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Effects of Pseudotime Uncertainty in Downstream Analysis for Single-cell Data: A Case Study

by Sumon Ahmed
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 18
Year of Publication: 2020
Authors: Sumon Ahmed
10.5120/ijca2020920696

Sumon Ahmed . Effects of Pseudotime Uncertainty in Downstream Analysis for Single-cell Data: A Case Study. International Journal of Computer Applications. 175, 18 ( Sep 2020), 1-6. DOI=10.5120/ijca2020920696

@article{ 10.5120/ijca2020920696,
author = { Sumon Ahmed },
title = { Effects of Pseudotime Uncertainty in Downstream Analysis for Single-cell Data: A Case Study },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2020 },
volume = { 175 },
number = { 18 },
month = { Sep },
year = { 2020 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number18/31549-2020920696/ },
doi = { 10.5120/ijca2020920696 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:25:20.904549+05:30
%A Sumon Ahmed
%T Effects of Pseudotime Uncertainty in Downstream Analysis for Single-cell Data: A Case Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 18
%P 1-6
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The analysis of high-throughput single-cell genomics data creates opportunities to uncover the temporal dynamics of cell populations undergoing some complex biological processes such as differentiation and cell division, where the development of bulk-based time course experiments is challenging or technically impossible. One popular approach is to learn a lower-dimensional manifold or trajectory called pseudotime through the data capturing major sources of variation. Most of the current approaches of trajectory inference only provide a point estimate of pseudotime, concealing the consequence of inherent biological and technical noise in single-cell data. Therefore, the intrinsic uncertainty in pseudotime and trajectory inference is not propagated to the downstream and its effects remain unknown. Here three commonly used pseudotime and trajectory inference methods have been discussed along with an important downstream analysis of trajectory inference, i.e. identification of gene-specific branching locations. The alteration of gene-specific branching locations in downstream is illustrated for different pseudotime and trajectory inference methods used in upstream. Finally, A set of recommendations is made that the downstream results or hypotheses should be confirmed using several pseudotime and trajectory inference methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Single-cell gene expression pseudotime trajectory branching

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