bio-experimental-design-power-analysis

What problem does it solve?

Planning sequencing studies requires estimating the statistical power and minimum sample sizes to detect meaningful effects in RNA-seq and ATAC-seq data.

Core Features & Use Cases

• Power and sample-size calculations: guidance and example workflows using RNASeqPower and ssizeRNA for RNA-seq and ATAC-seq.
• Study design guidance: practical recommendations for selecting depth, CV, and expected fold changes to meet target power.
• Use Case: design a sequencing experiment to detect a 2-fold change with 80% power at alpha = 0.05, and determine the required replicates.

Quick Start

Ask to compute either the required sample size or achievable power for an RNA-seq or ATAC-seq study by providing depth, CV, expected fold change, and alpha.