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Dead or alive? Pitfall of survival analysis with TCGA datasets.

Masashi IdogawaMasayo KoizumiTomomi HiranoShoichiro TangeHiroshi NakaseTakashi Tokino
Published in: Cancer biology & therapy (2021)
We often encounter situations in which data from the TCGA that have been analyzed in papers we read or reviewed cannot be reproduced, even when TCGA datasets are used, especially in survival analyses. Therefore, we attempted to confirm the data source for TCGA survival analysis and found that several websites used to analyze the survival data of TCGA datasets inappropriately handle the survival data, causing differences in statistical analyses. This causes the misinterpretation of results because figures of survival analysis results in several papers are sometimes exactly as generated by these sites, and the results depend on only the tools provided by these sites. We would like to make this situation widely known and raise the problem for scientific soundness.
Keyphrases
  • free survival
  • electronic health record
  • big data
  • rna seq
  • deep learning
  • single molecule
  • artificial intelligence