Nature Communications (Mar 2021)

Improving gene function predictions using independent transcriptional components

  • Carlos G. Urzúa-Traslaviña,
  • Vincent C. Leeuwenburgh,
  • Arkajyoti Bhattacharya,
  • Stefan Loipfinger,
  • Marcel A. T. M. van Vugt,
  • Elisabeth G. E. de Vries,
  • Rudolf S. N. Fehrmann

DOI
https://doi.org/10.1038/s41467-021-21671-w
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 14

Abstract

Read online

Our understanding of the function of many transcripts is still incomplete, limiting the interpretability of transcriptomic data. Here the authors use consensus-independent component analysis, together with a guilt-by-association approach, to improve the prediction of gene function.