Locality Sensitive Imputation for Single-Cell RNA-Seq Data

Moussa, M.; Mandoiu, I.

doi:10.1101/291807

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bioRxiv · 10.1101/291807

Locality Sensitive Imputation for Single-Cell RNA-Seq Data

Moussa, M.·Mandoiu, I.

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Abstract

One of the most notable challenges in single cell RNA-Seq data analysis is the so called drop-out effect, where only a fraction of the transcriptome of each cell is captured. The random nature of drop-outs, however, makes it possible to consider imputation methods as means of correcting for drop-outs. In this paper we study some existing scRNA-Seq imputation methods and propose a novel iterative imputation approach based on efficiently computing highly similar cells. We then present the results of a comprehensive assessment of existing and proposed methods on real scRNA-Seq datasets with varying per cell sequencing depth.

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Moussa, M., Mandoiu, I.. 2018-03-29. Locality Sensitive Imputation for Single-Cell RNA-Seq Data. https://doi.org/10.1101/291807

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