To learn more about how to use easyFulcrum, check out the andersenlab/easyFulcrum repo and the easyFulcrum manuscript. This package is designed for processing and analyzing ecological sampling data generated using the Fulcrum mobile application.
To learn more about easyXpress including how to install and use the package, check out the andersenlab/easyXpress repo and the easyXpress manuscript. This package is designed for the reading, processing, and visualization of images obtained from the Molecular Devices ImageExpress Nano Imager, and processed with CellProfiler's WormToolbox. The easysorter package requires COPASutils installation as well. 2019)Īlmost every paper published from the lab has used easysorter, for more, check out our lab papers The first dominance/hemizygosity easysorter paperĪ Novel Gene Underlies Bleomycin-Response Variation in Caenorhabditis elegans ( Brady et al. The Gene scb-1 Underlies Variation in Caenorhabditis elegans Chemotherapeutic Responses ( Evans and Andersen 2020) Here are some of the papers using easysorter:Ī Powerful New Quantitative Genetics Platform, Combining Caenorhabditis elegans High-Throughput Fitness Assays with a Large Collection of Recombinant Strains ( Andersen et al. This package is specialized for use with worms and includes additional functionality on top of that provided by COPASutils, including division of recorded objects by larval stage and the ability to regress out control phenotypes from those recorded in experimental conditions To learn more about easysorter including how to install and use the package, check out the andersenlab/easysorter repo. This package is effectively version 2 of the COPASutils package. To learn more about COPASutils including how to install and use the package, check out the andersenlab/COPASutils repo and the COPASutils manuscript easysorter ¶ COPASutils offers a powerful suite of functions for the rapid processing and analysis of large high-throughput screening data sets.
Researchers studying small organisms, such as Caenorhabditis elegans, Anopheles gambiae, and Danio rerio, and using these devices will benefit from this streamlined and extensible R package. Data obtained from these powerful experimental platforms can be unwieldy, leading to difficulties in the ability to process and visualize the data using existing tools. The R package COPASutils provides a logical workflow for the reading, processing, and visualization of data obtained from the Union Biometrica Complex Object Parametric Analyzer and Sorter (COPAS) or the BioSorter large-particle flow cytometers. For help running a GWA mapping using cegwas2, see cegwas2-nf or the dry guideĪlso check out the linkagemapping-nf repo for a reproducible Nextflow pipeline for linkage mapping and two-dimensional genome scans (scan2) for one or several traits. To learn more about the cegwas2 R package, see the andersenlab/cegwas2 repo. However, mapping is rarely if never done with cegwas2 in R manually. In 2019, the cegwas2-nf Nextflow pipeline was developed to perform GWA mapping on QUEST using this cegwas2 R package. This package contains a set of functions to process phenotype data, perform GWAS, and perform post-mapping data processing for C. The Andersen lab maintains several R packages useful for high-throughput data analysis. Also check out the lab_code slack channel for help/questions!.Andersen Lab R Knowledge base & Cheatsheet.If you are looking for some help getting started with R or taking your R to the next level, check out these useful resources: