  Motivation: P values derived from the null hypothesis significance testing
framework are strongly affected by sample size, and are known to be
irreproducible in underpowered studies, yet no suitable replacement has been
proposed. Results: Here we present implementations of non-parametric
standardized median effect size estimates, dNEF, for high-throughput sequencing
datasets. Case studies are shown for transcriptome and tag-sequencing datasets.
The dNEF measure is shown to be more reproducible and robust than P values and
requires sample sizes as small as 3 to reproducibly identify differentially
abundant features. Availability: Source code and binaries freely available at:
https://bioconductor.org/packages/ALDEx2.html , omicplotR, and
https://github.com/ggloor/CoDaSeq .
