Abstract
Inferences on the evolutionary history of a gene can provide insight into whether the findings made for a given gene in a given species can be extrapolated to other species, including humans, help explain morphological evolution or give an explanation for unexpected findings regarding gene expression suppression experiments, among others. The large amount of sequence data that is already available, and that is predicted to dramatically increase in the next few years, means that life science researchers need efficient automated ways of analyzing such data. Moreover, especially when dealing with divergent sequences, inferences can be affected by the chosen alignment and tree building algorithms, and thus the same dataset should be analyzed in different ways, reinforcing the need for the availability of efficient automated ways of analyzing the sequencing data. Therefore, here, we present auto-phylo, a simple pipeline maker for phylogenetic studies, and provide two examples of its utility: one involving a small already formatted sequenced dataset (41 CDS) to determine the impact of the use of different alignment and tree building algorithms in an automated way, and another one involving the automated identification and processing of the sequences of interest, starting from 16550 bacterial CDS FASTA files downloaded from the NCBI Assembly RefSeq database, and subsequent alignment and tree building inferences.
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Acknowledgments
This research was financed by the National Funds through FCT—Fundação para a Ciência e a Tecnologia, I.P., under the project UIDB/04293/2020, and by the Consellería de Educación, Universidades e Formación Profesional (Xunta de Galicia), under the scope of the strategic funding ED431C2018/55-GRC and ED431C 2022/03-GRC Competitive Reference Group. PD is supported by a PhD fellowship from Fundação para a Ciência e Tecnologia (SFRH/BD/145515/2019), co-financed by the European Social Fund through the Norte Portugal Regional Operational Programme (NORTE 2020).
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López-Fenández, H., Pinto, M., Vieira, C.P., Duque, P., Reboiro-Jato, M., Vieira, J. (2023). Auto-phylo: A Pipeline Maker for Phylogenetic Studies. In: Rocha, M., Fdez-Riverola, F., Mohamad, M.S., Gil-González, A.B. (eds) Practical Applications of Computational Biology and Bioinformatics, 17th International Conference (PACBB 2023). PACBB 2023. Lecture Notes in Networks and Systems, vol 743. Springer, Cham. https://doi.org/10.1007/978-3-031-38079-2_3
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DOI: https://doi.org/10.1007/978-3-031-38079-2_3
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