PHYLUCE is a software package for the analysis of conserved genomic loci

By B. Faircloth. bioRxiv, 2015

907 citations recorded by the source corpus.

Summary Targeted enrichment of conserved and ultraconserved genomic elements allows universal collection of phylogenomic data from hundreds of species at multiple time scales (< 5 Ma to > 300 Ma). Prior to downstream inference, data from these types of targeted enrichment studies must undergo pre-processing to assemble contigs from sequence data; identify targeted, enriched loci from the off-target background data; align enriched contigs representing conserved loci to one another; and prepare and manipulate these alignments for subsequent phylogenomic inference. PHYLUCE is an efficient and easy-to-install software package that accomplishes these tasks across hundreds of taxa and thousands of enriched loci. Availability and Implementation PHYLUCE is written for Python 2.7. PHYLUCE is supported on OSX and Linux (RedHat/CentOS) operating systems. PHYLUCE source code is distributed under a BSD-style license from https://www.github.com/fairclothUlab/phyluce/. PHYLUCE is also available as a package (https://binstar.org/fairclothUlab/phyluce) for the Anaconda Python distribution that installs all dependencies, and users can request a PHYLUCE instance on iPlant Atmosphere (tag: phyluce). The software manual and a tutorial are available from http://phyluce.readthedocs.org/en/latest/ and test data are available from doi: 10.6084/m9.figshare.1284521. Contact brant@fairclothUlab.org Supplementary information Supplementary Figure 1.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4bcedf9bdf76e95ee35fbd9e0738e2585969c7c9

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Citations in the corpus

MitoFinder: Efficient automated large‐scale extraction of mitogenomic data in target enrichment phylogenomics (2019, methodology): “As recommended by Faircloth (2016), we first relied on T riniTy to assemble UCE contigs using the phyluce_assembly_assemblo_trinity module of PHyLUCE .”
Identifying conserved genomic elements and designing universal bait sets to enrich them (2017, methodology): “Finally, because the targeted enrichment approach is DNA based, it can be applied to degraded and low-quantity samples, such as those in many specimen or tissue collections (Bi et al. 2013; McCormack, Tsai & Faircloth 2015; Blaimer et al. 2016; Lim&Braun 2016; Ruane&Austin 2017).”
Ultraconserved elements show utility in phylogenetic inference of Adephaga (Coleoptera) and suggest paraphyly of ‘Hydradephaga’ (2017, methodology): “We assembled our UCE dataset as described at https://github .com/laninsky/UCE_processing_steps, primarily using the phyluce 1.5 software package for Python 2.7 (Faircloth, 2016).”
Enriching the ant tree of life: enhanced UCE bait set for genome‐scale phylogenetics of ants and other Hymenoptera (2017, methodology): “Sequence capture of conserved genomic loci (UCEs) has emerged as a revolutionary tool for efficiently investigating the evolutionary history of organisms (Faircloth et al. 2012, 2015; Blaimer et al. 2015; Branstetter et al. 2016b; Glenn & Faircloth 2016).”