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bioRxiv · 10.1101/2020.03.16.994038

Pitfalls in re-analysis of observational omics studies: a post-mortem of the human pathology atlas.

Gilis, J.·Taelman, S.·Davey, L.·Martens, L.·Clement, L.
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Abstract

Uhlen et al. (Reports, 18 august 2017) published an open-access resource with cancer-specific marker genes that are prognostic for patient survival in seventeen different types of cancer. However, their data analysis workflow is prone to the accumulation of false positives. A more reliable workflow with flexible Cox proportional hazards models employed on the same data highlights three distinct problems with such large-scale, publicly available omics datasets from observational studies today: (i) re-analysis results can not necessarily be taken forward by others, highlighting a need to cross-check important analyses with high impact outcomes; (ii) current methods are not necessarily optimal for the re-analysis of such data, indicating an urgent need to develop more suitable methods; and (iii) the limited availability of potential confounders in public metadata renders it very difficult (if not impossible) to adequately prioritize clinically relevant genes, which should prompt an in-depth discussion on how such information could be made more readily available while respecting privacy and ethics concerns.

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Gilis, J., Taelman, S., Davey, L., Martens, L., Clement, L.. 2020-03-18. Pitfalls in re-analysis of observational omics studies: a post-mortem of the human pathology atlas.. https://doi.org/10.1101/2020.03.16.994038

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