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Spöri, Y.

Publications and source records attributed to Spöri, Y..

2 recordsLinked to original sources

Haxe as a Swiss knife for bioinformatic applications: the SeqPHASE case story

1Haxe is a general purpose, object-oriented programming language supporting syntactic macros. The Haxe compiler is well known for its ability to translate the source code of Haxe programs into the source code of a variety of other programming languages including Java, C++, JavaScript and Python. Although Haxe is becoming more and more used for a variety of purposes, including games, it has not yet attracted much attention from bioinformaticians. This is surprising, as Haxe allows generating different versions of the same program (e.g. a graphical user interface version in JavaScript running in a web browser for beginners and a command-line version in C++ or Python for increased performance) while maintaining a single code, a feature that should be of interest for many bioinformatic applications. To demonstrate the usefulness of Haxe in bioinformatics, we present here the case story of the program SeqPHASE, written originally in Perl (with a CGI version running on a server) and published in 2010. As Perl+CGI is not desirable anymore for security purposes, we decided to rewrite the SeqPHASE program in Haxe and to host it at Github Pages (https://eeg-ebe.github.io/SeqPHASE), thereby alleviating the need to configure and maintain a dedicated server. Using SeqPHASE as an example, we discuss the advantages and disadvantages of Haxes source code conversion functionality when it comes to implementing bioinformatic software.

bioinformatics↗

KoT: an automatic implementation of the K/θ method for species delimitation

AO_SCPLOWBSTRACTC_SCPLOWK/{theta} is a method to delineate species that rests on the calculation of the ratio between the average distance K separating two putative species-level clades and the genetic diversity{theta} of these clades. Although this method is explicitly rooted in population genetic theory, it was never benchmarked due to the absence of a program allowing automated analyses. For the same reason, its application by hand was limited to small datasets of a few tens of sequences. We present an automatic implementation of the K/{theta} method, dubbed KoT (short for "K over Theta"), that takes as input a FASTA file, builds a neighbour-joining tree, and returns putative species boundaries based on a user-specified K/{theta} threshold. This automatic implementation avoids errors and makes it possible to apply the method to datasets comprising many sequences, as well as to test easily the impact of choosing different K/{theta} threshold ratios. KoT is implemented in Haxe, with a javascript webserver interface freely available at https://eeg-ebe.github.io/KoT/

evolutionary biology↗