Introduction

VIEWpoly is a shiny app and R package for visualizing and exploring results from polyploid computational tools using an interactive graphical user interface. The package allows users to directly upload output files from polymapR (Bourke et al. (2018)), MAPpoly (Mollinari et al. (2019)), polyqtlR (Bourke et al. (2021)), QTLpoly (Pereira et al. (2019)), diaQTL (Amadeu et al. (2021)) and genomic assembly, variants, annotation and alignment files. VIEWpoly uses shiny, golem, ggplot2, plotly, and JBrowseR libraries to integrate and graphically display the QTL profiles, positions, estimated allele effects, progeny individuals containing specific haplotypes, and their breeding values. When genomic information is available, QTL positions can be interactively explored using JBrowseR interface, allowing the search for candidate genes. The software allows for visualization of parental haplotypes and marker dosages, and provides features to download specific information into comprehensive tables and images for further analysis and presentation.

The app is organized in the Input data section and three main modules: VIEWqtl, VIEWgenome, and VIEWmap. Please check our tutorial video for a step-by-step guide through all VIEWpoly’s features and functionalities.

Install and run the app

VIEWpoly is available in both stable and development versions. To install and load its stable version from the CRAN repository, please run:

install.packages("viewpoly")
viewpoly::run_app()

If you want to install and check the development version from the Github repository, please run the commands below:

install.packages("devtools")
devtools::install_github("mmollina/viewpoly")
viewpoly::run_app()

NOTE: Windows users may need to install Rtools before running the commands above.

The four VIEWpoly’s main modules are available in the top menu, which are described in the following sections:


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Input data

The first module allows users to upload datasets or select pre-loaded examples. Uploaded datasets may include results from at least one of the following: linkage analysis, QTL analysis. Users can use RData or standard format files (CSV and TSV) to upload linkage and QTL analysis results. Genome assemblies can be provided in the regular FASTA format. VIEWpoly also accepts remote URLs to access genome-related files on-the-fly (see description here), and can optionally integrate other genomic information (GFF3, VCF, BAM, WIG files).

Please note that each section accepts multiple options for the same type of analysis. When files for more than one option is provided, only the last one will be displayed. Users need to make sure that linkage, QTL and genome-related files are tied to each other, e.g., uploaded QTL results were obtained using the uploaded linkage map, and both were based on the same uploaded genome assembly and gene annotation versions. Each section-related features will be enabled once their respective files are uploaded. The package also detects results from the supported software that are currently loaded in the R environment.

The app will automatically convert linkage and QTL analysis results to the VIEWpoly file format. Users may optionally download it using the Download VIEWpoly dataset button, so it can be used in future sessions to expedite data processing and loading time. This file can be loaded directly within the R environment (code: load("my_dataset.RData")) or uploaded using the Upload VIEWpoly dataset button. Due to their size, genome information cannot be stored using the VIEWpoly data structure, so these files need to be provided each section.

Available example datasets

Linkage and QTL analysis results from a previous study in a tetraploid potato (S. tuberosum) mapping population are available as a pre-loaded example in the app:

NOTE: to save space in the package repository, only a small subset of the progeny individuals is provided.


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Other example files are available here, including data from an hexaploid sweetpotato (I. batatas) mapping population:

Users may choose one of the pre-loaded examples to explore the software features. By default, the app will display the tetraploid potato dataset.

Upload linkage map files

Click in the + on the right side of the Upload linkage map files box to upload linkage analysis results:


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Users can upload files in three different formats: MAPpoly, polymapR, and standard formats (CSV or TSV files). There is a brief description with useful links on how to build linkage maps and obtain the necessary files using the supported packages.


Upload MAPpoly

All you need is an object of class mappoly.map saved in a RData file. Click on the + icon in the upper right side of the box to upload the file:


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