The phruta R package and salphycon shiny app: increasing access, reproducibility, and transparency in phylogenetic analyses
Roman Palacios, C.
Show abstract
O_LICurrent practices for assembling phylogenetic trees often recur to sequence data stored in GenBank. However, the molecular and taxonomic make up of sequences deposited in GenBank is generally not very clear. C_LIO_LI phruta, a newly developed R package, is designed to primarily improve access to genetic data stored in GenBank. Functions in phruta further enable users to assemble single- and multi-gene molecular datasets, and run basic phylogenetic tasks, all within R. C_LIO_LIThe structure of the functions implemented in phruta, designed as a workflow, aim to allow users to assemble simple workflows for particular tasks, which are in turn expected to increase reproducibility of relatively simple phylogenies. C_LIO_LITo support the use of phruta by researchers in different fields with variable levels of coding expertise, this paper presents salphycon, a shiny web app that is expected to increase access to the fundamental functions in the phruta R package. C_LI
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Treerecs: an integrated phylogenetic tool, from sequences to reconciliations 96%
- MSCquartets 1.0: Quartet methods for species trees and networks under the multispecies coalescent model in R 95%
- PoSeiDon: a Nextflow pipeline for the detection of evolutionary recombination events and positive selection 95%
Similar papers in this journal
- COInr and mkCOInr: Building and customizing a non-redundant barcoding reference database from BOLD and NCBI using a lightweight pipeline. 97%
- A snakemake toolkit for the batch assembly, annotation, and phylogenetic analysis of mitochondrial genomes and ribosomal genes from genome skims of museum collections. 94%
- TREEasy: an automated workflow to infer gene trees, species trees, and phylogenetic networks from multilocus data 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.