<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/34146?offset=40 https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing Mon, 23 Apr 2018 05:49:50 -0500 https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing <![CDATA[DendroPy: a Python library for phylogenetic computing]]> DendroPy is a Python library for phylogenetic computing. It provides classes and functions for the simulation, processing, and manipulation of phylogenetic trees and character matrices, and supports the reading and writing of phylogenetic data in a range of formats, such as NEXUS, NEWICK, NeXML, Phylip, FASTA, etc. Application scripts for performing some useful phylogenetic operations, such as data conversion and tree posterior distribution summarization, are also distributed and installed as part of the libary. DendroPy can thus function as a stand-alone library for phylogenetics, a component of more complex multi-library phyloinformatic pipelines, or as a scripting “glue” that assembles and drives such pipelines.

The primary home page for DendroPy, with detailed tutorials and documentation, is at:

DendroPy is also hosted in the official Python repository:

Requirements and Installation

DendroPy 4.x runs under Python 3 (all versions > 3.1) and Python 2 (Python 2.7 only).

You can install DendroPy by running:

 

More information is available here:

Address of the bookmark: https://pypi.org/project/DendroPy/

]]> Seema Singh https://bioinformaticsonline.com/bookmarks/view/44468/orthoflow-workflow-for-phylogenetic-inference-of-genome-scale-datasets-of-protein-coding-genes Wed, 21 Feb 2024 06:13:08 -0600 https://bioinformaticsonline.com/bookmarks/view/44468/orthoflow-workflow-for-phylogenetic-inference-of-genome-scale-datasets-of-protein-coding-genes <![CDATA[Orthoflow: workflow for phylogenetic inference of genome-scale datasets of protein-coding genes]]> Orthoflow is a workflow for phylogenetic inference of genome-scale datasets of protein-coding genes. Our goal was to make it straightforward to work from a combination of input sources including annotated contigs in Genbank format and FASTA files containing CDSs. It uses several state of the art inference methods for orthology inference, either based on HMM profiles or de novo inference of orthogroups. Through the use of OrthoSNAP, many additional ortholog alignments can be generated from multi-copy gene families. For phylogenetic inference, users can choose a supermatrix approach and/or gene tree inference followed by supertree reconstruction. Users can specify a range of alignment filtering settings to retain high-quality alignments for phylogenetic inference. The workflow produces a detailed report that, in addition to the phylogenetic results, includes a range of diagnostics to verify the quality of the results.

Address of the bookmark: https://github.com/rbturnbull/orthoflow

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