aphanotus / borealis

An R package for common activities in an integrative biology lab
5 stars 2 forks source link

borealis: an R package for reproducible geometric morphometric analysis

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.

GMM workflow template

GMM tutorial

Installation

The package can be installed in an instance of R from Git Hub using the package devtools.

devtools::install_github("aphanotus/borealis")
library(borealis)

Morphometrics

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")

Other functions

adonis.aic

A simple function to calculate generalized AIC for models created by vegan::adonis.

centroid.scaled.distances

Calculate the matrix of distances between landmarks in 2-D shape data, optionally scaled by centroid size.

pcvar

A function that returns the proportion of variance explained by each axis in a principal component analysis (PCA).

read.mmm

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.

Molecular stuff

qPCR.plot

This function takes raw qPCR data and produces a convenient plot and table, which can be used to assess the data.

Data

Jadera

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.

Bombus.forewings

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.

Bombus.tree

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.

mantis

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.

East1916

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).