Login / Signup

Comparative evaluation of full-length isoform quantification from RNA-Seq.

Dimitra SarantopoulouThomas G BrooksSoumyashant NayakAntonijo MrčelaNicholas F LahensGregory R Grant
Published in: BMC bioinformatics (2021)
Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.
Keyphrases
  • rna seq
  • single cell
  • electronic health record
  • big data
  • atomic force microscopy
  • high resolution
  • deep learning
  • high speed