Automated Cleaning of Occurrence Records from Biological Collections

Automated flagging of common spatial and temporal errors in biological and paleontological collection data, for the use in conservation, ecology and paleontology. Includes automated tests to easily flag (and exclude) records assigned to country or province centroid, the open ocean, the headquarters of the Global Biodiversity Information Facility, urban areas or the location of biodiversity institutions (museums, zoos, botanical gardens, universities). Furthermore identifies per species outlier coordinates, zero coordinates, identical latitude/longitude and invalid coordinates. Also implements an algorithm to identify data sets with a significant proportion of rounded coordinates. Especially suited for large data sets. The reference for the methodology is: Zizka et al. (2019) .

Make Fake Data

Make fake data that looks realistic, supporting addresses, person names, dates, times, colors, coordinates, currencies, digital object identifiers ('DOIs'), jobs, phone numbers, 'DNA' sequences, doubles and integers from distributions and within a range.

Interface to Chromosome Counts Database API

A programmatic interface to the Chromosome Counts Database (< https://ccdb.tau.ac.il/>), Rice et al. (2014) . This package is part of the 'ROpenSci' suite (< https://ropensci.org>).

Interface to the Global Biodiversity Information Facility API

A programmatic interface to the Web Service methods provided by the Global Biodiversity Information Facility (GBIF; < https://www.gbif.org/developer/summary>). GBIF is a database of species occurrence records from sources all over the globe. rgbif includes functions for searching for taxonomic names, retrieving information on data providers, getting species occurrence records, getting counts of occurrence records, and using the GBIF tile map service to make rasters summarizing huge amounts of data.

'BEAUti' from R

'BEAST2' (< https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'BEAUti 2' (which is part of 'BEAST2') is a GUI tool that allows users to specify the many possible setups and generates the XML file 'BEAST2' needs to run. This package provides a way to create 'BEAST2' input files without active user input, but using R function calls instead.

Integrated Taxonomic Information System Client

An interface to the Integrated Taxonomic Information System ('ITIS') (< https://www.itis.gov>). Includes functions to work with the 'ITIS' REST API methods (< https://www.itis.gov/ws_description.html>), as well as the 'Solr' web service (< https://www.itis.gov/solr_documentation.html>).

Analysis of Work Loops and Other Data from Muscle Physiology Experiments

Functions for the import, transformation, and analysis of data from muscle physiology experiments. The work loop technique is used to evaluate the mechanical work and power output of muscle. Josephson (1985) modernized the technique for application in comparative biomechanics. Although our initial motivation was to provide functions to analyze work loop experiment data, as we developed the package we incorporated the ability to analyze data from experiments that are often complementary to work loops. There are currently three supported experiment types: work loops, simple twitches, and tetanus trials. Data can be imported directly from .ddf files or via an object constructor function. Through either method, data can then be cleaned or transformed via methods typically used in studies of muscle physiology. Data can then be analyzed to determine the timing and magnitude of force development and relaxation (for isometric trials) or the magnitude of work, net power, and instantaneous power among other things (for work loops). Although we do not provide plotting functions, all resultant objects are designed to be friendly to visualization via either base-R plotting or 'tidyverse' functions. This package has been peer-reviewed by rOpenSci (v. 1.1.0).

Optimizing Acoustic Signal Detection

Facilitates the automatic detection of acoustic signals, providing functions to diagnose and optimize the performance of detection routines. Detections from other software can also be explored and optimized. This package has been peer-reviewed by rOpenSci. Araya-Salas et al. (2022) .

Download and Explore Datasets from UCSC Xena Data Hubs

Download and explore datasets from UCSC Xena data hubs, which are a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. Databases are normalized so they can be combined, linked, filtered, explored and downloaded.

Call Google's 'Natural Language', 'Cloud Translation', 'Cloud Speech', and 'Cloud Text-to-Speech' APIs

Access Google Cloud machine learning APIs for text and speech tasks. Use the Cloud Translation API for text detection and translation, the Natural Language API to analyze sentiment, entities, and syntax, the Cloud Speech API to transcribe audio to text, and the Cloud Text-to-Speech API to synthesize text into audio files.