they provide a wide range of options and are quite practical. Additionally, with R Markdown, journal articles and multi-part books can be written, and websites and blogs can be generated. With knitr package, a new Markdown file is created and converted into different file formats such as PDF, HTML, Word etc. R and RStudio create an R Markdown document provided by the rmarkdown package, which can store all code snippets, analyses, results, and images in a document. RStudio is a software that combines various components of R, such as console, resource editing, graphics, history, help, in one workbench. On the other hand, RStudio is an open-source Integrated Development Environment (IDE) for the R programming language. It is free and it enables static and dynamic program analyses. R is an environment for linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering and graphics. Although R (programming language) is a software environment for statistical computing and graphics, it is increasingly used in bioinformatics and phylogenetic data analysis thanks to advanced packages and libraries. At this point, there is a need for a platform where analyses can be performed in a single framework. This way of working can cause increased workload and time loss. Therefore, users have to prepare different input files for almost every program. To use these software packages, datasets need to be in different input file formats. Although there are many software packages to estimate parameters, they don’t work together in a common workflow that can compute these parameters in one task. Phylogenetic relationships are mostly calculated using computer programs with several mathematical models. This article presents a short guide on how to perform phylogenetic analyses using R and RStudio. As an example dataset, we used 120 Bombus terrestris dalmatinus mitochondrial cytochrome b gene (cyt b) sequences (373 bp) collected from eight different beehives in Antalya. In this article, by using the multiple sequences FASTA format file (.fas extension) we demonstrate and share a workflow of how to extract haplotypes and perform phylogenetic analyses and visualizations in R. Furthermore, it is also possible to perform several analyses using a single input file format. R is an open source software environment, and it supports open contribution and modification to its libraries. But these programs have their own specific input and output formats, and users need to create different input formats for almost every program. To analyze these data, powerful new methods based on large computations have been applied in various software packages and programs. By using special computer programs developed in recent years, large amounts of data have been produced in the molecular genetics area. Phylogenetic analyses can provide a wealth of information about the past demography of a population and the level of genetic diversity within and between species.
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