Title
Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments
Abstract
Motivation: The negative binomial distribution has been shown to be a good model for counts data from both bulk and single-cell RNA-sequencing (RNA-seq). Gaussian process (GP) regression provides a useful non-parametric approach for modelling temporal or spatial changes in gene expression. However, currently available GP regression methods that implement negative binomial likelihood models do not scale to the increasingly large datasets being produced by single-cell and spatial transcriptomics. Results: The GPcounts package implements GP regression methods for modelling counts data using a negative binomial likelihood function. Computational efficiency is achieved through the use of variational Bayesian inference. The GP function models changes in the mean of the negative binomial likelihood through a logarithmic link function and the dispersion parameter is fitted by maximum likelihood. We validate the method on simulated time course data, showing better performance to identify changes in over-dispersed counts data than methods based on Gaussian or Poisson likelihoods. To demonstrate temporal inference, we apply GPcounts to single-cell RNA-seq datasets after pseudotime and branching inference. To demonstrate spatial inference, we apply GPcounts to data from the mouse olfactory bulb to identify spatially variable genes and compare to two published GP methods. We also provide the option of modelling additional dropout using a zero-inflated negative binomial. Our results show that GPcounts can be used to model temporal and spatial counts data in cases where simpler Gaussian and Poisson likelihoods are unrealistic. Supplementary information: Supplementary data are available at Bioinformatics online.
Year
DOI
Venue
2021
10.1093/bioinformatics/btab486
BIOINFORMATICS
DocType
Volume
Issue
Conference
37
21
ISSN
Citations 
PageRank 
1367-4803
1
0.41
References 
Authors
0
7
Name
Order
Citations
PageRank
Nuha BinTayyash110.41
Sokratia Georgaka210.41
ST John310.41
Sumon Ahmed410.75
Alexis Boukouvalas510.41
James Hensman626520.05
Magnus Rattray711.09