Locality Sensitive Imputation for Single-Cell RNA-Seq Data

  • Marmar MoussaEmail author
  • Ion I. Măndoiu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10847)


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.


Single cell RNA-Seq Imputation 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentUniversity of ConnecticutStorrsUSA

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