Experimental Design in Differential Abundance analysis (EDDA) is a tool for systematic assessment of the impact of experimental design and the statistical test used on the ability to detect differential abundance. EDDA can aid in the design of a range of common experiments such as RNA-seq, ChIP-seq, Nanostring assays, RIP-seq and Metagenomic sequencing, and enables researchers to comprehensively investigate the impact of experimental decisions on the ability to detect differential abundance. More details of EDDA can be found at Luo, Huaien et al. “The Importance of Study Design for Detecting Differentially Abundant Features in High-Throughput Experiments.” Genome Biology 2014;15(12):527 (http://www.ncbi.nlm.nih.gov/pubmed/25517037/). An accompanying web server (http://edda.gis.a-star.edu.sg/) is available for easy access to some functionality of EDDA. Additionally a Bioconductor package (http://www.bioconductor.org/packages/release/bioc/html/EDDA.html) is available for easy installation of EDDA R package.