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bioRxiv · 10.1101/2021.07.30.454514

Length Biases in Single-Cell RNA Sequencing of pre-mRNA

Gorin, G.·Pachter, L.
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Abstract

Single-molecule pre-mRNA and mRNA sequencing data can be modeled and analyzed using the Markov chain formalism to yield genome-wide insights into transcription. However, quantitative inference with such data requires careful assessment and understanding of noise sources. We find that long pre-mRNA transcripts are over-represented in sequencing data, and explore the mechanistic implications. A biological explanation for this phenomenon within our modeling framework requires unrealistic transcriptional parameters, leading us to posit a length-based model of capture bias. We provide solutions for this model, and use them to find concordant and mechanistically plausible parameter trends across data from multiple single-cell RNA-seq experiments in several species.

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Gorin, G., Pachter, L.. 2021-07-31. Length Biases in Single-Cell RNA Sequencing of pre-mRNA. https://doi.org/10.1101/2021.07.30.454514

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