Sign in
BioinformaticsMolecular Biology and Evolution
Peer-reviewed journal article

Legacy Data Confounds Genomics Studies

Luke Anderson-TrocméiD, Rick FarouniiD, Mathieu BourgeyiD, Yoichiro KamataniiD, Koichiro HigasaiD, Jeong‐Sun SeoiD, Changhoon KimiD, Fumihiko MatsudaiD, Simon GraveliD

Abstract

Recent reports have identified differences in the mutational spectra across human populations. While some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data is used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower-quality data from the early phases of the 1kGP thus continues to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISKoenig '24Belsare '19Mafessoni '18Robinson '21Groza '20Ausmees '21
52% semantic matchGenomics
Zan Koenig, Mary T. Yohannes, Lethukuthula L. Nkambule+18 more·Genome Research·May 1, 2024· 160 citations