During my graduate career I had the incredible opportunity to build an R package from the ground up. This package is now available for download through GitHub. Details are below.

Motivation

Developments in high-throughput imaging techniques have led to a rapid increase in these data. Researchers are able to move away from the laborious manual collection of images that typically limits large-scale analyses. However, typical users require software methods for efficient handling, analysis, and visualization to make the most of these extensive image datasets.

The package

I developed easyXpress, a software package for the R statistical programming language, to assist in the processing, analysis, and visualization of C. elegans data generated using CellProfiler. easyXpress provides tools for quality control, summarization, and visualization of image-based C. elegans phenotype data. By leveraging existing R infrastructure, easyXpress enables reproducible analysis, integration with other statistical R packages, and extensibility to many research projects using an open-source analysis pipeline.

Additional info

A detailed walk through applying the easyXpress package to a sample dataset can be found here. Details about the publication can be found under publications.