Multi-platform evaluation and optimization of single-cell RNA isoform sequencing
James T. WebberiD, Daniel A. BartlettiD, Ghamdan Al‐EryaniiD, Akanksha KhorgadeiD, Asa ShiniD, Christophe GeorgescuiD, Houlin YuiD, Brian J. HaasiD, Victoria PopiciD, Aziz M. Al’KhafajiiD
Abstract
Long-read transcriptomics enables isoform identification and quantification at single-cell resolution, but analysis is complicated by artifacts introduced during library preparation. We characterize the distinct artifact profiles of three popular single-cell platforms and demonstrate their impact on isoform identification. We introduce a new method for the identification of a wide range of artifacts in cDNA libraries and novel biochemical and bioinformatic strategies to significantly reduce their impact on downstream applications. Finally, we provide a comprehensive framework for RNA isoform sequencing analysis and interpretation as the field continues to develop.
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