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Optimizing murine sample sizes for RNA-seq studies revealed from large-scale comparative analysis

ABSTRACT: In order to determine the N, the usual approach is to perform a power calculation, which involves understanding the variability between samples and the expected effect size. Here, we focused on bulk RNA-seq experiments, which have become ubiquitous in biology, but which have many unknown or difficult to estimate parameters, and so the required analyses to determine the minimum N is typically lacking. We therefore performed two N=30 profiling studies between wild-type mice and mice in which one copy of a gene had been deleted, to determine how many mice would be required to minimize false positives and to maximize true discoveries found in the N of 30 experiment

ORGANISM(S): Mus musculus

PROVIDER: GSE272152 | GEO | 2025/01/06

REPOSITORIES: GEO

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