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bioRxiv · 10.1101/211417

GPseudoRank: MCMC for sampling from posterior distributions of pseudo-orderings using Gaussian processes

Strauss, M. E.·Reid, J. E.·Wernisch, L.
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Abstract

MotivationA number of pseudotime methods have provided point estimates of the ordering of cells for scRNA-seq data. A still limited number of methods also model the uncertainty of the pseudotime estimate. However, there is still a need for a method to sample from complicated and multi-modal distributions of orders, and to estimate changes in the amount of the uncertainty of the order during the course of a biological development, as this can support the selection of suitable cells for the clustering of genes or for network inference.\n\nResultsIn an application to a microarray data set our proposed method, GPseudoRank, identifies two modes of the distribution, each of them corresponding to point estimates of orders obtained by a different established method. In an application to scRNA-seq data we demonstrate the potential of GPseudoRank to identify phases of lower and higher pseudotime uncertainty during a biological process. GPseudoRank also correctly identifies cells precocious in their antiviral response.\n\nAvailability and implementationOur method is available on github: https://github.com/magStra/GPseudoRank.\n\nContactmagdalena.strauss@mrc-bsu.cam.ac.uk\n\nSupplementary informationSupplementary materials are available.

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Strauss, M. E., Reid, J. E., Wernisch, L.. 2017-10-31. GPseudoRank: MCMC for sampling from posterior distributions of pseudo-orderings using Gaussian processes. https://doi.org/10.1101/211417

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