ISSN: 0974-276X
Department of Biotechnology, SunRise University, Alwar, Rajasthan, India
Research Article
BaySiCle: A Bayesian Inference Joint K-Nearest Neighbor Method for Imputation of Single-Cell RNA-Sequencing Data Making use of Local Effect
Author(s): Abhishek Narain Singh* and Krishan Pal
There is a marked technical variability and a high amount of missing observations in the single-cell data that we obtain from experiments. Apart from that clearly each of the batch of experiments have a batch effect on every cell in the batch. This batch effect can be taken into advantage for dealing with imputation, given that all the cells in a given batch belong to the same tissue. Here we introduce ‘BaySiCle’, a novel Bayesian inference based method combined with k-nearest neighbor’s algorithm for the imputation of missing data in scRNA-seq counts. The priors are found out based on expression value across cells for all the single cells of the same batch. We demonstrate using sample scRNA-seq datasets and simulated expression data that BaySiCle allows robust imputation of missing values generating realistic transcript distributions that match single mo.. View More»
DOI:
10.35248/0974-276X.23.16.627