 This paper discusses the importance of analyzing iron-acid datasets from multiple sources to gain more reliable insights into the expression of human endogenous retroviruses, HERV. The authors suggest that increasing the number of reads per sample will help to identify more HERV elements while reducing the impact of batch effects. Additionally, they propose that the use of different sequencing modes and read lengths should not affect the results significantly. This article was authored by Martin B. Hammond, Maisha Adiba and Ulrika Silanga.