This R package provides tools for 2D geometric morphometric (GMM) analysis with integrated recording of data provenance and data processing steps. Functions have been developed for use by beginning R users in a teaching context. Includes tutorial vignettes and sample datasets.
The package can be installed in an instance of R from Git Hub using the package devtools
.
devtools::install_github("aphanotus/borealis")
library(borealis)
One of the goals of this package is to provide a system to record data provenance in the objects produced through a morphometry workflow. Most of the important GMM steps employ functions from the R package geomorph.
For a tutorial of a GMM workflow using borealis
, see the vignettes online or in Rstudio.
vignette("gmm-tutorial", package="borealis")
vignette("gmm-template", package="borealis")
A simple function to calculate generalized AIC for models created by vegan::adonis
.
Calculate the matrix of distances between landmarks in 2-D shape data, optionally scaled by centroid size.
A function that returns the proportion of variance explained by each axis in a principal component analysis (PCA).
A function to read in linear multivariate morphometric (MMM) data from a csv
or xlsx
file.
The input spread sheet is assumed to be "long," in the sense that one column includes a list measurements made either by hand or in graphics software such as ImageJ.
This organization is typically convenient for rapid data entry.
The function re-formats the multiple measurements into a list containing the data in a traditional "wide" tabular format, with each measurement in a separate column. It also returns several elements
describing the data and providing data provenance.
This function takes raw qPCR data and produces a convenient plot and table, which can be used to assess the data.
Shape data and associated metadata for soapberry bug specimens (Jadera haematoloma) from Fawcett et al. 2018 Nature Communications. Jadera
contains data for bugs collected in the wild and raised under various environmental conditions in the lab. JaderaRNAi
includes similar data for bugs subjected to juvenile stage RNA interference targeting FoxO and several components of the EGF signaling pathway. Both datasets include 42 landmarks from the dorsal side and linear metadata for the length of ventral appendages. Landmarks include the head, pronotum, mesonotum and one (upper) forewing.
Preliminary shape data from bumblebee forewings. These data were imported from a tps
file using read.tps
. (The file was created from raw data using create.tps
.) These data are very preliminary. They have not been curated and have not undergone Procrustes alignment. The main purpose of these data are for trouble shooting morphometric workflows.
This phylogeny covers 26 bumblebee species (Bombus) focusing on those found in northeastern North America. The tree is based on sequence data from five genes, reported by Cameron et al. (2007). The taxa in that study were subset to the species included here. Sequences were realigned using ClustalW and the consensus tree was inferred using RAxML. The phylo
list also includes data on taxonomy, node support, species names, and convenient short species codes.
A simulated dataset of with 16 landmarks on the femur and tibia for 100 mantis specimens. Two species with male and female shape differences are included.
A dataset reporting the corolla lengths of Nicotiana flowers of different breeds, after hybridization, and after several generations of artificial selection for longer or shorter corolla lengths. These data originally appeared in East (1916).
This dataset is often used in genetics courses to present the effects of selection on quantitative traits. East1916
organizes the data in a "tidy" long format. East1916.wide
presents the data in a data frame that most closely resembles the original Table 1 from East (1916).