CiLiQuant: Quantification of RNA Junction Reads Based on Their Circular or Linear Transcript Origin

Annelien Morlion; Eva Hulstaert; Jasper Anckaert; Celine Everaert; Jo Vandesompele; Pieter Mestdagh

doi:10.20944/preprints202109.0183.v1

A peer-reviewed article of this Preprint also exists.

Morlion, A.; Hulstaert, E.; Vromman, M.; Anckaert, J.; Everaert, C.; Vandesompele, J.; Mestdagh, P. CiLiQuant: Quantification of RNA Junction Reads Based on Their Circular or Linear Transcript Origin. Frontiers in Bioinformatics, 2022, 2. https://doi.org/10.3389/fbinf.2022.834034. Morlion, A.; Hulstaert, E.; Vromman, M.; Anckaert, J.; Everaert, C.; Vandesompele, J.; Mestdagh, P. CiLiQuant: Quantification of RNA Junction Reads Based on Their Circular or Linear Transcript Origin. Frontiers in Bioinformatics, 2022, 2. https://doi.org/10.3389/fbinf.2022.834034.

Abstract

Distinguishing circular RNA (circRNA) reads from reads derived from the linear host transcript is a challenging task because of sequence overlap. We developed a computational approach, CiLiQuant, that determines the relative circular and linear abundance of transcripts and gene loci using backsplice and forward splice junction reads generated by existing mapping and circRNA discovery tools.

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Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

CiLiQuant: Quantification of RNA Junction Reads Based on Their Circular or Linear Transcript Origin

Abstract

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